Economic impacts of climate change on agriculture: the AgMIP approach

NASA Astrophysics Data System (ADS)

Delincé, Jacques; Ciaian, Pavel; Witzke, Heinz-Peter

2015-01-01

The current paper investigates the long-term global impacts on crop productivity under different climate scenarios using the AgMIP approach (Agricultural Model Intercomparison and Improvement Project). The paper provides horizontal model intercomparison from 11 economic models as well as a more detailed analysis of the simulated effects from the Common Agricultural Policy Regionalized Impact (CAPRI) model to systematically compare its performance with other AgMIP models and specifically for the Chinese agriculture. CAPRI is a comparative static partial equilibrium model extensively used for medium and long-term economic and environmental policy impact applications. The results indicate that, at the global level, the climate change will cause an agricultural productivity decrease (between -2% and -15% by 2050), a food price increase (between 1.3% and 56%) and an expansion of cultivated area (between 1% and 4%) by 2050. The results for China indicate that the climate change effects tend to be smaller than the global impacts. The CAPRI-simulated effects are, in general, close to the median across all AgMIP models. Model intercomparison analyses reveal consistency in terms of direction of change to climate change but relatively strong heterogeneity in the magnitude of the effects between models.

Pliocene Model Intercomparison (PlioMIP) Phase 2: Scientific Objectives and Experimental Design

NASA Technical Reports Server (NTRS)

Haywood, A. M.; Dowsett, H. J.; Dolan, A. M.; Rowley, D.; Abe-Ouchi, A.; Otto-Bliesner, B.; Chandler, M. A.; Hunter, S. J.; Lunt, D. J.; Pound, M.;

Pliocene Model Intercomparison Project (PlioMIP): Experimental Design and Boundary Conditions (Experiment 2)

NASA Technical Reports Server (NTRS)

Haywood, A. M.; Dowsett, H. J.; Robinson, M. M.; Stoll, D. K.; Dolan, A. M.; Lunt, D. J.; Otto-Bliesner, B.; Chandler, M. A.

2011-01-01

The Palaeoclimate Modelling Intercomparison Project has expanded to include a model intercomparison for the mid-Pliocene warm period (3.29 to 2.97 million yr ago). This project is referred to as PlioMIP (the Pliocene Model Intercomparison Project). Two experiments have been agreed upon and together compose the initial phase of PlioMIP. The first (Experiment 1) is being performed with atmosphere only climate models. The second (Experiment 2) utilizes fully coupled ocean-atmosphere climate models. Following on from the publication of the experimental design and boundary conditions for Experiment 1 in Geoscientific Model Development, this paper provides the necessary description of differences and/or additions to the experimental design for Experiment 2.

Pliocene Model Intercomparison Project (PlioMIP): experimental design and boundary conditions (Experiment 2)

USGS Publications Warehouse

Haywood, A.M.; Dowsett, H.J.; Robinson, M.M.; Stoll, D.K.; Dolan, A.M.; Lunt, D.J.; Otto-Bliesner, B.; Chandler, M.A.

2011-01-01

The Palaeoclimate Modelling Intercomparison Project has expanded to include a model intercomparison for the mid-Pliocene warm period (3.29 to 2.97 million yr ago). This project is referred to as PlioMIP (the Pliocene Model Intercomparison Project). Two experiments have been agreed upon and together compose the initial phase of PlioMIP. The first (Experiment 1) is being performed with atmosphere-only climate models. The second (Experiment 2) utilises fully coupled ocean-atmosphere climate models. Following on from the publication of the experimental design and boundary conditions for Experiment 1 in Geoscientific Model Development, this paper provides the necessary description of differences and/or additions to the experimental design for Experiment 2.

Subglacial Hydrology Model Intercomparison Project (SHMIP)

NASA Astrophysics Data System (ADS)

Werder, Mauro A.; de Fleurian, Basile; Creyts, Timothy T.; Damsgaard, Anders; Delaney, Ian; Dow, Christine F.; Gagliardini, Olivier; Hoffman, Matthew J.; Seguinot, Julien; Sommers, Aleah; Irarrazaval Bustos, Inigo; Downs, Jakob

2017-04-01

The SHMIP project is the first intercomparison project of subglacial drainage models (http://shmip.bitbucket.org). Its synthetic test suites and evaluation were designed such that any subglacial hydrology model producing effective pressure can participate. In contrast to ice deformation, the physical processes of subglacial hydrology (which in turn impacts basal sliding of glaciers) are poorly known. A further complication is that different glacial and geological settings can lead to different drainage physics. The aim of the project is therefore to qualitatively compare the outputs of the participating models for a wide range of water forcings and glacier geometries. This will allow to put existing studies, which use different drainage models, into context and will allow new studies to select the most suitable model for the problem at hand. We present the results from the just completed intercomparison exercise. Twelve models participated: eight 2D and four 1D models; nine include both an efficient and inefficient system, the other three one of the systems; all but two models use R-channels as efficient system, and/or a linked-cavity like inefficient system, one exception uses porous layers with different characteristic for each of the systems, the other exception is based on canals. The main variable used for the comparison is effective pressure, as that is a direct proxy for basal sliding of glaciers. The models produce large differences in the effective pressure fields, in particular for higher water input scenarios. This shows that the selection of a subglacial drainage model will likely impact the conclusions of a study significantly.

The Inter-Sectoral Impact Model Intercomparison Project (ISI–MIP): Project framework

PubMed Central

Warszawski, Lila; Frieler, Katja; Huber, Veronika; Piontek, Franziska; Serdeczny, Olivia; Schewe, Jacob

2014-01-01

The Inter-Sectoral Impact Model Intercomparison Project offers a framework to compare climate impact projections in different sectors and at different scales. Consistent climate and socio-economic input data provide the basis for a cross-sectoral integration of impact projections. The project is designed to enable quantitative synthesis of climate change impacts at different levels of global warming. This report briefly outlines the objectives and framework of the first, fast-tracked phase of Inter-Sectoral Impact Model Intercomparison Project, based on global impact models, and provides an overview of the participating models, input data, and scenario set-up. PMID:24344316

Estimating near-road pollutant dispersion: a model inter-comparison

EPA Science Inventory

A model inter-comparison study to assess the abilities of steady-state Gaussian dispersion models to capture near-road pollutant dispersion has been carried out with four models (AERMOD, run with both the area-source and volume-source options to represent roadways, CALINE, versio...

THE NORTH AMERICAN MERCURY MODEL INTER-COMPARISON STUDY (NAMMIS)

EPA Science Inventory

This paper describes the North American Mercury Model Inter-comparison Study (NAMMIS). The NAMMIS is an effort to apply atmospheric Hg models in a tightly constrained testing environment with a focus on North America. With each model using the same input data sets for initial co...

The Program for climate Model diagnosis and Intercomparison: 20-th anniversary Symposium

DOE Office of Scientific and Technical Information (OSTI.GOV)

Potter, Gerald L; Bader, David C; Riches, Michael

Twenty years ago, W. Lawrence (Larry) Gates approached the U.S. Department of Energy (DOE) Office of Energy Research (now the Office of Science) with a plan to coordinate the comparison and documentation of climate model differences. This effort would help improve our understanding of climate change through a systematic approach to model intercomparison. Early attempts at comparing results showed a surprisingly large range in control climate from such parameters as cloud cover, precipitation, and even atmospheric temperature. The DOE agreed to fund the effort at the Lawrence Livermore National Laboratory (LLNL), in part because of the existing computing environment andmore » because of a preexisting atmospheric science group that contained a wide variety of expertise. The project was named the Program for Climate Model Diagnosis and Intercomparison (PCMDI), and it has changed the international landscape of climate modeling over the past 20 years. In spring 2009 the DOE hosted a 1-day symposium to celebrate the twentieth anniversary of PCMDI and to honor its founder, Larry Gates. Through their personal experiences, the morning presenters painted an image of climate science in the 1970s and 1980s, that generated early support from the international community for model intercomparison, thereby bringing PCMDI into existence. Four talks covered Gates's early contributions to climate research at the University of California, Los Angeles (UCLA), the RAND Corporation, and Oregon State University through the founding of PCMDI to coordinate the Atmospheric Model Intercomparison Project (AMIP). The speakers were, in order of presentation, Warren Washington [National Center for Atmospheric Research (NCAR)], Kelly Redmond (Western Regional Climate Center), George Boer (Canadian Centre for Climate Modelling and Analysis), and Lennart Bengtsson [University of Reading, former director of the European Centre for Medium-Range Weather Forecasts (ECMWF)]. The afternoon session

INTERCOMPARISON STUDY OF ATMOSPHERIC MERCURY MODELS: 1. COMPARISON OF MODELS WITH SHORT-TERM MEASUREMENTS

EPA Science Inventory

Five regional scale models with a horizontal domain covering the European continent and its surrounding seas, one hemispheric and one global scale model participated in an atmospheric mercury modelling intercomparison study. Model-predicted concentrations in ambient air were comp...

Evaluation of Intercomparisons of Four Different Types of Model Simulating TWP-ICE

NASA Technical Reports Server (NTRS)

Petch, Jon; Hill, Adrian; Davies, Laura; Fridlind, Ann; Jakob, Christian; Lin, Yanluan; Xie, Shaoecheng; Zhu, Ping

2013-01-01

Four model intercomparisons were run and evaluated using the TWP-ICE field campaign, each involving different types of atmospheric model. Here we highlight what can be learnt from having single-column model (SCM), cloud-resolving model (CRM), global atmosphere model (GAM) and limited-area model (LAM) intercomparisons all based around the same field campaign. We also make recommendations for anyone planning further large multi-model intercomparisons to ensure they are of maximum value to the model development community. CRMs tended to match observations better than other model types, although there were exceptions such as outgoing long-wave radiation. All SCMs grew large temperature and moisture biases and performed worse than other model types for many diagnostics. The GAMs produced a delayed and significantly reduced peak in domain-average rain rate when compared to the observations. While it was shown that this was in part due to the analysis used to drive these models, the LAMs were also driven by this analysis and did not have the problem to the same extent. Based on differences between the models with parametrized convection (SCMs and GAMs) and those without (CRMs and LAMs), we speculate that that having explicit convection helps to constrain liquid water whereas the ice contents are controlled more by the representation of the microphysics.

A soil sampling intercomparison exercise for the ALMERA network.

PubMed

Belli, Maria; de Zorzi, Paolo; Sansone, Umberto; Shakhashiro, Abduhlghani; Gondin da Fonseca, Adelaide; Trinkl, Alexander; Benesch, Thomas

2009-11-01

Soil sampling and analysis for radionuclides after an accidental or routine release is a key factor for the dose calculation to members of the public, and for the establishment of possible countermeasures. The IAEA organized for selected laboratories of the ALMERA (Analytical Laboratories for the Measurement of Environmental Radioactivity) network a Soil Sampling Intercomparison Exercise (IAEA/SIE/01) with the objective of comparing soil sampling procedures used by different laboratories. The ALMERA network is a world-wide network of analytical laboratories located in IAEA member states capable of providing reliable and timely analysis of environmental samples in the event of an accidental or intentional release of radioactivity. Ten ALMERA laboratories were selected to participate in the sampling exercise. The soil sampling intercomparison exercise took place in November 2005 in an agricultural area qualified as a "reference site", aimed at assessing the uncertainties associated with soil sampling in agricultural, semi-natural, urban and contaminated environments and suitable for performing sampling intercomparison. In this paper, the laboratories sampling performance were evaluated.

The Southern Ocean in the Coupled Model Intercomparison Project phase 5

PubMed Central

Meijers, A. J. S.

2014-01-01

The Southern Ocean is an important part of the global climate system, but its complex coupled nature makes both its present state and its response to projected future climate forcing difficult to model. Clear trends in wind, sea-ice extent and ocean properties emerged from multi-model intercomparison in the Coupled Model Intercomparison Project phase 3 (CMIP3). Here, we review recent analyses of the historical and projected wind, sea ice, circulation and bulk properties of the Southern Ocean in the updated Coupled Model Intercomparison Project phase 5 (CMIP5) ensemble. Improvements to the models include higher resolutions, more complex and better-tuned parametrizations of ocean mixing, and improved biogeochemical cycles and atmospheric chemistry. CMIP5 largely reproduces the findings of CMIP3, but with smaller inter-model spreads and biases. By the end of the twenty-first century, mid-latitude wind stresses increase and shift polewards. All water masses warm, and intermediate waters freshen, while bottom waters increase in salinity. Surface mixed layers shallow, warm and freshen, whereas sea ice decreases. The upper overturning circulation intensifies, whereas bottom water formation is reduced. Significant disagreement exists between models for the response of the Antarctic Circumpolar Current strength, for reasons that are as yet unclear. PMID:24891395

The Joint Experiment for Crop Assessment and Monitoring (JECAM): Synthetic Aperture Radar (SAR) Inter-Comparison Experiment

NASA Astrophysics Data System (ADS)

Dingle Robertson, L.; Hosseini, M.; Davidson, A. M.; McNairn, H.

2017-12-01

The Joint Experiment for Crop Assessment and Monitoring (JECAM) is the research and development branch of GEOGLAM (Group on Earth Observations Global Agricultural Monitoring), a G20 initiative to improve the global monitoring of agriculture through the use of Earth Observation (EO) data and remote sensing. JECAM partners represent a diverse network of researchers collaborating towards a set of best practices and recommendations for global agricultural analysis using EO data, with well monitored test sites covering a wide range of agriculture types, cropping systems and climate regimes. Synthetic Aperture Radar (SAR) for crop inventory and condition monitoring offers many advantages particularly the ability to collect data under cloudy conditions. The JECAM SAR Inter-Comparison Experiment is a multi-year, multi-partner project that aims to compare global methods for (1) operational SAR & optical; multi-frequency SAR; and compact polarimetry methods for crop monitoring and inventory, and (2) the retrieval of Leaf Area Index (LAI) and biomass estimations using models such as the Water Cloud Model (WCM) employing single frequency SAR; multi-frequency SAR; and compact polarimetry. The results from these activities will be discussed along with an examination of the requirements of a global experiment including best-date determination for SAR data acquisition, pre-processing techniques, in situ data sharing, model development and statistical inter-comparison of the results.

The Pliocene Model Intercomparison Project - Phase 2

NASA Astrophysics Data System (ADS)

Haywood, Alan; Dowsett, Harry; Dolan, Aisling; Rowley, David; Abe-Ouchi, Ayako; Otto-Bliesner, Bette; Chandler, Mark; Hunter, Stephen; Lunt, Daniel; Pound, Matthew; Salzmann, Ulrich

2016-04-01

The Pliocene Model Intercomparison Project (PlioMIP) is a co-ordinated international climate modelling initiative to study and understand climate and environments of the Late Pliocene, and their potential relevance in the context of future climate change. PlioMIP examines the consistency of model predictions in simulating Pliocene climate, and their ability to reproduce climate signals preserved by geological climate archives. Here we provide a description of the aim and objectives of the next phase of the model intercomparison project (PlioMIP Phase 2), and we present the experimental design and boundary conditions that will be utilised for climate model experiments in Phase 2. Following on from PlioMIP Phase 1, Phase 2 will continue to be a mechanism for sampling structural uncertainty within climate models. However, Phase 1 demonstrated the requirement to better understand boundary condition uncertainties as well as uncertainty in the methodologies used for data-model comparison. Therefore, our strategy for Phase 2 is to utilise state-of-the-art boundary conditions that have emerged over the last 5 years. These include a new palaeogeographic reconstruction, detailing ocean bathymetry and land/ice surface topography. The ice surface topography is built upon the lessons learned from offline ice sheet modelling studies. Land surface cover has been enhanced by recent additions of Pliocene soils and lakes. Atmospheric reconstructions of palaeo-CO2 are emerging on orbital timescales and these are also incorporated into PlioMIP Phase 2. New records of surface and sea surface temperature change are being produced that will be more temporally consistent with the boundary conditions and forcings used within models. Finally we have designed a suite of prioritized experiments that tackle issues surrounding the basic understanding of the Pliocene and its relevance in the context of future climate change in a discrete way.

Design and results of the ice sheet model initialisation experiments initMIP-Greenland: an ISMIP6 intercomparison

NASA Astrophysics Data System (ADS)

Goelzer, Heiko; Nowicki, Sophie; Edwards, Tamsin; Beckley, Matthew; Abe-Ouchi, Ayako; Aschwanden, Andy; Calov, Reinhard; Gagliardini, Olivier; Gillet-Chaulet, Fabien; Golledge, Nicholas R.; Gregory, Jonathan; Greve, Ralf; Humbert, Angelika; Huybrechts, Philippe; Kennedy, Joseph H.; Larour, Eric; Lipscomb, William H.; Le clec'h, Sébastien; Lee, Victoria; Morlighem, Mathieu; Pattyn, Frank; Payne, Antony J.; Rodehacke, Christian; Rückamp, Martin; Saito, Fuyuki; Schlegel, Nicole; Seroussi, Helene; Shepherd, Andrew; Sun, Sainan; van de Wal, Roderik; Ziemen, Florian A.

2018-04-01

Earlier large-scale Greenland ice sheet sea-level projections (e.g. those run during the ice2sea and SeaRISE initiatives) have shown that ice sheet initial conditions have a large effect on the projections and give rise to important uncertainties. The goal of this initMIP-Greenland intercomparison exercise is to compare, evaluate, and improve the initialisation techniques used in the ice sheet modelling community and to estimate the associated uncertainties in modelled mass changes. initMIP-Greenland is the first in a series of ice sheet model intercomparison activities within ISMIP6 (the Ice Sheet Model Intercomparison Project for CMIP6), which is the primary activity within the Coupled Model Intercomparison Project Phase 6 (CMIP6) focusing on the ice sheets. Two experiments for the large-scale Greenland ice sheet have been designed to allow intercomparison between participating models of (1) the initial present-day state of the ice sheet and (2) the response in two idealised forward experiments. The forward experiments serve to evaluate the initialisation in terms of model drift (forward run without additional forcing) and in response to a large perturbation (prescribed surface mass balance anomaly); they should not be interpreted as sea-level projections. We present and discuss results that highlight the diversity of data sets, boundary conditions, and initialisation techniques used in the community to generate initial states of the Greenland ice sheet. We find good agreement across the ensemble for the dynamic response to surface mass balance changes in areas where the simulated ice sheets overlap but differences arising from the initial size of the ice sheet. The model drift in the control experiment is reduced for models that participated in earlier intercomparison exercises.

Design and results of the ice sheet model initialisation experiments initMIP-Greenland: an ISMIP6 intercomparison

DOE PAGES

Goelzer, Heiko; Nowicki, Sophie; Edwards, Tamsin; ...

2018-04-19

Earlier large-scale Greenland ice sheet sea-level projections (e.g. those run during the ice2sea and SeaRISE initiatives) have shown that ice sheet initial conditions have a large effect on the projections and give rise to important uncertainties. Here, the goal of this initMIP-Greenland intercomparison exercise is to compare, evaluate, and improve the initialisation techniques used in the ice sheet modelling community and to estimate the associated uncertainties in modelled mass changes. initMIP-Greenland is the first in a series of ice sheet model intercomparison activities within ISMIP6 (the Ice Sheet Model Intercomparison Project for CMIP6), which is the primary activity within themore » Coupled Model Intercomparison Project Phase 6 (CMIP6) focusing on the ice sheets. Two experiments for the large-scale Greenland ice sheet have been designed to allow intercomparison between participating models of (1) the initial present-day state of the ice sheet and (2) the response in two idealised forward experiments. The forward experiments serve to evaluate the initialisation in terms of model drift (forward run without additional forcing) and in response to a large perturbation (prescribed surface mass balance anomaly); they should not be interpreted as sea-level projections. We present and discuss results that highlight the diversity of data sets, boundary conditions, and initialisation techniques used in the community to generate initial states of the Greenland ice sheet. We find good agreement across the ensemble for the dynamic response to surface mass balance changes in areas where the simulated ice sheets overlap but differences arising from the initial size of the ice sheet. The model drift in the control experiment is reduced for models that participated in earlier intercomparison exercises.« less

Design and results of the ice sheet model initialisation experiments initMIP-Greenland: an ISMIP6 intercomparison

DOE Office of Scientific and Technical Information (OSTI.GOV)

Goelzer, Heiko; Nowicki, Sophie; Edwards, Tamsin

Earlier large-scale Greenland ice sheet sea-level projections (e.g. those run during the ice2sea and SeaRISE initiatives) have shown that ice sheet initial conditions have a large effect on the projections and give rise to important uncertainties. Here, the goal of this initMIP-Greenland intercomparison exercise is to compare, evaluate, and improve the initialisation techniques used in the ice sheet modelling community and to estimate the associated uncertainties in modelled mass changes. initMIP-Greenland is the first in a series of ice sheet model intercomparison activities within ISMIP6 (the Ice Sheet Model Intercomparison Project for CMIP6), which is the primary activity within themore » Coupled Model Intercomparison Project Phase 6 (CMIP6) focusing on the ice sheets. Two experiments for the large-scale Greenland ice sheet have been designed to allow intercomparison between participating models of (1) the initial present-day state of the ice sheet and (2) the response in two idealised forward experiments. The forward experiments serve to evaluate the initialisation in terms of model drift (forward run without additional forcing) and in response to a large perturbation (prescribed surface mass balance anomaly); they should not be interpreted as sea-level projections. We present and discuss results that highlight the diversity of data sets, boundary conditions, and initialisation techniques used in the community to generate initial states of the Greenland ice sheet. We find good agreement across the ensemble for the dynamic response to surface mass balance changes in areas where the simulated ice sheets overlap but differences arising from the initial size of the ice sheet. The model drift in the control experiment is reduced for models that participated in earlier intercomparison exercises.« less

Ice Sheet Model Intercomparison Project (ISMIP6) contribution to CMIP6

PubMed Central

Nowicki, Sophie M.J.; Payne, Tony; Larour, Eric; Seroussi, Helene; Goelzer, Heiko; Lipscomb, William; Gregory, Jonathan; Abe-Ouchi, Ayako; Shepherd, Andrew

2018-01-01

Reducing the uncertainty in the past, present and future contribution of ice sheets to sea-level change requires a coordinated effort between the climate and glaciology communities. The Ice Sheet Model Intercomparison Project for CMIP6 (ISMIP6) is the primary activity within the Coupled Model Intercomparison Project – phase 6 (CMIP6) focusing on the Greenland and Antarctic Ice Sheets. In this paper, we describe the framework for ISMIP6 and its relationship to other activities within CMIP6. The ISMIP6 experimental design relies on CMIP6 climate models and includes, for the first time within CMIP, coupled ice sheet – climate models as well as standalone ice sheet models. To facilitate analysis of the multi-model ensemble and to generate a set of standard climate inputs for standalone ice sheet models, ISMIP6 defines a protocol for all variables related to ice sheets. ISMIP6 will provide a basis for investigating the feedbacks, impacts, and sea-level changes associated with dynamic ice sheets and for quantifying the uncertainty in ice-sheet-sourced global sea-level change. PMID:29697697

Ice Sheet Model Intercomparison Project (ISMIP6) Contribution to CMIP6

NASA Technical Reports Server (NTRS)

Nowicki, Sophie M. J.; Payne, Tony; Larour, Eric; Seroussi, Helene; Goelzer, Heiko; Lipscomb, William; Gregory, Jonathan; Abe-Ouchi, Ayako; Shepherd, Andrew

2016-01-01

Reducing the uncertainty in the past, present, and future contribution of ice sheets to sea-level change requires a coordinated effort between the climate and glaciology communities. The Ice Sheet Model Intercomparison Project for CMIP6 (ISMIP6) is the primary activity within the Coupled Model Intercomparison Project phase 6 (CMIP6) focusing on the Greenland and Antarctic ice sheets. In this paper, we describe the framework for ISMIP6 and its relationship with other activities within CMIP6. The ISMIP6 experimental design relies on CMIP6 climate models and includes, for the first time within CMIP, coupled ice-sheetclimate models as well as standalone ice-sheet models. To facilitate analysis of the multi-model ensemble and to generate a set of standard climate inputs for standalone ice-sheet models, ISMIP6 defines a protocol for all variables related to ice sheets. ISMIP6 will provide a basis for investigating the feedbacks, impacts, and sea-level changes associated with dynamic ice sheets and for quantifying the uncertainty in ice-sheet-sourced global sea-level change.

Inter-comparison of three-dimensional models of volcanic plumes

USGS Publications Warehouse

Suzuki, Yujiro; Costa, Antonio; Cerminara, Matteo; Esposti Ongaro, Tomaso; Herzog, Michael; Van Eaton, Alexa; Denby, Leif

2016-01-01

We performed an inter-comparison study of three-dimensional models of volcanic plumes. A set of common volcanological input parameters and meteorological conditions were provided for two kinds of eruptions, representing a weak and a strong eruption column. From the different models, we compared the maximum plume height, neutral buoyancy level (where plume density equals that of the atmosphere), and level of maximum radial spreading of the umbrella cloud. We also compared the vertical profiles of eruption column properties, integrated across cross-sections of the plume (integral variables). Although the models use different numerical procedures and treatments of subgrid turbulence and particle dynamics, the inter-comparison shows qualitatively consistent results. In the weak plume case (mass eruption rate 1.5 × 106 kg s− 1), the vertical profiles of plume properties (e.g., vertical velocity, temperature) are similar among models, especially in the buoyant plume region. Variability among the simulated maximum heights is ~ 20%, whereas neutral buoyancy level and level of maximum radial spreading vary by ~ 10%. Time-averaging of the three-dimensional (3D) flow fields indicates an effective entrainment coefficient around 0.1 in the buoyant plume region, with much lower values in the jet region, which is consistent with findings of small-scale laboratory experiments. On the other hand, the strong plume case (mass eruption rate 1.5 × 109 kg s− 1) shows greater variability in the vertical plume profiles predicted by the different models. Our analysis suggests that the unstable flow dynamics in the strong plume enhances differences in the formulation and numerical solution of the models. This is especially evident in the overshooting top of the plume, which extends a significant portion (~ 1/8) of the maximum plume height. Nonetheless, overall variability in the spreading level and neutral buoyancy level is ~ 20%, whereas that of maximum height is ~ 10

Representative Agricultural Pathways and Scenarios for Regional Integrated Assessment of Climate Change Impacts, Vulnerability, and Adaptation. 5; Chapter

NASA Technical Reports Server (NTRS)

Valdivia, Roberto O.; Antle, John M.; Rosenzweig, Cynthia; Ruane, Alexander C.; Vervoort, Joost; Ashfaq, Muhammad; Hathie, Ibrahima; Tui, Sabine Homann-Kee; Mulwa, Richard; Nhemachena, Charles;

An AgMIP framework for improved agricultural representation in integrated assessment models

NASA Astrophysics Data System (ADS)

Ruane, Alex C.; Rosenzweig, Cynthia; Asseng, Senthold; Boote, Kenneth J.; Elliott, Joshua; Ewert, Frank; Jones, James W.; Martre, Pierre; McDermid, Sonali P.; Müller, Christoph; Snyder, Abigail; Thorburn, Peter J.

2017-12-01

Integrated assessment models (IAMs) hold great potential to assess how future agricultural systems will be shaped by socioeconomic development, technological innovation, and changing climate conditions. By coupling with climate and crop model emulators, IAMs have the potential to resolve important agricultural feedback loops and identify unintended consequences of socioeconomic development for agricultural systems. Here we propose a framework to develop robust representation of agricultural system responses within IAMs, linking downstream applications with model development and the coordinated evaluation of key climate responses from local to global scales. We survey the strengths and weaknesses of protocol-based assessments linked to the Agricultural Model Intercomparison and Improvement Project (AgMIP), each utilizing multiple sites and models to evaluate crop response to core climate changes including shifts in carbon dioxide concentration, temperature, and water availability, with some studies further exploring how climate responses are affected by nitrogen levels and adaptation in farm systems. Site-based studies with carefully calibrated models encompass the largest number of activities; however they are limited in their ability to capture the full range of global agricultural system diversity. Representative site networks provide more targeted response information than broadly-sampled networks, with limitations stemming from difficulties in covering the diversity of farming systems. Global gridded crop models provide comprehensive coverage, although with large challenges for calibration and quality control of inputs. Diversity in climate responses underscores that crop model emulators must distinguish between regions and farming system while recognizing model uncertainty. Finally, to bridge the gap between bottom-up and top-down approaches we recommend the deployment of a hybrid climate response system employing a representative network of sites to bias

IPRT polarized radiative transfer model intercomparison project - Phase A

NASA Astrophysics Data System (ADS)

Emde, Claudia; Barlakas, Vasileios; Cornet, Céline; Evans, Frank; Korkin, Sergey; Ota, Yoshifumi; Labonnote, Laurent C.; Lyapustin, Alexei; Macke, Andreas; Mayer, Bernhard; Wendisch, Manfred

2015-10-01

The polarization state of electromagnetic radiation scattered by atmospheric particles such as aerosols, cloud droplets, or ice crystals contains much more information about the optical and microphysical properties than the total intensity alone. For this reason an increasing number of polarimetric observations are performed from space, from the ground and from aircraft. Polarized radiative transfer models are required to interpret and analyse these measurements and to develop retrieval algorithms exploiting polarimetric observations. In the last years a large number of new codes have been developed, mostly for specific applications. Benchmark results are available for specific cases, but not for more sophisticated scenarios including polarized surface reflection and multi-layer atmospheres. The International Polarized Radiative Transfer (IPRT) working group of the International Radiation Commission (IRC) has initiated a model intercomparison project in order to fill this gap. This paper presents the results of the first phase A of the IPRT project which includes ten test cases, from simple setups with only one layer and Rayleigh scattering to rather sophisticated setups with a cloud embedded in a standard atmosphere above an ocean surface. All scenarios in the first phase A of the intercomparison project are for a one-dimensional plane-parallel model geometry. The commonly established benchmark results are available at the IPRT website.

Radiative-convective equilibrium model intercomparison project

NASA Astrophysics Data System (ADS)

Wing, Allison A.; Reed, Kevin A.; Satoh, Masaki; Stevens, Bjorn; Bony, Sandrine; Ohno, Tomoki

2018-03-01

RCEMIP, an intercomparison of multiple types of models configured in radiative-convective equilibrium (RCE), is proposed. RCE is an idealization of the climate system in which there is a balance between radiative cooling of the atmosphere and heating by convection. The scientific objectives of RCEMIP are three-fold. First, clouds and climate sensitivity will be investigated in the RCE setting. This includes determining how cloud fraction changes with warming and the role of self-aggregation of convection in climate sensitivity. Second, RCEMIP will quantify the dependence of the degree of convective aggregation and tropical circulation regimes on temperature. Finally, by providing a common baseline, RCEMIP will allow the robustness of the RCE state across the spectrum of models to be assessed, which is essential for interpreting the results found regarding clouds, climate sensitivity, and aggregation, and more generally, determining which features of tropical climate a RCE framework is useful for. A novel aspect and major advantage of RCEMIP is the accessibility of the RCE framework to a variety of models, including cloud-resolving models, general circulation models, global cloud-resolving models, single-column models, and large-eddy simulation models.

An AgMIP framework for improved agricultural representation in integrated assessment models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ruane, Alex C.; Rosenzweig, Cynthia; Asseng, Senthold

Integrated assessment models (IAMs) hold great potential to assess how future agricultural systems will be shaped by socioeconomic development, technological innovation, and changing climate conditions. By coupling with climate and crop model emulators, IAMs have the potential to resolve important agricultural feedback loops and identify unintended consequences of socioeconomic development for agricultural systems. Here we propose a framework to develop robust representation of agricultural system responses within IAMs, linking downstream applications with model development and the coordinated evaluation of key climate responses from local to global scales. We survey the strengths and weaknesses of protocol-based assessments linked to the Agriculturalmore » Model Intercomparison and Improvement Project (AgMIP), each utilizing multiple sites and models to evaluate crop response to core climate changes including shifts in carbon dioxide concentration, temperature, and water availability, with some studies further exploring how climate responses are affected by nitrogen levels and adaptation in farm systems. Site-based studies with carefully calibrated models encompass the largest number of activities; however they are limited in their ability to capture the full range of global agricultural system diversity. Representative site networks provide more targeted response information than broadly-sampled networks, with limitations stemming from difficulties in covering the diversity of farming systems. Global gridded crop models provide comprehensive coverage, although with large challenges for calibration and quality control of inputs. Diversity in climate responses underscores that crop model emulators must distinguish between regions and farming system while recognizing model uncertainty. Finally, to bridge the gap between bottom-up and top-down approaches we recommend the deployment of a hybrid climate response system employing a representative network of sites to

Radiance and Jacobian Intercomparison of Radiative Transfer Models Applied to HIRS and AMSU Channels

NASA Technical Reports Server (NTRS)

Garand, L.; Turner, D. S.; Larocque, M.; Bates, J.; Boukabara, S.; Brunel, P.; Chevallier, F.; Deblonde, G.; Engelen, R.; Hollingshead, M.;

Radiance and Jacobian Intercomparison of Radiative Transfer Models Applied to HIRS and AMSU Channels

NASA Technical Reports Server (NTRS)

Garand, L.; Turner, D. S.; Larocque, M.; Bates, J.; Boukabara, S.; Brunel, P.; Chevallier, F.; Deblonde, G.; Engelen, R.; Atlas, Robert (Technical Monitor)

2000-01-01

The goals of this study are the evaluation of current fast radiative transfer models (RTMs) and line-by-line (LBL) models. The intercomparison focuses on the modeling of 11 representative sounding channels routinely used at numerical weather prediction centers: seven HIRS (High-resolution Infrared Sounder) and four AMSU (Advanced Microwave Sounding Unit) channels. Interest in this topic was evidenced by the participation of 24 scientists from 16 institutions. An ensemble of 42 diverse atmospheres was used and results compiled for 19 infrared models and 10 microwave models, including several LBL RTMs. For the first time, not only radiances, but also Jacobians (of temperature, water vapor, and ozone) were compared to various LBL models for many channels. In the infrared, LBL models typically agree to within 0.05-0.15 K (standard deviation) in terms of top-of-the-atmosphere brightness temperature (BT). Individual differences up to 0.5 K still exist, systematic in some channels, and linked to the type of atmosphere in others. The best fast models emulate LBL BTs to within 0.25 K, but no model achieves this desirable level of success for all channels. The ozone modeling is particularly challenging. In the microwave, fast models generally do quite well against the LBL model to which they were tuned. However significant differences were noted among LBL models. Extending the intercomparison to the Jacobians proved very useful in detecting subtle and more obvious modeling errors. In addition, total and single gas optical depths were calculated, which provided additional insight on the nature of differences. Recommendations for future intercomparisons are suggested.

New Results from the Geoengineering Model Intercomparison Project (GeoMIP)

NASA Astrophysics Data System (ADS)

Robock, A.; Kravitz, B.

2013-12-01

The Geoengineering Model Intercomparison Project (GeoMIP) was designed to determine robust climate system model responses to Solar Radiation Management (SRM). While mitigation (reducing greenhouse gases emissions) is the most effective way of reducing future climate change, SRM (the deliberate modification of incoming solar radiation) has been proposed as a means of temporarily alleviating some of the effects of global warming. For society to make informed decisions as to whether SRM should ever be implemented, information is needed on the benefits, risks, and side effects, and GeoMIP seeks to aid in that endeavor. GeoMIP has organized four standardized climate model simulations involving reduction of insolation or increased amounts of stratospheric sulfate aerosols to counteract increasing greenhouse gases. Thirteen comprehensive atmosphere-ocean general circulation models have participated in the project so far. GeoMIP is a 'CMIP Coordinated Experiment' as part of the Climate Model Intercomparison Project 5 (CMIP5) and has been endorsed by SPARC (Stratosphere-troposphere Processes And their Role in Climate). GeoMIP has held three international workshops and has produced a number of recent journal articles. GeoMIP has found that if increasing greenhouse gases could be counteracted with insolation reduction, the global average temperature could be kept constant, but global average precipitation would reduce, particularly in summer monsoon regions around the world. Temperature changes would also not be uniform. The tropics would cool, but high latitudes would warm, with continuing, but reduced sea ice and ice sheet melting. Temperature extremes would still increase, but not as much as without SRM. If SRM were halted all at once, there would be rapid temperature and precipitation increases at 5-10 times the rates from gradual global warming. SRM combined with CO2 fertilization would have small impacts on rice production in China, but would increase maize production

Intercomparison and interpretation of climate feedback processes in 19 atmospheric general circulation models

NASA Technical Reports Server (NTRS)

Cess, R. D.; Potter, G. L.; Blanchet, J. P.; Boer, G. J.; Del Genio, A. D.

1990-01-01

The present study provides an intercomparison and interpretation of climate feedback processes in 19 atmospheric general circulation models. This intercomparison uses sea surface temperature change as a surrogate for climate change. The interpretation of cloud-climate interactions is given special attention. A roughly threefold variation in one measure of global climate sensitivity is found among the 19 models. The important conclusion is that most of this variation is attributable to differences in the models' depiction of cloud feedback, a result that emphasizes the need for improvements in the treatment of clouds in these models if they are ultimately to be used as reliable climate predictors. It is further emphazied that cloud feedback is the consequence of all interacting physical and dynamical processes in a general circulation model. The result of these processes is to produce changes in temperature, moisture distribution, and clouds which are integrated into the radiative response termed cloud feedback.

INTERCOMPARISON STUDY OF ATMOSPHERIC MERCURY MODELS: 2. MODELING RESULTS VS. LONG-TERM OBSERVATIONS AND COMPARISON OF COUNTRY ATMOSPHERIC BALANCES

EPA Science Inventory

Five regional scale models with a horizontal domain covering the European continent and its surrounding seas, two hemispheric and one global scale model participated in the atmospheric Hg modelling intercomparison study. The models were compared between each other and with availa...

Applying the World Water and Agriculture Model to Filling Scenarios for the Grand Ethiopian Renaissance Dam

DOE Office of Scientific and Technical Information (OSTI.GOV)

Villa, Daniel L.; Tidwell, Vincent C.; Passell, Howard D.

The World Water and Agriculture Model has been used to simulate water, hydropower, and food sector effects in Egypt, Sudan, and Ethiopia during the filling of the Grand Ethiopian Renaissance Dam reservoir. This unique capability allows tradeoffs to be made between filling policies for the Grand Ethiopian Renaissance Dam reservoir. This Nile River Basin study is presented to illustrate the capacity to use the World Water and Agriculture Model to simulate regional food security issues while keeping a global perspective. The study uses runoff data from the Intergovernmental Panel for Climate Change Coupled Model Inter-comparison Project Phase 5 and informationmore » from the literature in order to establish a reasonable set of hydrological initial conditions. Gross Domestic Product and population growth are modelled exogenously based on a composite projection of United Nations and World Bank data. The effects of the Grand Ethiopian Renaissance Dam under various percentages of water withheld are presented.« less

An intercomparison of models used to simulate the short-range atmospheric dispersion of agricultural ammonia emissions

EPA Science Inventory

Ammonia emitted into the atmosphere from agricultural sources can have an impact on nearby sensitive ecosystems either through elevated ambient concentrations or dry/wet deposition to vegetation and soil surfaces. Short-range atmospheric dispersion models are often used to assess...

Inter-comparison of dynamic models for radionuclide transfer to marine biota in a Fukushima accident scenario

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vives i Batlle, J.; Beresford, N. A.; Beaugelin-Seiller, K.

We report an inter-comparison of eight models designed to predict the radiological exposure of radionuclides in marine biota. The models were required to simulate dynamically the uptake and turnover of radionuclides by marine organisms. Model predictions of radionuclide uptake and turnover using kinetic calculations based on biological half-life (TB1/2) and/or more complex metabolic modelling approaches were used to predict activity concentrations and, consequently, dose rates of 90Sr, 131I and 137Cs to fish, crustaceans, macroalgae and molluscs under circumstances where the water concentrations are changing with time. For comparison, the ERICA Tool, a model commonly used in environmental assessment, and whichmore » uses equilibrium concentration ratios, was also used. As input to the models we used hydrodynamic forecasts of water and sediment activity concentrations using a simulated scenario reflecting the Fukushima accident releases. Although model variability is important, the intercomparison gives logical results, in that the dynamic models predict consistently a pattern of delayed rise of activity concentration in biota and slow decline instead of the instantaneous equilibrium with the activity concentration in seawater predicted by the ERICA Tool. The differences between ERICA and the dynamic models increase the shorter the TB1/2 becomes; however, there is significant variability between models, underpinned by parameter and methodological differences between them. The need to validate the dynamic models used in this intercomparison has been highlighted, particularly in regards to optimisation of the model biokinetic parameters.« less

GMMIP (v1.0) contribution to CMIP6: Global Monsoons Model Inter-comparison Project

NASA Astrophysics Data System (ADS)

Zhou, Tianjun; Turner, Andrew G.; Kinter, James L.; Wang, Bin; Qian, Yun; Chen, Xiaolong; Wu, Bo; Wang, Bin; Liu, Bo; Zou, Liwei; He, Bian

2016-10-01

The Global Monsoons Model Inter-comparison Project (GMMIP) has been endorsed by the panel of Coupled Model Inter-comparison Project (CMIP) as one of the participating model inter-comparison projects (MIPs) in the sixth phase of CMIP (CMIP6). The focus of GMMIP is on monsoon climatology, variability, prediction and projection, which is relevant to four of the "Grand Challenges" proposed by the World Climate Research Programme. At present, 21 international modeling groups are committed to joining GMMIP. This overview paper introduces the motivation behind GMMIP and the scientific questions it intends to answer. Three tiers of experiments, of decreasing priority, are designed to examine (a) model skill in simulating the climatology and interannual-to-multidecadal variability of global monsoons forced by the sea surface temperature during historical climate period; (b) the roles of the Interdecadal Pacific Oscillation and Atlantic Multidecadal Oscillation in driving variations of the global and regional monsoons; and (c) the effects of large orographic terrain on the establishment of the monsoons. The outputs of the CMIP6 Diagnostic, Evaluation and Characterization of Klima experiments (DECK), "historical" simulation and endorsed MIPs will also be used in the diagnostic analysis of GMMIP to give a comprehensive understanding of the roles played by different external forcings, potential improvements in the simulation of monsoon rainfall at high resolution and reproducibility at decadal timescales. The implementation of GMMIP will improve our understanding of the fundamental physics of changes in the global and regional monsoons over the past 140 years and ultimately benefit monsoons prediction and projection in the current century.

A protocol for the intercomparison of marine fishery and ecosystem models: Fish-MIP v1.0

NASA Astrophysics Data System (ADS)

Tittensor, Derek P.; Eddy, Tyler D.; Lotze, Heike K.; Galbraith, Eric D.; Cheung, William; Barange, Manuel; Blanchard, Julia L.; Bopp, Laurent; Bryndum-Buchholz, Andrea; Büchner, Matthias; Bulman, Catherine; Carozza, David A.; Christensen, Villy; Coll, Marta; Dunne, John P.; Fernandes, Jose A.; Fulton, Elizabeth A.; Hobday, Alistair J.; Huber, Veronika; Jennings, Simon; Jones, Miranda; Lehodey, Patrick; Link, Jason S.; Mackinson, Steve; Maury, Olivier; Niiranen, Susa; Oliveros-Ramos, Ricardo; Roy, Tilla; Schewe, Jacob; Shin, Yunne-Jai; Silva, Tiago; Stock, Charles A.; Steenbeek, Jeroen; Underwood, Philip J.; Volkholz, Jan; Watson, James R.; Walker, Nicola D.

2018-04-01

Model intercomparison studies in the climate and Earth sciences communities have been crucial to building credibility and coherence for future projections. They have quantified variability among models, spurred model development, contrasted within- and among-model uncertainty, assessed model fits to historical data, and provided ensemble projections of future change under specified scenarios. Given the speed and magnitude of anthropogenic change in the marine environment and the consequent effects on food security, biodiversity, marine industries, and society, the time is ripe for similar comparisons among models of fisheries and marine ecosystems. Here, we describe the Fisheries and Marine Ecosystem Model Intercomparison Project protocol version 1.0 (Fish-MIP v1.0), part of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP), which is a cross-sectoral network of climate impact modellers. Given the complexity of the marine ecosystem, this class of models has substantial heterogeneity of purpose, scope, theoretical underpinning, processes considered, parameterizations, resolution (grain size), and spatial extent. This heterogeneity reflects the lack of a unified understanding of the marine ecosystem and implies that the assemblage of all models is more likely to include a greater number of relevant processes than any single model. The current Fish-MIP protocol is designed to allow these heterogeneous models to be forced with common Earth System Model (ESM) Coupled Model Intercomparison Project Phase 5 (CMIP5) outputs under prescribed scenarios for historic (from the 1950s) and future (to 2100) time periods; it will be adapted to CMIP phase 6 (CMIP6) in future iterations. It also describes a standardized set of outputs for each participating Fish-MIP model to produce. This enables the broad characterization of differences between and uncertainties within models and projections when assessing climate and fisheries impacts on marine ecosystems and the

Large-Scale Features of Pliocene Climate: Results from the Pliocene Model Intercomparison Project

NASA Technical Reports Server (NTRS)

Haywood, A. M.; Hill, D.J.; Dolan, A. M.; Otto-Bliesner, B. L.; Bragg, F.; Chan, W.-L.; Chandler, M. A.; Contoux, C.; Dowsett, H. J.; Jost, A.;

IPRT polarized radiative transfer model intercomparison project - Three-dimensional test cases (phase B)

NASA Astrophysics Data System (ADS)

Emde, Claudia; Barlakas, Vasileios; Cornet, Céline; Evans, Frank; Wang, Zhen; Labonotte, Laurent C.; Macke, Andreas; Mayer, Bernhard; Wendisch, Manfred

2018-04-01

Initially unpolarized solar radiation becomes polarized by scattering in the Earth's atmosphere. In particular molecular scattering (Rayleigh scattering) polarizes electromagnetic radiation, but also scattering of radiation at aerosols, cloud droplets (Mie scattering) and ice crystals polarizes. Each atmospheric constituent produces a characteristic polarization signal, thus spectro-polarimetric measurements are frequently employed for remote sensing of aerosol and cloud properties. Retrieval algorithms require efficient radiative transfer models. Usually, these apply the plane-parallel approximation (PPA), assuming that the atmosphere consists of horizontally homogeneous layers. This allows to solve the vector radiative transfer equation (VRTE) efficiently. For remote sensing applications, the radiance is considered constant over the instantaneous field-of-view of the instrument and each sensor element is treated independently in plane-parallel approximation, neglecting horizontal radiation transport between adjacent pixels (Independent Pixel Approximation, IPA). In order to estimate the errors due to the IPA approximation, three-dimensional (3D) vector radiative transfer models are required. So far, only a few such models exist. Therefore, the International Polarized Radiative Transfer (IPRT) working group of the International Radiation Commission (IRC) has initiated a model intercomparison project in order to provide benchmark results for polarized radiative transfer. The group has already performed an intercomparison for one-dimensional (1D) multi-layer test cases [phase A, 1]. This paper presents the continuation of the intercomparison project (phase B) for 2D and 3D test cases: a step cloud, a cubic cloud, and a more realistic scenario including a 3D cloud field generated by a Large Eddy Simulation (LES) model and typical background aerosols. The commonly established benchmark results for 3D polarized radiative transfer are available at the IPRT website (http

Inter-comparison of dynamic models for radionuclide transfer to marine biota in a Fukushima accident scenario.

PubMed

Vives I Batlle, J; Beresford, N A; Beaugelin-Seiller, K; Bezhenar, R; Brown, J; Cheng, J-J; Ćujić, M; Dragović, S; Duffa, C; Fiévet, B; Hosseini, A; Jung, K T; Kamboj, S; Keum, D-K; Kryshev, A; LePoire, D; Maderich, V; Min, B-I; Periáñez, R; Sazykina, T; Suh, K-S; Yu, C; Wang, C; Heling, R

2016-03-01

We report an inter-comparison of eight models designed to predict the radiological exposure of radionuclides in marine biota. The models were required to simulate dynamically the uptake and turnover of radionuclides by marine organisms. Model predictions of radionuclide uptake and turnover using kinetic calculations based on biological half-life (TB1/2) and/or more complex metabolic modelling approaches were used to predict activity concentrations and, consequently, dose rates of (90)Sr, (131)I and (137)Cs to fish, crustaceans, macroalgae and molluscs under circumstances where the water concentrations are changing with time. For comparison, the ERICA Tool, a model commonly used in environmental assessment, and which uses equilibrium concentration ratios, was also used. As input to the models we used hydrodynamic forecasts of water and sediment activity concentrations using a simulated scenario reflecting the Fukushima accident releases. Although model variability is important, the intercomparison gives logical results, in that the dynamic models predict consistently a pattern of delayed rise of activity concentration in biota and slow decline instead of the instantaneous equilibrium with the activity concentration in seawater predicted by the ERICA Tool. The differences between ERICA and the dynamic models increase the shorter the TB1/2 becomes; however, there is significant variability between models, underpinned by parameter and methodological differences between them. The need to validate the dynamic models used in this intercomparison has been highlighted, particularly in regards to optimisation of the model biokinetic parameters. Copyright © 2015 Elsevier Ltd. All rights reserved.

An Analysis of Simulated Wet Deposition of Mercury from the North American Mercury Model Intercomparison Study

EPA Science Inventory

A previous intercomparison of atmospheric mercury models in North America has been extended to compare simulated and observed wet deposition of mercury. Three regional-scale atmospheric mercury models were tested; CMAQ, REMSAD and TEAM. These models were each employed using thr...

GMMIP (v1.0) contribution to CMIP6: Global Monsoons Model Inter-comparison Project

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, Tianjun; Turner, Andrew G.; Kinter, James L.

The Global Monsoons Model Inter-comparison Project (GMMIP) has been endorsed by the panel of Coupled Model Inter-comparison Project (CMIP) as one of the participating model inter-comparison projects (MIPs) in the sixth phase of CMIP (CMIP6). The focus of GMMIP is on monsoon climatology, variability, prediction and projection, which is relevant to four of the “Grand Challenges” proposed by the World Climate Research Programme. At present, 21 international modeling groups are committed to joining GMMIP. This overview paper introduces the motivation behind GMMIP and the scientific questions it intends to answer. Three tiers of experiments, of decreasing priority, are designed to examinemore » (a) model skill in simulating the climatology and interannual-to-multidecadal variability of global monsoons forced by the sea surface temperature during historical climate period; (b) the roles of the Interdecadal Pacific Oscillation and Atlantic Multidecadal Oscillation in driving variations of the global and regional monsoons; and (c) the effects of large orographic terrain on the establishment of the monsoons. The outputs of the CMIP6 Diagnostic, Evaluation and Characterization of Klima experiments (DECK), “historical” simulation and endorsed MIPs will also be used in the diagnostic analysis of GMMIP to give a comprehensive understanding of the roles played by different external forcings, potential improvements in the simulation of monsoon rainfall at high resolution and reproducibility at decadal timescales. The implementation of GMMIP will improve our understanding of the fundamental physics of changes in the global and regional monsoons over the past 140 years and ultimately benefit monsoons prediction and projection in the current century.« less

The CMIP6 Sea-Ice Model Intercomparison Project (SIMIP): Understanding sea ice through climate-model simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Notz, Dirk; Jahn, Alexandra; Holland, Marika

A better understanding of the role of sea ice for the changing climate of our planet is the central aim of the diagnostic Coupled Model Intercomparison Project 6 (CMIP6)-endorsed Sea-Ice Model Intercomparison Project (SIMIP). To reach this aim, SIMIP requests sea-ice-related variables from climate-model simulations that allow for a better understanding and, ultimately, improvement of biases and errors in sea-ice simulations with large-scale climate models. This then allows us to better understand to what degree CMIP6 model simulations relate to reality, thus improving our confidence in answering sea-ice-related questions based on these simulations. Furthermore, the SIMIP protocol provides a standardmore » for sea-ice model output that will streamline and hence simplify the analysis of the simulated sea-ice evolution in research projects independent of CMIP. To reach its aims, SIMIP provides a structured list of model output that allows for an examination of the three main budgets that govern the evolution of sea ice, namely the heat budget, the momentum budget, and the mass budget. Furthermore, we explain the aims of SIMIP in more detail and outline how its design allows us to answer some of the most pressing questions that sea ice still poses to the international climate-research community.« less

The CMIP6 Sea-Ice Model Intercomparison Project (SIMIP): Understanding sea ice through climate-model simulations

DOE PAGES

Notz, Dirk; Jahn, Alexandra; Holland, Marika; ...

2016-09-23

A better understanding of the role of sea ice for the changing climate of our planet is the central aim of the diagnostic Coupled Model Intercomparison Project 6 (CMIP6)-endorsed Sea-Ice Model Intercomparison Project (SIMIP). To reach this aim, SIMIP requests sea-ice-related variables from climate-model simulations that allow for a better understanding and, ultimately, improvement of biases and errors in sea-ice simulations with large-scale climate models. This then allows us to better understand to what degree CMIP6 model simulations relate to reality, thus improving our confidence in answering sea-ice-related questions based on these simulations. Furthermore, the SIMIP protocol provides a standardmore » for sea-ice model output that will streamline and hence simplify the analysis of the simulated sea-ice evolution in research projects independent of CMIP. To reach its aims, SIMIP provides a structured list of model output that allows for an examination of the three main budgets that govern the evolution of sea ice, namely the heat budget, the momentum budget, and the mass budget. Furthermore, we explain the aims of SIMIP in more detail and outline how its design allows us to answer some of the most pressing questions that sea ice still poses to the international climate-research community.« less

Agricultural response functions to changes in carbon, temperature, and water based on the C3MP data set

NASA Astrophysics Data System (ADS)

Snyder, A.; Ruane, A. C.; Phillips, M.; Calvin, K. V.; Clarke, L.

2017-12-01

Agricultural yields vary depending on temperature, precipitation/irrigation conditions, fertilizer application, and CO2 concentration. The Coordinated Climate-Crop Modeling Project (C3MP), conducted as a component of the Agricultural Model Intercomparison and Improvement Project (AgMIP), organized a sensitivity experiments across carbon-temperature-water (CTW) space across 1100 management conditions in 50+ countries, sampling 15 crop species and 20 crop models. Such coordinated sensitivity tests allow for the building of emulators of yield response to changes in CTW values, allowing rapid estimation of yield changes from the types of climate changes projected by the climate modeling community. The resulting emulator may be used to supply agricultural responses to climate change in any user-defined scenario, rather than the restriction to the RCPs in many past works. We present the resulting emulators built from the C3MP output data set for use in the Global Change Assessment Model (GCAM) integrated assessment model that allows for the co-evolution of socioeconomic development, greenhouse gas emissions, climate change, and agricultural sector ramifications. C3MP-based emulators may be of use in designing agricultural impact studies in other IAMs, and we place them in the context of past crop modeling efforts, including the Challinor et al. Meta-analysis, the AgMIP Wheat team results, the AgMIP Global Gridded Crop Model Intercomparison (GGCMI) fast-track modeling results, and the MACSUR impact response surface results.

Biogeochemical Protocols and Diagnostics for the CMIP6 Ocean Model Intercomparison Project (OMIP)

NASA Technical Reports Server (NTRS)

Orr, James C.; Najjar, Raymond G.; Aumont, Olivier; Bopp, Laurent; Bullister, John L.; Danabasoglu, Gokhan; Doney, Scott C.; Dunne, John P.; Dutay, Jean-Claude; Graven, Heather;

Biogeochemical protocols and diagnostics for the CMIP6 Ocean Model Intercomparison Project (OMIP)

NASA Astrophysics Data System (ADS)

Orr, James C.; Najjar, Raymond G.; Aumont, Olivier; Bopp, Laurent; Bullister, John L.; Danabasoglu, Gokhan; Doney, Scott C.; Dunne, John P.; Dutay, Jean-Claude; Graven, Heather; Griffies, Stephen M.; John, Jasmin G.; Joos, Fortunat; Levin, Ingeborg; Lindsay, Keith; Matear, Richard J.; McKinley, Galen A.; Mouchet, Anne; Oschlies, Andreas; Romanou, Anastasia; Schlitzer, Reiner; Tagliabue, Alessandro; Tanhua, Toste; Yool, Andrew

2017-06-01

The Ocean Model Intercomparison Project (OMIP) focuses on the physics and biogeochemistry of the ocean component of Earth system models participating in the sixth phase of the Coupled Model Intercomparison Project (CMIP6). OMIP aims to provide standard protocols and diagnostics for ocean models, while offering a forum to promote their common assessment and improvement. It also offers to compare solutions of the same ocean models when forced with reanalysis data (OMIP simulations) vs. when integrated within fully coupled Earth system models (CMIP6). Here we detail simulation protocols and diagnostics for OMIP's biogeochemical and inert chemical tracers. These passive-tracer simulations will be coupled to ocean circulation models, initialized with observational data or output from a model spin-up, and forced by repeating the 1948-2009 surface fluxes of heat, fresh water, and momentum. These so-called OMIP-BGC simulations include three inert chemical tracers (CFC-11, CFC-12, SF6) and biogeochemical tracers (e.g., dissolved inorganic carbon, carbon isotopes, alkalinity, nutrients, and oxygen). Modelers will use their preferred prognostic BGC model but should follow common guidelines for gas exchange and carbonate chemistry. Simulations include both natural and total carbon tracers. The required forced simulation (omip1) will be initialized with gridded observational climatologies. An optional forced simulation (omip1-spunup) will be initialized instead with BGC fields from a long model spin-up, preferably for 2000 years or more, and forced by repeating the same 62-year meteorological forcing. That optional run will also include abiotic tracers of total dissolved inorganic carbon and radiocarbon, CTabio and 14CTabio, to assess deep-ocean ventilation and distinguish the role of physics vs. biology. These simulations will be forced by observed atmospheric histories of the three inert gases and CO2 as well as carbon isotope ratios of CO2. OMIP-BGC simulation protocols are

Smoke and Emissions Model Intercomparison Project (SEMIP)

NASA Astrophysics Data System (ADS)

Larkin, N. K.; Raffuse, S.; Strand, T.; Solomon, R.; Sullivan, D.; Wheeler, N.

2008-12-01

Fire emissions and smoke impacts from wildland fire are a growing concern due to increasing fire season severity, dwindling tolerance of smoke by the public, tightening air quality regulations, and their role in climate change issues. Unfortunately, while a number of models and modeling system solutions are available to address these issues, the lack of quantitative information on the limitations and difference between smoke and emissions models impedes the use of these tools for real-world applications (JFSP, 2007). We describe a new, open-access project to directly address this issue, the open-access Smoke Emissions Model Intercomparison Project (SEMIP) and invite the community to participate. Preliminary work utilizing the modular BlueSky framework to directly compare fire location and size information, fuel loading amounts, fuel consumption rates, and fire emissions from a number of current models that has found model-to-model variability as high as two orders of magnitude for an individual fire. Fire emissions inventories also show significant variability on both regional and national scales that are dependant on the fire location information used (ground report vs. satellite), the fuel loading maps assumed, and the fire consumption models employed. SEMIP expands on this work and creates an open-access database of model results and observations with the goal of furthering model development and model prediction usability for real-world decision support.

A Bootstrap Algorithm for Mixture Models and Interval Data in Inter-Comparisons

DTIC Science & Technology

2001-07-01

parametric bootstrap. The present algorithm will be applied to a thermometric inter-comparison, where data cannot be assumed to be normally distributed. 2 Data...experimental methods, used in each laboratory) often imply that the statistical assumptions are not satisfied, as for example in several thermometric ...triangular). Indeed, in thermometric experiments these three probabilistic models can represent several common stochastic variabilities for

Constraints and potentials of future irrigation water availability on agricultural production under climate change.

PubMed

Elliott, Joshua; Deryng, Delphine; Müller, Christoph; Frieler, Katja; Konzmann, Markus; Gerten, Dieter; Glotter, Michael; Flörke, Martina; Wada, Yoshihide; Best, Neil; Eisner, Stephanie; Fekete, Balázs M; Folberth, Christian; Foster, Ian; Gosling, Simon N; Haddeland, Ingjerd; Khabarov, Nikolay; Ludwig, Fulco; Masaki, Yoshimitsu; Olin, Stefan; Rosenzweig, Cynthia; Ruane, Alex C; Satoh, Yusuke; Schmid, Erwin; Stacke, Tobias; Tang, Qiuhong; Wisser, Dominik

2014-03-04

We compare ensembles of water supply and demand projections from 10 global hydrological models and six global gridded crop models. These are produced as part of the Inter-Sectoral Impacts Model Intercomparison Project, with coordination from the Agricultural Model Intercomparison and Improvement Project, and driven by outputs of general circulation models run under representative concentration pathway 8.5 as part of the Fifth Coupled Model Intercomparison Project. Models project that direct climate impacts to maize, soybean, wheat, and rice involve losses of 400-1,400 Pcal (8-24% of present-day total) when CO2 fertilization effects are accounted for or 1,400-2,600 Pcal (24-43%) otherwise. Freshwater limitations in some irrigated regions (western United States; China; and West, South, and Central Asia) could necessitate the reversion of 20-60 Mha of cropland from irrigated to rainfed management by end-of-century, and a further loss of 600-2,900 Pcal of food production. In other regions (northern/eastern United States, parts of South America, much of Europe, and South East Asia) surplus water supply could in principle support a net increase in irrigation, although substantial investments in irrigation infrastructure would be required.

Model Intercomparison of CCN-Limited Arctic Clouds During ASCOS

NASA Astrophysics Data System (ADS)

Stevens, Robin; Dearden, Chris; Dimetrelos, Antonios; Eirund, Gesa; Possner, Anna; Raatikainen, Tomi; Loewe, Katharina; Hill, Adrian; Shipway, Ben; Connolly, Paul; Ekman, Annica; Hoose, Corinna; Laaksonen, Ari; de Leeuw, Gerrit; Kolmonen, Pekka; Saponaro, Giulia; Field, Paul; Carlsaw, Ken

2017-04-01

Future decreases in Arctic sea ice are expected to increase fluxes of aerosol and precursor gases from the open ocean surface within the Arctic. The resulting increase in cloud condensation nuclei (CCN) concentrations would be expected to result in increased cloud albedo (Struthers et al, 2011), leading to potentially large changes in radiative forcings. However, Browse et al. (2014) have shown that these increases in condensable material could also result in the growth of existing particles to sizes where they are more efficiently removed by wet deposition in drizzling stratocumulus clouds, ultimately decreasing CCN concentrations in the high Arctic. Their study was limited in that it did not simulate alterations of dynamics or cloud properties due to either changes in heat and moisture fluxes following sea­-ice loss or changing aerosol concentrations. Taken together, these results show that significant uncertainties remain in trying to quantify aerosol­-cloud processes in the Arctic system. The current representation of these processes in global climate models is most likely insufficient to realistically simulate long­-term changes. In order to better understand the microphysical processes currently governing Arctic clouds, we perform a model intercomparison of summertime high Arctic (>80N) clouds observed during the 2008 ASCOS campaign. The intercomparison includes results from three large eddy simulation models (UCLALES-SALSA, COSMO-LES, and MIMICA) and three numerical weather prediction models (COSMO-NWP, WRF, and UM-CASIM). The results of these experiments will be used as a basis for sensitivity studies on the impact of sea-ice loss on Arctic clouds through changes in aerosol and precursor emissions as well as changes in latent and sensible heat fluxes. Browse, J., et al., Atmos. Chem. Phys., 14(14), 7543-7557, doi:10.5194/acp-14-7543-2014, 2014. Struthers, H., et al., Atmos. Chem. Phys., 11(7), 3459-3477, doi:10.5194/acp-11-3459-2011, 2011.

Climate Forcing Datasets for Agricultural Modeling: Merged Products for Gap-Filling and Historical Climate Series Estimation

NASA Technical Reports Server (NTRS)

Ruane, Alex C.; Goldberg, Richard; Chryssanthacopoulos, James

2014-01-01

The AgMERRA and AgCFSR climate forcing datasets provide daily, high-resolution, continuous, meteorological series over the 1980-2010 period designed for applications examining the agricultural impacts of climate variability and climate change. These datasets combine daily resolution data from retrospective analyses (the Modern-Era Retrospective Analysis for Research and Applications, MERRA, and the Climate Forecast System Reanalysis, CFSR) with in situ and remotely-sensed observational datasets for temperature, precipitation, and solar radiation, leading to substantial reductions in bias in comparison to a network of 2324 agricultural-region stations from the Hadley Integrated Surface Dataset (HadISD). Results compare favorably against the original reanalyses as well as the leading climate forcing datasets (Princeton, WFD, WFD-EI, and GRASP), and AgMERRA distinguishes itself with substantially improved representation of daily precipitation distributions and extreme events owing to its use of the MERRA-Land dataset. These datasets also peg relative humidity to the maximum temperature time of day, allowing for more accurate representation of the diurnal cycle of near-surface moisture in agricultural models. AgMERRA and AgCFSR enable a number of ongoing investigations in the Agricultural Model Intercomparison and Improvement Project (AgMIP) and related research networks, and may be used to fill gaps in historical observations as well as a basis for the generation of future climate scenarios.

The Joint Experiment for Crop Assessment and Monitoring (JECAM): Update on Multisite Inter-comparison Experiments

NASA Astrophysics Data System (ADS)

Jarvis, I.; Gilliams, S. J. B.; Defourny, P.

2016-12-01

Globally there is significant convergence on agricultural monitoring research questions. The focus of interest usually revolves around crop type, crop area estimation and near real time crop condition and yield forecasting. Notwithstanding this convergence, agricultural systems differ significantly throughout the world, reflecting the diversity of ecosystems they are located in. Consequently, a global system of systems for operational monitoring must be based on multiple approaches. Research is required to compare and assess these approaches to identify which are most appropriate for any given location. To this end the Joint Experiments for Crop Assessment and Monitoring (JECAM) was established in 2009 to as a research platform to allow the global agricultural monitoring community to work towards a set of best practices and recommendations for using earth observation data to map, monitor and report on agricultural productivity globally. The JECAM initiative brings together researchers from a large number of globally distributed, well monitored agricultural test sites that cover a range of crop types, cropping systems and climate regimes. The results of JECAM optical inter-comparison research taking place in the Stimulating Innovation for Global Monitoring of Agriculture (SIGMA) project and the Sentinel-2 for Agriculture project will be discussed. The presentation will also highlight upcoming work on a Synthetic Aperture Radar (SAR) inter-comparison study. The outcome of these projects will result in a set of best practices that cover the range of remote sensing monitoring and reporting needs, including satellite data acquisition, pre-processing techniques, information retrieval and ground data validation. These outcomes provide the R&D foundation for GEOGLAM and will help to inform the development of the GEOGLAM system of systems for global agricultural monitoring.

The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6

DOE PAGES

O'Neill, Brian C.; Tebaldi, Claudia; van Vuuren, Detlef P.; ...

2016-09-28

Projections of future climate change play a fundamental role in improving understanding of the climate system as well as characterizing societal risks and response options. The Scenario Model Intercomparison Project (ScenarioMIP) is the primary activity within Phase 6 of the Coupled Model Intercomparison Project (CMIP6) that will provide multi-model climate projections based on alternative scenarios of future emissions and land use changes produced with integrated assessment models. Here, we describe ScenarioMIP's objectives, experimental design, and its relation to other activities within CMIP6. The ScenarioMIP design is one component of a larger scenario process that aims to facilitate a wide rangemore » of integrated studies across the climate science, integrated assessment modeling, and impacts, adaptation, and vulnerability communities, and will form an important part of the evidence base in the forthcoming Intergovernmental Panel on Climate Change (IPCC) assessments. Furthermore, it will provide the basis for investigating a number of targeted science and policy questions that are especially relevant to scenario-based analysis, including the role of specific forcings such as land use and aerosols, the effect of a peak and decline in forcing, the consequences of scenarios that limit warming to below 2°C, the relative contributions to uncertainty from scenarios, climate models, and internal variability, and long-term climate system outcomes beyond the 21st century. In order to serve this wide range of scientific communities and address these questions, a design has been identified consisting of eight alternative 21st century scenarios plus one large initial condition ensemble and a set of long-term extensions, divided into two tiers defined by relative priority. Some of these scenarios will also provide a basis for variants planned to be run in other CMIP6-Endorsed MIPs to investigate questions related to specific forcings. Harmonized, spatially explicit

The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6

DOE Office of Scientific and Technical Information (OSTI.GOV)

O'Neill, Brian C.; Tebaldi, Claudia; van Vuuren, Detlef P.

2016-01-01

Projections of future climate change play a fundamental role in improving understanding of the climate system as well as characterizing societal risks and response options. The Scenario Model Intercomparison Project (ScenarioMIP) is the primary activity within Phase 6 of the Coupled Model Intercomparison Project (CMIP6) that will provide multi-model climate projections based on alternative scenarios of future emissions and land use changes produced with integrated assessment models. In this paper, we describe ScenarioMIP's objectives, experimental design, and its relation to other activities within CMIP6. The ScenarioMIP design is one component of a larger scenario process that aims to facilitate amore » wide range of integrated studies across the climate science, integrated assessment modeling, and impacts, adaptation, and vulnerability communities, and will form an important part of the evidence base in the forthcoming Intergovernmental Panel on Climate Change (IPCC) assessments. At the same time, it will provide the basis for investigating a number of targeted science and policy questions that are especially relevant to scenario-based analysis, including the role of specific forcings such as land use and aerosols, the effect of a peak and decline in forcing, the consequences of scenarios that limit warming to below 2 °C, the relative contributions to uncertainty from scenarios, climate models, and internal variability, and long-term climate system outcomes beyond the 21st century. To serve this wide range of scientific communities and address these questions, a design has been identified consisting of eight alternative 21st century scenarios plus one large initial condition ensemble and a set of long-term extensions, divided into two tiers defined by relative priority. Some of these scenarios will also provide a basis for variants planned to be run in other CMIP6-Endorsed MIPs to investigate questions related to specific forcings. Harmonized, spatially

The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6

NASA Astrophysics Data System (ADS)

O'Neill, Brian C.; Tebaldi, Claudia; van Vuuren, Detlef P.; Eyring, Veronika; Friedlingstein, Pierre; Hurtt, George; Knutti, Reto; Kriegler, Elmar; Lamarque, Jean-Francois; Lowe, Jason; Meehl, Gerald A.; Moss, Richard; Riahi, Keywan; Sanderson, Benjamin M.

2016-09-01

Projections of future climate change play a fundamental role in improving understanding of the climate system as well as characterizing societal risks and response options. The Scenario Model Intercomparison Project (ScenarioMIP) is the primary activity within Phase 6 of the Coupled Model Intercomparison Project (CMIP6) that will provide multi-model climate projections based on alternative scenarios of future emissions and land use changes produced with integrated assessment models. In this paper, we describe ScenarioMIP's objectives, experimental design, and its relation to other activities within CMIP6. The ScenarioMIP design is one component of a larger scenario process that aims to facilitate a wide range of integrated studies across the climate science, integrated assessment modeling, and impacts, adaptation, and vulnerability communities, and will form an important part of the evidence base in the forthcoming Intergovernmental Panel on Climate Change (IPCC) assessments. At the same time, it will provide the basis for investigating a number of targeted science and policy questions that are especially relevant to scenario-based analysis, including the role of specific forcings such as land use and aerosols, the effect of a peak and decline in forcing, the consequences of scenarios that limit warming to below 2 °C, the relative contributions to uncertainty from scenarios, climate models, and internal variability, and long-term climate system outcomes beyond the 21st century. To serve this wide range of scientific communities and address these questions, a design has been identified consisting of eight alternative 21st century scenarios plus one large initial condition ensemble and a set of long-term extensions, divided into two tiers defined by relative priority. Some of these scenarios will also provide a basis for variants planned to be run in other CMIP6-Endorsed MIPs to investigate questions related to specific forcings. Harmonized, spatially explicit

The Cloud Feedback Model Intercomparison Project Observational Simulator Package: Version 2

NASA Astrophysics Data System (ADS)

Swales, Dustin J.; Pincus, Robert; Bodas-Salcedo, Alejandro

2018-01-01

The Cloud Feedback Model Intercomparison Project Observational Simulator Package (COSP) gathers together a collection of observation proxies or satellite simulators that translate model-simulated cloud properties to synthetic observations as would be obtained by a range of satellite observing systems. This paper introduces COSP2, an evolution focusing on more explicit and consistent separation between host model, coupling infrastructure, and individual observing proxies. Revisions also enhance flexibility by allowing for model-specific representation of sub-grid-scale cloudiness, provide greater clarity by clearly separating tasks, support greater use of shared code and data including shared inputs across simulators, and follow more uniform software standards to simplify implementation across a wide range of platforms. The complete package including a testing suite is freely available.

Uranium adsorption on weathered schist - Intercomparison of modeling approaches

USGS Publications Warehouse

Payne, T.E.; Davis, J.A.; Ochs, M.; Olin, M.; Tweed, C.J.

2004-01-01

Experimental data for uranium adsorption on a complex weathered rock were simulated by twelve modelling teams from eight countries using surface complexation (SC) models. This intercomparison was part of an international project to evaluate the present capabilities and limitations of SC models in representing sorption by geologic materials. The models were assessed in terms of their predictive ability, data requirements, number of optimised parameters, ability to simulate diverse chemical conditions and transferability to other substrates. A particular aim was to compare the generalised composite (GC) and component additivity (CA) approaches for modelling sorption by complex substrates. Both types of SC models showed a promising capability to simulate sorption data obtained across a range of chemical conditions. However, the models incorporated a wide variety of assumptions, particularly in terms of input parameters such as site densities and surface site types. Furthermore, the methods used to extrapolate the model simulations to different weathered rock samples collected at the same field site tended to be unsatisfactory. The outcome of this modelling exercise provides an overview of the present status of adsorption modelling in the context of radionuclide migration as practised in a number of countries worldwide.

Low-cost solar array project: Four absolute cavity radiometer (pyrheliometer) intercomparisons at New River, Arizona: Radiometer standards

NASA Technical Reports Server (NTRS)

Estey, R. S.; Seaman, C. H.

1981-01-01

Four detailed intercomparisons were made for a number of models of cavity-type self-calibrating radiometers (pyrheliometers). Each intercomparison consisted of simultaneous readings of pyrheliometers at 30-second intervals in runs of 10 minutes, with at least 15 runs per intercomparison. Twenty-seven instruments were in at least one intercomparison, and five were in all four. Summarized results and all raw data are provided from the intercomparisons.

Constraints and potentials of future irrigation water availability on agricultural production under climate change

PubMed Central

Elliott, Joshua; Deryng, Delphine; Müller, Christoph; Frieler, Katja; Konzmann, Markus; Gerten, Dieter; Glotter, Michael; Flörke, Martina; Wada, Yoshihide; Best, Neil; Eisner, Stephanie; Fekete, Balázs M.; Folberth, Christian; Foster, Ian; Gosling, Simon N.; Haddeland, Ingjerd; Khabarov, Nikolay; Ludwig, Fulco; Masaki, Yoshimitsu; Olin, Stefan; Rosenzweig, Cynthia; Ruane, Alex C.; Satoh, Yusuke; Schmid, Erwin; Stacke, Tobias; Tang, Qiuhong; Wisser, Dominik

2014-01-01

We compare ensembles of water supply and demand projections from 10 global hydrological models and six global gridded crop models. These are produced as part of the Inter-Sectoral Impacts Model Intercomparison Project, with coordination from the Agricultural Model Intercomparison and Improvement Project, and driven by outputs of general circulation models run under representative concentration pathway 8.5 as part of the Fifth Coupled Model Intercomparison Project. Models project that direct climate impacts to maize, soybean, wheat, and rice involve losses of 400–1,400 Pcal (8–24% of present-day total) when CO2 fertilization effects are accounted for or 1,400–2,600 Pcal (24–43%) otherwise. Freshwater limitations in some irrigated regions (western United States; China; and West, South, and Central Asia) could necessitate the reversion of 20–60 Mha of cropland from irrigated to rainfed management by end-of-century, and a further loss of 600–2,900 Pcal of food production. In other regions (northern/eastern United States, parts of South America, much of Europe, and South East Asia) surplus water supply could in principle support a net increase in irrigation, although substantial investments in irrigation infrastructure would be required. PMID:24344283

Representative Agricultural Pathways and Climate Impact Assessment for Pacific Northwest Agricultural Systems

NASA Astrophysics Data System (ADS)

MU, J.; Antle, J. M.; Zhang, H.; Capalbo, S. M.; Eigenbrode, S.; Kruger, C.; Stockle, C.; Wolfhorst, J. D.

2013-12-01

Representative Agricultural Pathways (RAPs) are projections of plausible future biophysical and socio-economic conditions used to carry out climate impact assessments for agriculture. The development of RAPs iss motivated by the fact that the various global and regional models used for agricultural climate change impact assessment have been implemented with individualized scenarios using various data and model structures, often without transparent documentation or public availability. These practices have hampered attempts at model inter-comparison, improvement, and synthesis of model results across studies. This paper aims to (1) present RAPs developed for the principal wheat-producing region of the Pacific Northwest, and to (2) combine these RAPs with downscaled climate data, crop model simulations and economic model simulations to assess climate change impacts on winter wheat production and farm income. This research was carried out as part of a project funded by the USDA known as the Regional Approaches to Climate Change in the Pacific Northwest (REACCH). The REACCH study region encompasses the major winter wheat production area in Pacific Northwest and preliminary research shows that farmers producing winter wheat could benefit from future climate change. However, the future world is uncertain in many dimensions, including commodity and input prices, production technology, and policies, as well as increased probability of disturbances (pests and diseases) associated with a changing climate. Many of these factors cannot be modeled, so they are represented in the regional RAPS. The regional RAPS are linked to global agricultural and shared social-economic pathways, and used along with climate change projections to simulate future outcomes for the wheat-based farms in the REACCH region.

ARM/GCSS/SPARC TWP-ICE CRM Intercomparison Study

NASA Technical Reports Server (NTRS)

Fridlind, Ann; Ackerman, Andrew; Petch, Jon; Field, Paul; Hill, Adrian; McFarquhar, Greg; Xie, Shaocheng; Zhang, Minghua

2010-01-01

Specifications are provided for running a cloud-resolving model (CRM) and submitting results in a standardized format for inclusion in a n intercomparison study and archiving for public access. The simulated case study is based on measurements obtained during the 2006 Tropical Warm Pool - International Cloud Experiment (TWP-ICE) led by the U. S. department of Energy Atmospheric Radiation Measurement (ARM) program. The modeling intercomparison study is based on objectives developed in concert with the Stratospheric Processes And their Role in Climate (SPARC) program and the GEWEX cloud system study (GCSS) program. The Global Energy and Water Cycle Experiment (GEWEX) is a core project of the World Climate Research PRogramme (WCRP).

The Geoengineering Model Intercomparison Project Phase 6 (GeoMIP6): Simulation design and preliminary results

DOE PAGES

Kravitz, Benjamin S.; Robock, Alan; Tilmes, S.; ...

2015-10-27

We present a suite of new climate model experiment designs for the Geoengineering Model Intercomparison Project (GeoMIP). This set of experiments, named GeoMIP6 (to be consistent with the Coupled Model Intercomparison Project Phase 6), builds on the previous GeoMIP project simulations, and has been expanded to address several further important topics, including key uncertainties in extreme events, the use of geoengineering as part of a portfolio of responses to climate change, and the relatively new idea of cirrus cloud thinning to allow more long wave radiation to escape to space. We discuss experiment designs, as well as the rationale formore » those designs, showing preliminary results from individual models when available. We also introduce a new feature, called the GeoMIP Testbed, which provides a platform for simulations that will be performed with a few models and subsequently assessed to determine whether the proposed experiment designs will be adopted as core (Tier 1) GeoMIP experiments. In conclusion, this is meant to encourage various stakeholders to propose new targeted experiments that address their key open science questions, with the goal of making GeoMIP more relevant to a broader set of communities.« less

High Resolution Model Intercomparison Project (HighResMIP v1.0) for CMIP6

NASA Astrophysics Data System (ADS)

Haarsma, Reindert J.; Roberts, Malcolm J.; Vidale, Pier Luigi; Senior, Catherine A.; Bellucci, Alessio; Bao, Qing; Chang, Ping; Corti, Susanna; Fučkar, Neven S.; Guemas, Virginie; von Hardenberg, Jost; Hazeleger, Wilco; Kodama, Chihiro; Koenigk, Torben; Leung, L. Ruby; Lu, Jian; Luo, Jing-Jia; Mao, Jiafu; Mizielinski, Matthew S.; Mizuta, Ryo; Nobre, Paulo; Satoh, Masaki; Scoccimarro, Enrico; Semmler, Tido; Small, Justin; von Storch, Jin-Song

2016-11-01

Robust projections and predictions of climate variability and change, particularly at regional scales, rely on the driving processes being represented with fidelity in model simulations. The role of enhanced horizontal resolution in improved process representation in all components of the climate system is of growing interest, particularly as some recent simulations suggest both the possibility of significant changes in large-scale aspects of circulation as well as improvements in small-scale processes and extremes. However, such high-resolution global simulations at climate timescales, with resolutions of at least 50 km in the atmosphere and 0.25° in the ocean, have been performed at relatively few research centres and generally without overall coordination, primarily due to their computational cost. Assessing the robustness of the response of simulated climate to model resolution requires a large multi-model ensemble using a coordinated set of experiments. The Coupled Model Intercomparison Project 6 (CMIP6) is the ideal framework within which to conduct such a study, due to the strong link to models being developed for the CMIP DECK experiments and other model intercomparison projects (MIPs). Increases in high-performance computing (HPC) resources, as well as the revised experimental design for CMIP6, now enable a detailed investigation of the impact of increased resolution up to synoptic weather scales on the simulated mean climate and its variability. The High Resolution Model Intercomparison Project (HighResMIP) presented in this paper applies, for the first time, a multi-model approach to the systematic investigation of the impact of horizontal resolution. A coordinated set of experiments has been designed to assess both a standard and an enhanced horizontal-resolution simulation in the atmosphere and ocean. The set of HighResMIP experiments is divided into three tiers consisting of atmosphere-only and coupled runs and spanning the period 1950-2050, with the

High Resolution Model Intercomparison Project (HighResMIP v1.0) for CMIP6

DOE PAGES

Haarsma, Reindert J.; Roberts, Malcolm J.; Vidale, Pier Luigi; ...

2016-11-22

Robust projections and predictions of climate variability and change, particularly at regional scales, rely on the driving processes being represented with fidelity in model simulations. The role of enhanced horizontal resolution in improved process representation in all components of the climate system is of growing interest, particularly as some recent simulations suggest both the possibility of significant changes in large-scale aspects of circulation as well as improvements in small-scale processes and extremes. However, such high-resolution global simulations at climate timescales, with resolutions of at least 50 km in the atmosphere and 0.25° in the ocean, have been performed at relativelymore » few research centres and generally without overall coordination, primarily due to their computational cost. Assessing the robustness of the response of simulated climate to model resolution requires a large multi-model ensemble using a coordinated set of experiments. The Coupled Model Intercomparison Project 6 (CMIP6) is the ideal framework within which to conduct such a study, due to the strong link to models being developed for the CMIP DECK experiments and other model intercomparison projects (MIPs). Increases in high-performance computing (HPC) resources, as well as the revised experimental design for CMIP6, now enable a detailed investigation of the impact of increased resolution up to synoptic weather scales on the simulated mean climate and its variability. The High Resolution Model Intercomparison Project (HighResMIP) presented in this paper applies, for the first time, a multi-model approach to the systematic investigation of the impact of horizontal resolution. A coordinated set of experiments has been designed to assess both a standard and an enhanced horizontal-resolution simulation in the atmosphere and ocean. The set of HighResMIP experiments is divided into three tiers consisting of atmosphere-only and coupled runs and spanning the period 1950�

Multi-Model Combination techniques for Hydrological Forecasting: Application to Distributed Model Intercomparison Project Results

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ajami, N K; Duan, Q; Gao, X

2005-04-11

This paper examines several multi-model combination techniques: the Simple Multi-model Average (SMA), the Multi-Model Super Ensemble (MMSE), Modified Multi-Model Super Ensemble (M3SE) and the Weighted Average Method (WAM). These model combination techniques were evaluated using the results from the Distributed Model Intercomparison Project (DMIP), an international project sponsored by the National Weather Service (NWS) Office of Hydrologic Development (OHD). All of the multi-model combination results were obtained using uncalibrated DMIP model outputs and were compared against the best uncalibrated as well as the best calibrated individual model results. The purpose of this study is to understand how different combination techniquesmore » affect the skill levels of the multi-model predictions. This study revealed that the multi-model predictions obtained from uncalibrated single model predictions are generally better than any single member model predictions, even the best calibrated single model predictions. Furthermore, more sophisticated multi-model combination techniques that incorporated bias correction steps work better than simple multi-model average predictions or multi-model predictions without bias correction.« less

The AgMIP Coordinated Global and Regional Assessments (CGRA) of Climate Change Impacts on Agriculture and Food Security

NASA Technical Reports Server (NTRS)

Ruane, Alex; Rosenzweig, Cynthia; Elliott, Joshua; Antle, John

2015-01-01

The Agricultural Model Intercomparison and Improvement Project (AgMIP) has been working since 2010 to construct a protocol-based framework enabling regional assessments (led by regional experts and modelers) that can provide consistent inputs to global economic and integrated assessment models. These global models can then relay important global-level information that drive regional decision-making and outcomes throughout an interconnected agricultural system. AgMIPs community of nearly 800 climate, crop, livestock, economics, and IT experts has improved the state-of-the-art through model intercomparisons, validation exercises, regional integrated assessments, and the launch of AgMIP programs on all six arable continents. AgMIP is now launching Coordinated Global and Regional Assessments (CGRA) of climate change impacts on agriculture and food security to link global and regional crop and economic models using a protocol-based framework. The CGRA protocols are being developed to utilize historical observations, climate projections, and RCPsSSPs from CMIP5 (and potentially CMIP6), and will examine stakeholder-driven agricultural development and adaptation scenarios to provide cutting-edge assessments of climate changes impact on agriculture and food security. These protocols will build on the foundation of established protocols from AgMIPs 30+ activities, and will emphasize the use of multiple models, scenarios, and scales to enable an accurate assessment of related uncertainties. The CGRA is also designed to provide the outputs necessary to feed into integrated assessment models (IAMs), nutrition and food security assessments, nitrogen and carbon cycle models, and additional impact-sector assessments (e.g., water resources, land-use, biomes, urban areas). This presentation will describe the current status of CGRA planning and initial prototype experiments to demonstrate key aspects of the protocols before wider implementation ahead of the IPCC Sixth Assessment

The AgMIP Coordinated Global and Regional Assessments (CGRA) of Climate Change Impacts on Agriculture and Food Security

NASA Astrophysics Data System (ADS)

Ruane, A. C.; Rosenzweig, C.; Antle, J. M.; Elliott, J. W.

2015-12-01

The Agricultural Model Intercomparison and Improvement Project (AgMIP) has been working since 2010 to construct a protocol-based framework enabling regional assessments (led by regional experts and modelers) that can provide consistent inputs to global economic and integrated assessment models. These global models can then relay important global-level information that drive regional decision-making and outcomes throughout an interconnected agricultural system. AgMIP's community of nearly 800 climate, crop, livestock, economics, and IT experts has improved the state-of-the-art through model intercomparisons, validation exercises, regional integrated assessments, and the launch of AgMIP programs on all six arable continents. AgMIP is now launching Coordinated Global and Regional Assessments (CGRA) of climate change impacts on agriculture and food security to link global and regional crop and economic models using a protocol-based framework. The CGRA protocols are being developed to utilize historical observations, climate projections, and RCPs/SSPs from CMIP5 (and potentially CMIP6), and will examine stakeholder-driven agricultural development and adaptation scenarios to provide cutting-edge assessments of climate change's impact on agriculture and food security. These protocols will build on the foundation of established protocols from AgMIP's 30+ activities, and will emphasize the use of multiple models, scenarios, and scales to enable an accurate assessment of related uncertainties. The CGRA is also designed to provide the outputs necessary to feed into integrated assessment models (IAMs), nutrition and food security assessments, nitrogen and carbon cycle models, and additional impact-sector assessments (e.g., water resources, land-use, biomes, urban areas). This presentation will describe the current status of CGRA planning and initial prototype experiments to demonstrate key aspects of the protocols before wider implementation ahead of the IPCC Sixth Assessment

The 1996 North American Interagency Intercomparison of Ultraviolet Monitoring Spectroradiometers

PubMed Central

Early, Edward; Thompson, Ambler; Johnson, Carol; DeLuisi, John; Disterhoft, Patrick; Wardle, David; Wu, Edmund; Mou, Wanfeng; Ehramjian, James; Tusson, John; Mestechkina, Tanya; Beaubian, Mark; Gibson, James; Hayes, Douglass

1998-01-01

Concern over stratospheric ozone depletion has prompted several government agencies in North America to establish networks of spectroradiometers for monitoring solar ultraviolet irradiance at the surface of the Earth. To assess the ability of spectroradiometers to accurately measure solar ultraviolet irradiance, and to compare the results between instruments of different monitoring networks, the third North American Interagency Intercomparison of Ultraviolet Monitoring Spectroradiometers was held June 17–25, 1996 at Table Mountain outside Boulder, Colorado, USA. This Intercomparison was coordinated by the National Institute of Standards and Technology (NIST) and the National Oceanic and Atmospheric Administration (NOAA). Participating agencies were the Environmental Protection Agency; the National Science Foundation; the Smithsonian Environmental Research Center; the Department of Agriculture; and the Atmospheric Environment Service, Canada. The spectral irradiances of participants’ calibrated standard lamps were measured at NIST prior to the Intercomparison. The spectral irradiance scales used by the participants agreed with the NIST scale within the combined uncertainties, and for all lamps the spectral irradiance in the horizontal position was lower than that in the vertical position. Instruments were characterized for wavelength uncertainty, bandwidth, stray-light rejection, and spectral irradiance responsivity, the latter with NIST standard lamps operating in specially designed field calibration units. The spectral irradiance responsivity demonstrated instabilities for some instruments. Synchronized spectral scans of the solar irradiance were performed over several days. Using the spectral irradiance responsivities determined with the NIST standard lamps, the measured solar irradiances had some unexplained systematic differences between instruments. PMID:28009358

Three models intercomparison for Quantitative Precipitation Forecast over Calabria

NASA Astrophysics Data System (ADS)

Federico, S.; Avolio, E.; Bellecci, C.; Colacino, M.; Lavagnini, A.; Accadia, C.; Mariani, S.; Casaioli, M.

2004-11-01

In the framework of the National Project “Sviluppo di distretti industriali per le Osservazioni della Terra” (Development of Industrial Districts for Earth Observations) funded by MIUR (Ministero dell'Università e della Ricerca Scientifica --Italian Ministry of the University and Scientific Research) two operational mesoscale models were set-up for Calabria, the southernmost tip of the Italian peninsula. Models are RAMS (Regional Atmospheric Modeling System) and MM5 (Mesoscale Modeling 5) that are run every day at Crati scrl to produce weather forecast over Calabria (http://www.crati.it). This paper reports model intercomparison for Quantitative Precipitation Forecast evaluated for a 20 month period from 1th October 2000 to 31th May 2002. In addition to RAMS and MM5 outputs, QBOLAM rainfall fields are available for the period selected and included in the comparison. This model runs operationally at “Agenzia per la Protezione dell'Ambiente e per i Servizi Tecnici”. Forecasts are verified comparing models outputs with raingauge data recorded by the regional meteorological network, which has 75 raingauges. Large-scale forcing is the same for all models considered and differences are due to physical/numerical parameterizations and horizontal resolutions. QPFs show differences between models. Largest differences are for BIA compared to the other considered scores. Performances decrease with increasing forecast time for RAMS and MM5, whilst QBOLAM scores better for second day forecast.

Towards an integrated economic assessment of climate change impacts on agriculture

NASA Astrophysics Data System (ADS)

Lotze-Campen, H.; Piontek, F.; Stevanovic, M.; Popp, A.; Bauer, N.; Dietrich, J.; Mueller, C.; Schmitz, C.

2012-12-01

For a detailed understanding of the effects of climate change on global agricultural production systems, it is essential to consider the variability of climate change patterns as projected by General Circulation Models (GCMs), their bio-physical impact on crops and the response in land-use patterns and markets. So far, approaches that account for the interaction of bio-physical and economic impacts are largely lacking. We present an integrative analysis by using a soft-coupled system of a biophysical impact model (LPJmL, Bondeau et al. 2007), an economically driven land use model (MAgPIE, Lotze-Campen et al. 2008) and an integrated assessment model (ReMIND-R, Leimbach et al. 2010) to study climate change impacts and economic damages in the agricultural sector. First, the dynamic global vegetation and hydrology model LPJmL is used to derive climate change impacts on crop yields for wheat, maize, soy, rice and other major crops. A range of different climate projections is used, taken from the dataset provided by the Intersectoral Impact Model Intercomparison Project (ISI-MIP, www.isi-mip.org), which bias-corrected the latest CMIP5 climate data (Taylor et al. 2011). Crop yield impacts cover scenarios with and without CO2 fertilization as well as different Representative Concentration Pathways (RCPs) and different GCMs. With increasing temperature towards the end of the century yields generally decrease in tropical and subtropical regions, while they tend to benefit in higher latitudes. LPJmL results have been compared to other global crop models in the Agricultural Model Intercomparison and Improvement Project (AgMIP, www.agmip.org). Second, changes in crop yields are analysed with the spatially explicit agro-economic model MAgPIE, which covers their interaction with economic development and changes in food demand. Changes in prices as well as welfare changes of producer and consumer surplus are taken as economic indicators. Due to climate-change related reductions in

The North American Carbon Program Multi-scale Synthesis and Terrestrial Model Intercomparison Project – Part 2: Environmental driver data

DOE PAGES

Wei, Yaxing; Liu, Shishi; Huntzinger, Deborah N.; ...

2014-12-05

Ecosystems are important and dynamic components of the global carbon cycle, and terrestrial biospheric models (TBMs) are crucial tools in further understanding of how terrestrial carbon is stored and exchanged with the atmosphere across a variety of spatial and temporal scales. Improving TBM skills, and quantifying and reducing their estimation uncertainties, pose significant challenges. The Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP) is a formal multi-scale and multi-model intercomparison effort set up to tackle these challenges. The MsTMIP protocol prescribes standardized environmental driver data that are shared among model teams to facilitate model model and model observation comparisons. Inmore » this article, we describe the global and North American environmental driver data sets prepared for the MsTMIP activity to both support their use in MsTMIP and make these data, along with the processes used in selecting/processing these data, accessible to a broader audience. Based on project needs and lessons learned from past model intercomparison activities, we compiled climate, atmospheric CO 2 concentrations, nitrogen deposition, land use and land cover change (LULCC), C3 / C4 grasses fractions, major crops, phenology and soil data into a standard format for global (0.5⁰ x 0.5⁰ resolution) and regional (North American: 0.25⁰ x 0.25⁰ resolution) simulations. In order to meet the needs of MsTMIP, improvements were made to several of the original environmental data sets, by improving the quality, and/or changing their spatial and temporal coverage, and resolution. The resulting standardized model driver data sets are being used by over 20 different models participating in MsTMIP. Lastly, the data are archived at the Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC, http://daac.ornl.gov) to provide long-term data management and distribution.« less

A River Model Intercomparison Project in Preparation for SWOT

NASA Astrophysics Data System (ADS)

David, C. H.; Andreadis, K.; Famiglietti, J. S.; Beighley, E.; Boone, A. A.; Yamazaki, D.; Paiva, R. C. D.; Fleischmann, A. S.; Collischonn, W.; Fisher, C. K.; Kim, H.; Biancamaria, S.

2017-12-01

The Surface Water and Ocean Topography (SWOT) mission is currently scheduled to launch at the beginning of next decade. SWOT is expected to retrieve unprecedented measurements of water extent, elevation, and slope in the largest terrestrial water bodies. Such potential transformative information motivates the investigation of our ability to ingest the associated data into continental-scale models of terrestrial hydrology. In preparation for the expected SWOT observations, an inter-comparison of continental-scale river models is being performed. This comparison experiment focuses on four of the world's largest river basins: the Amazon, the Mississippi, the Niger, and the Saint-Lawrence. This ongoing project focuses on two main research questions: 1) How can we best prepare for the expected SWOT continental to global measurements before SWOT even flies?, and 2) What is the added value of including SWOT terrestrial measurements into global hydro models for enhancing our understanding of the terrestrial water cycle and the climate system? We present here the results of the second year of this project which now includes simulations from six numerical models of rivers over the Mississippi and sheds light on the implications of various modeling choices on simulation quality as well as on the potential impact of SWOT observations.

C4MIP - The Coupled Climate-Carbon Cycle Model Intercomparison Project: experimental protocol for CMIP6

NASA Astrophysics Data System (ADS)

Jones, Chris D.; Arora, Vivek; Friedlingstein, Pierre; Bopp, Laurent; Brovkin, Victor; Dunne, John; Graven, Heather; Hoffman, Forrest; Ilyina, Tatiana; John, Jasmin G.; Jung, Martin; Kawamiya, Michio; Koven, Charlie; Pongratz, Julia; Raddatz, Thomas; Randerson, James T.; Zaehle, Sönke

2016-08-01

Coordinated experimental design and implementation has become a cornerstone of global climate modelling. Model Intercomparison Projects (MIPs) enable systematic and robust analysis of results across many models, by reducing the influence of ad hoc differences in model set-up or experimental boundary conditions. As it enters its 6th phase, the Coupled Model Intercomparison Project (CMIP6) has grown significantly in scope with the design and documentation of individual simulations delegated to individual climate science communities. The Coupled Climate-Carbon Cycle Model Intercomparison Project (C4MIP) takes responsibility for design, documentation, and analysis of carbon cycle feedbacks and interactions in climate simulations. These feedbacks are potentially large and play a leading-order contribution in determining the atmospheric composition in response to human emissions of CO2 and in the setting of emissions targets to stabilize climate or avoid dangerous climate change. For over a decade, C4MIP has coordinated coupled climate-carbon cycle simulations, and in this paper we describe the C4MIP simulations that will be formally part of CMIP6. While the climate-carbon cycle community has created this experimental design, the simulations also fit within the wider CMIP activity, conform to some common standards including documentation and diagnostic requests, and are designed to complement the CMIP core experiments known as the Diagnostic, Evaluation and Characterization of Klima (DECK). C4MIP has three key strands of scientific motivation and the requested simulations are designed to satisfy their needs: (1) pre-industrial and historical simulations (formally part of the common set of CMIP6 experiments) to enable model evaluation, (2) idealized coupled and partially coupled simulations with 1 % per year increases in CO2 to enable diagnosis of feedback strength and its components, (3) future scenario simulations to project how the Earth system will respond to

Solid precipitation measurement intercomparison in Bismarck, North Dakota, from 1988 through 1997

USGS Publications Warehouse

Ryberg, Karen R.; Emerson, Douglas G.; Macek-Rowland, Kathleen M.

2009-01-01

A solid precipitation measurement intercomparison was recommended by the World Meteorological Organization (WMO) and was initiated after approval by the ninth session of the Commission for Instruments and Methods of Observation. The goal of the intercomparison was to assess national methods of measuring solid precipitation against methods whose accuracy and reliability were known. A field study was started in Bismarck, N. Dak., during the 1988-89 winter as part of the intercomparison. The last official field season of the WMO intercomparison was 1992-93; however, the Bismarck site continued to operate through the winter of 1996-97. Precipitation events at Bismarck were categorized as snow, mixed, or rain on the basis of descriptive notes recorded as part of the solid precipitation intercomparison. The rain events were not further analyzed in this study. Catch ratios (CRs) - the ratio of the precipitation catch at each gage to the true precipitation measurement (the corrected double fence intercomparison reference) - were calculated. Then, regression analysis was used to develop equations that model the snow and mixed precipitation CRs at each gage as functions of wind speed and temperature. Wind speed at the gages, functions of temperature, and upper air conditions (wind speed and air temperature at 700 millibars pressure) were used as possible explanatory variables in the multiple regression analysis done for this study. The CRs were modeled by using multiple regression analysis for the Tretyakov gage, national shielded gage, national unshielded gage, AeroChem gage, national gage with double fence, and national gage with Wyoming windshield. As in earlier studies by the WMO, wind speed and air temperature were found to influence the CR of the Tretyakov gage. However, in this study, the temperature variable represented the average upper air temperature over the duration of the event. The WMO did not use upper air conditions in its analysis. The national shielded and

Risk Modelling of Agricultural Products

NASA Astrophysics Data System (ADS)

Nugrahani, E. H.

2017-03-01

In the real world market, agricultural commodity are imposed with fluctuating prices. This means that the price of agricultural products are relatively volatile, which means that agricultural business is a quite risky business for farmers. This paper presents some mathematical models to model such risks in the form of its volatility, based on certain assumptions. The proposed models are time varying volatility model, as well as time varying volatility with mean reversion and with seasonal mean equation models. Implementation on empirical data show that agricultural products are indeed risky.

The Pliocene Model Intercomparison Project (PlioMIP) Phase 2: scientific objectives and experimental design

NASA Astrophysics Data System (ADS)

Haywood, Alan M.; Dowsett, Harry J.; Dolan, Aisling M.; Rowley, David; Abe-Ouchi, Ayako; Otto-Bliesner, Bette; Chandler, Mark A.; Hunter, Stephen J.; Lunt, Daniel J.; Pound, Matthew; Salzmann, Ulrich

2016-03-01

The Pliocene Model Intercomparison Project (PlioMIP) is a co-ordinated international climate modelling initiative to study and understand climate and environments of the Late Pliocene, as well as their potential relevance in the context of future climate change. PlioMIP examines the consistency of model predictions in simulating Pliocene climate and their ability to reproduce climate signals preserved by geological climate archives. Here we provide a description of the aim and objectives of the next phase of the model intercomparison project (PlioMIP Phase 2), and we present the experimental design and boundary conditions that will be utilized for climate model experiments in Phase 2. Following on from PlioMIP Phase 1, Phase 2 will continue to be a mechanism for sampling structural uncertainty within climate models. However, Phase 1 demonstrated the requirement to better understand boundary condition uncertainties as well as uncertainty in the methodologies used for data-model comparison. Therefore, our strategy for Phase 2 is to utilize state-of-the-art boundary conditions that have emerged over the last 5 years. These include a new palaeogeographic reconstruction, detailing ocean bathymetry and land-ice surface topography. The ice surface topography is built upon the lessons learned from offline ice sheet modelling studies. Land surface cover has been enhanced by recent additions of Pliocene soils and lakes. Atmospheric reconstructions of palaeo-CO2 are emerging on orbital timescales, and these are also incorporated into PlioMIP Phase 2. New records of surface and sea surface temperature change are being produced that will be more temporally consistent with the boundary conditions and forcings used within models. Finally we have designed a suite of prioritized experiments that tackle issues surrounding the basic understanding of the Pliocene and its relevance in the context of future climate change in a discrete way.

The Pliocene Model Intercomparison Project (PlioMIP) Phase 2: Scientific Objectives and Experimental Design

NASA Technical Reports Server (NTRS)

Haywood, Alan M.; Dowsett, Harry J.; Dolan, Aisling M.; Rowley, David; Abe-Ouchi, Ayako; Otto-Bliesner, Bette; Chandler, Mark A.; Hunter, Stephen J.; Lunt, Daniel J.; Pound, Matthew;

Indoor and Outdoor Spectroradiometer Intercomparison for Spectral Irradiance Measurement

DOE Office of Scientific and Technical Information (OSTI.GOV)

Habte, A.; Andreas, A.; Ottoson, L.

2014-05-01

This report details the global spectral irradiance intercomparison using spectroradiometers that was organized by the National Renewable Energy Laboratory's Solar Radiation Research Laboratory. The intercomparison was performed both indoors and outdoors on September 17, 2013. Five laboratories participated in the intercomparison using 10 spectroradiometers, and a coordinated measurement setup and a common platform were employed to compare spectral irradiances under both indoor and outdoor conditions. The intercomparison aimed to understand the performance of the different spectroradiometers and to share knowledge in making spectral irradiance measurements. This intercomparison was the first of its kind in the United States.

C4MIP – The Coupled Climate–Carbon Cycle Model Intercomparison Project: Experimental protocol for CMIP6

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jones, Chris D.; Arora, Vivek; Friedlingstein, Pierre

Coordinated experimental design and implementation has become a cornerstone of global climate modelling. Model Intercomparison Projects (MIPs) enable systematic and robust analysis of results across many models, by reducing the influence of ad hoc differences in model set-up or experimental boundary conditions. As it enters its 6th phase, the Coupled Model Intercomparison Project (CMIP6) has grown significantly in scope with the design and documentation of individual simulations delegated to individual climate science communities. The Coupled Climate–Carbon Cycle Model Intercomparison Project (C4MIP) takes responsibility for design, documentation, and analysis of carbon cycle feedbacks and interactions in climate simulations. These feedbacks aremore » potentially large and play a leading-order contribution in determining the atmospheric composition in response to human emissions of CO 2 and in the setting of emissions targets to stabilize climate or avoid dangerous climate change. For over a decade, C4MIP has coordinated coupled climate–carbon cycle simulations, and in this paper we describe the C4MIP simulations that will be formally part of CMIP6. While the climate–carbon cycle community has created this experimental design, the simulations also fit within the wider CMIP activity, conform to some common standards including documentation and diagnostic requests, and are designed to complement the CMIP core experiments known as the Diagnostic, Evaluation and Characterization of Klima (DECK). C4MIP has three key strands of scientific motivation and the requested simulations are designed to satisfy their needs: (1) pre-industrial and historical simulations (formally part of the common set of CMIP6 experiments) to enable model evaluation, (2) idealized coupled and partially coupled simulations with 1 % per year increases in CO 2 to enable diagnosis of feedback strength and its components, (3) future scenario simulations to project how the Earth system will

C4MIP – The Coupled Climate–Carbon Cycle Model Intercomparison Project: Experimental protocol for CMIP6

DOE PAGES

Jones, Chris D.; Arora, Vivek; Friedlingstein, Pierre; ...

2016-08-25

Coordinated experimental design and implementation has become a cornerstone of global climate modelling. Model Intercomparison Projects (MIPs) enable systematic and robust analysis of results across many models, by reducing the influence of ad hoc differences in model set-up or experimental boundary conditions. As it enters its 6th phase, the Coupled Model Intercomparison Project (CMIP6) has grown significantly in scope with the design and documentation of individual simulations delegated to individual climate science communities. The Coupled Climate–Carbon Cycle Model Intercomparison Project (C4MIP) takes responsibility for design, documentation, and analysis of carbon cycle feedbacks and interactions in climate simulations. These feedbacks aremore » potentially large and play a leading-order contribution in determining the atmospheric composition in response to human emissions of CO 2 and in the setting of emissions targets to stabilize climate or avoid dangerous climate change. For over a decade, C4MIP has coordinated coupled climate–carbon cycle simulations, and in this paper we describe the C4MIP simulations that will be formally part of CMIP6. While the climate–carbon cycle community has created this experimental design, the simulations also fit within the wider CMIP activity, conform to some common standards including documentation and diagnostic requests, and are designed to complement the CMIP core experiments known as the Diagnostic, Evaluation and Characterization of Klima (DECK). C4MIP has three key strands of scientific motivation and the requested simulations are designed to satisfy their needs: (1) pre-industrial and historical simulations (formally part of the common set of CMIP6 experiments) to enable model evaluation, (2) idealized coupled and partially coupled simulations with 1 % per year increases in CO 2 to enable diagnosis of feedback strength and its components, (3) future scenario simulations to project how the Earth system will

Stability of the Atlantic meridional overturning circulation: A model intercomparison

NASA Astrophysics Data System (ADS)

Weaver, Andrew J.; Sedláček, Jan; Eby, Michael; Alexander, Kaitlin; Crespin, Elisabeth; Fichefet, Thierry; Philippon-Berthier, Gwenaëlle; Joos, Fortunat; Kawamiya, Michio; Matsumoto, Katsumi; Steinacher, Marco; Tachiiri, Kaoru; Tokos, Kathy; Yoshimori, Masakazu; Zickfeld, Kirsten

2012-10-01

The evolution of the Atlantic Meridional Overturning Circulation (MOC) in 30 models of varying complexity is examined under four distinct Representative Concentration Pathways. The models include 25 Atmosphere-Ocean General Circulation Models (AOGCMs) or Earth System Models (ESMs) that submitted simulations in support of the 5th phase of the Coupled Model Intercomparison Project (CMIP5) and 5 Earth System Models of Intermediate Complexity (EMICs). While none of the models incorporated the additional effects of ice sheet melting, they all projected very similar behaviour during the 21st century. Over this period the strength of MOC reduced by a best estimate of 22% (18%-25% 5%-95% confidence limits) for RCP2.6, 26% (23%-30%) for RCP4.5, 29% (23%-35%) for RCP6.0 and 40% (36%-44%) for RCP8.5. Two of the models eventually realized a slow shutdown of the MOC under RCP8.5, although no model exhibited an abrupt change of the MOC. Through analysis of the freshwater flux across 30°-32°S into the Atlantic, it was found that 40% of the CMIP5 models were in a bistable regime of the MOC for the duration of their RCP integrations. The results support previous assessments that it is very unlikely that the MOC will undergo an abrupt change to an off state as a consequence of global warming.

Climate Model Response from the Geoengineering Model Intercomparison Project (GeoMIP)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kravitz, Benjamin S.; Caldeira, Ken; Boucher, Olivier

2013-08-09

Solar geoengineering—deliberate reduction in the amount of solar radiation retained by the Earth—has been proposed as a means of counteracting some of the climatic effects of anthropogenic greenhouse gas emissions. We present results from Experiment G1 of the Geoengineering Model Intercomparison Project, in which 12 climate models have simulated the climate response to an abrupt quadrupling of CO2 from preindustrial concentrations brought into radiative balance via a globally uniform reduction in insolation. Models show this reduction largely offsets global mean surface temperature increases due to quadrupled CO2 concentrations and prevents 97% of the Arctic sea ice loss that would otherwisemore » occur under high CO2 levels but, compared to the preindustrial climate, leaves the tropics cooler (-0.3 K) and the poles warmer (+0.8 K). Annual mean precipitation minus evaporation anomalies for G1 are less than 0.2mmday-1 in magnitude over 92% of the globe, but some tropical regions receive less precipitation, in part due to increased moist static stability and suppression of convection. Global average net primary productivity increases by 120% in G1 over simulated preindustrial levels, primarily from CO2 fertilization, but also in part due to reduced plant heat stress compared to a high CO2 world with no geoengineering. All models show that uniform solar geoengineering in G1 cannot simultaneously return regional and global temperature and hydrologic cycle intensity to preindustrial levels.« less

Climate model response from the Geoengineering Model Intercomparison Project (GeoMIP)

NASA Astrophysics Data System (ADS)

Kravitz, Ben; Caldeira, Ken; Boucher, Olivier; Robock, Alan; Rasch, Philip J.; Alterskjær, Kari; Karam, Diana Bou; Cole, Jason N. S.; Curry, Charles L.; Haywood, James M.; Irvine, Peter J.; Ji, Duoying; Jones, Andy; Kristjánsson, Jón Egill; Lunt, Daniel J.; Moore, John C.; Niemeier, Ulrike; Schmidt, Hauke; Schulz, Michael; Singh, Balwinder; Tilmes, Simone; Watanabe, Shingo; Yang, Shuting; Yoon, Jin-Ho

2013-08-01

geoengineering—deliberate reduction in the amount of solar radiation retained by the Earth—has been proposed as a means of counteracting some of the climatic effects of anthropogenic greenhouse gas emissions. We present results from Experiment G1 of the Geoengineering Model Intercomparison Project, in which 12 climate models have simulated the climate response to an abrupt quadrupling of CO2 from preindustrial concentrations brought into radiative balance via a globally uniform reduction in insolation. Models show this reduction largely offsets global mean surface temperature increases due to quadrupled CO2 concentrations and prevents 97% of the Arctic sea ice loss that would otherwise occur under high CO2 levels but, compared to the preindustrial climate, leaves the tropics cooler (-0.3 K) and the poles warmer (+0.8 K). Annual mean precipitation minus evaporation anomalies for G1 are less than 0.2 mm day-1 in magnitude over 92% of the globe, but some tropical regions receive less precipitation, in part due to increased moist static stability and suppression of convection. Global average net primary productivity increases by 120% in G1 over simulated preindustrial levels, primarily from CO2 fertilization, but also in part due to reduced plant heat stress compared to a high CO2 world with no geoengineering. All models show that uniform solar geoengineering in G1 cannot simultaneously return regional and global temperature and hydrologic cycle intensity to preindustrial levels.

An Intercomparison of 2-D Models Within a Common Framework

NASA Technical Reports Server (NTRS)

Weisenstein, Debra K.; Ko, Malcolm K. W.; Scott, Courtney J.; Jackman, Charles H.; Fleming, Eric L.; Considine, David B.; Kinnison, Douglas E.; Connell, Peter S.; Rotman, Douglas A.; Bhartia, P. K. (Technical Monitor)

2002-01-01

A model intercomparison among the Atmospheric and Environmental Research (AER) 2-D model, the Goddard Space Flight Center (GSFC) 2-D model, and the Lawrence Livermore National Laboratory 2-D model allows us to separate differences due to model transport from those due to the model's chemical formulation. This is accomplished by constructing two hybrid models incorporating the transport parameters of the GSFC and LLNL models within the AER model framework. By comparing the results from the native models (AER and e.g. GSFC) with those from the hybrid model (e.g. AER chemistry with GSFC transport), differences due to chemistry and transport can be identified. For the analysis, we examined an inert tracer whose emission pattern is based on emission from a High Speed Civil Transport (HSCT) fleet; distributions of trace species in the 2015 atmosphere; and the response of stratospheric ozone to an HSCT fleet. Differences in NO(y) in the upper stratosphere are found between models with identical transport, implying different model representations of atmospheric chemical processes. The response of O3 concentration to HSCT aircraft emissions differs in the models from both transport-dominated differences in the HSCT-induced perturbations of H2O and NO(y) as well as from differences in the model represent at ions of O3 chemical processes. The model formulations of cold polar processes are found to be the most significant factor in creating large differences in the calculated ozone perturbations

The Radiative Forcing Model Intercomparison Project (RFMIP): Assessment and characterization of forcing to enable feedback studies

NASA Astrophysics Data System (ADS)

Pincus, R.; Stevens, B. B.; Forster, P.; Collins, W.; Ramaswamy, V.

2014-12-01

The Radiative Forcing Model Intercomparison Project (RFMIP): Assessment and characterization of forcing to enable feedback studies An enormous amount of attention has been paid to the diversity of responses in the CMIP and other multi-model ensembles. This diversity is normally interpreted as a distribution in climate sensitivity driven by some distribution of feedback mechanisms. Identification of these feedbacks relies on precise identification of the forcing to which each model is subject, including distinguishing true error from model diversity. The Radiative Forcing Model Intercomparison Project (RFMIP) aims to disentangle the role of forcing from model sensitivity as determinants of varying climate model response by carefully characterizing the radiative forcing to which such models are subject and by coordinating experiments in which it is specified. RFMIP consists of four activities: 1) An assessment of accuracy in flux and forcing calculations for greenhouse gases under past, present, and future climates, using off-line radiative transfer calculations in specified atmospheres with climate model parameterizations and reference models 2) Characterization and assessment of model-specific historical forcing by anthropogenic aerosols, based on coordinated diagnostic output from climate models and off-line radiative transfer calculations with reference models 3) Characterization of model-specific effective radiative forcing, including contributions of model climatology and rapid adjustments, using coordinated climate model integrations and off-line radiative transfer calculations with a single fast model 4) Assessment of climate model response to precisely-characterized radiative forcing over the historical record, including efforts to infer true historical forcing from patterns of response, by direct specification of non-greenhouse-gas forcing in a series of coordinated climate model integrations This talk discusses the rationale for RFMIP, provides an overview

Intercomparison of general circulation models for hot extrasolar planets

NASA Astrophysics Data System (ADS)

Polichtchouk, I.; Cho, J. Y.-K.; Watkins, C.; Thrastarson, H. Th.; Umurhan, O. M.; de la Torre Juárez, M.

2014-02-01

We compare five general circulation models (GCMs) which have been recently used to study hot extrasolar planet atmospheres (BOB, CAM, IGCM, MITgcm, and PEQMOD), under three test cases useful for assessing model convergence and accuracy. Such a broad, detailed intercomparison has not been performed thus far for extrasolar planets study. The models considered all solve the traditional primitive equations, but employ different numerical algorithms or grids (e.g., pseudospectral and finite volume, with the latter separately in longitude-latitude and ‘cubed-sphere’ grids). The test cases are chosen to cleanly address specific aspects of the behaviors typically reported in hot extrasolar planet simulations: (1) steady-state, (2) nonlinearly evolving baroclinic wave, and (3) response to fast timescale thermal relaxation. When initialized with a steady jet, all models maintain the steadiness, as they should-except MITgcm in cubed-sphere grid. A very good agreement is obtained for a baroclinic wave evolving from an initial instability in pseudospectral models (only). However, exact numerical convergence is still not achieved across the pseudospectral models: amplitudes and phases are observably different. When subject to a typical ‘hot-Jupiter’-like forcing, all five models show quantitatively different behavior-although qualitatively similar, time-variable, quadrupole-dominated flows are produced. Hence, as have been advocated in several past studies, specific quantitative predictions (such as the location of large vortices and hot regions) by GCMs should be viewed with caution. Overall, in the tests considered here, pseudospectral models in pressure coordinate (PEBOB and PEQMOD) perform the best and MITgcm in cubed-sphere grid performs the worst.

SECOND LATIN AMERICAN INTERCOMPARISON ON INTERNAL DOSE ASSESSMENT.

PubMed

Rojo, A; Puerta, N; Gossio, S; Gómez Parada, I; Cruz Suarez, R; López, E; Medina, C; Lastra Boylan, J; Pinheiro Ramos, M; Mora Ramírez, E; Alves Dos Reis, A; Yánez, H; Rubio, J; Vironneau Janicek, L; Somarriba Vanegas, F; Puerta Ortiz, J; Salas Ramírez, M; López Bejerano, G; da Silva, T; Miri Oliveira, C; Terán, M; Alfaro, M; García, T; Angeles, A; Duré Romero, E; Farias de Lima, F

2016-09-01

Internal dosimetry intercomparisons are essential for the verification of applied models and the consistency of results'. To that aim, the First Regional Intercomparison was organised in 2005, and that results led to the Second Regional Intercomparison Exercise in 2013, which was organised in the frame of the RLA 9/066 and coordinated by Autoridad Regulatoria Nuclear of Argentina. Four simulated cases covering intakes of (131)I, (137)Cs and Tritium were proposed. Ninteen centres from thirteen different countries participated in this exercise. This paper analyses the participants' results in this second exercise in order to test their skills and acquired knowledge, particularly in the application of the IDEAS Guidelines. It is important to highlight the increased number of countries that participated in this exercise compared with the first one and, furthermore, the improvement in the overall performance. The impact of the International Atomic Energy Agency (IAEA) Projects since 2003 has led to a significant enhancement of internal dosimetry capabilities that strengthen the radiation protection of workers. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Brief History of Agricultural Systems Modeling

NASA Technical Reports Server (NTRS)

Jones, James W.; Antle, John M.; Basso, Bruno O.; Boote, Kenneth J.; Conant, Richard T.; Foster, Ian; Godfray, H. Charles J.; Herrrero, Mario; Howitt, Richard E.; Janssen, Sandor;

Brief history of agricultural systems modeling.

PubMed

Jones, James W; Antle, John M; Basso, Bruno; Boote, Kenneth J; Conant, Richard T; Foster, Ian; Godfray, H Charles J; Herrero, Mario; Howitt, Richard E; Janssen, Sander; Keating, Brian A; Munoz-Carpena, Rafael; Porter, Cheryl H; Rosenzweig, Cynthia; Wheeler, Tim R

2017-07-01

Agricultural systems science generates knowledge that allows researchers to consider complex problems or take informed agricultural decisions. The rich history of this science exemplifies the diversity of systems and scales over which they operate and have been studied. Modeling, an essential tool in agricultural systems science, has been accomplished by scientists from a wide range of disciplines, who have contributed concepts and tools over more than six decades. As agricultural scientists now consider the "next generation" models, data, and knowledge products needed to meet the increasingly complex systems problems faced by society, it is important to take stock of this history and its lessons to ensure that we avoid re-invention and strive to consider all dimensions of associated challenges. To this end, we summarize here the history of agricultural systems modeling and identify lessons learned that can help guide the design and development of next generation of agricultural system tools and methods. A number of past events combined with overall technological progress in other fields have strongly contributed to the evolution of agricultural system modeling, including development of process-based bio-physical models of crops and livestock, statistical models based on historical observations, and economic optimization and simulation models at household and regional to global scales. Characteristics of agricultural systems models have varied widely depending on the systems involved, their scales, and the wide range of purposes that motivated their development and use by researchers in different disciplines. Recent trends in broader collaboration across institutions, across disciplines, and between the public and private sectors suggest that the stage is set for the major advances in agricultural systems science that are needed for the next generation of models, databases, knowledge products and decision support systems. The lessons from history should be

A Methodological Inter-Comparison of Gridded Meteorological Products

NASA Astrophysics Data System (ADS)

Newman, A. J.; Clark, M. P.; Longman, R. J.; Giambelluca, T. W.; Arnold, J.

2017-12-01

Here we present a gridded meteorology inter-comparison using the state of Hawaíi as a testbed. This inter-comparison is motivated by two general goals: 1) the broad user community of gridded observation based meteorological fields should be aware of inter-product differences and the reasons they exist, which allows users to make informed choices on product selection to best meet their specific application(s); 2) we want to demonstrate the utility of inter-comparisons to meet the first goal, yet highlight that they are limited to mostly generic statements regarding attribution of differences that limits our understanding of these complex algorithms and obscures future research directions. Hawaíi is a useful testbed because it is a meteorologically complex region with well-known spatial features that are tied to specific physical processes (e.g. the trade wind inversion). From a practical standpoint, there are now several monthly climatological and daily precipitation and temperature datasets available that are being used for impact modeling. General conclusions that have emerged are: 1) differences in input station data significantly influence product differences; 2) prediction of precipitation occurrence is crucial across multiple metrics; 3) derived temperature statistics (e.g. diurnal temperature range) may have large spatial differences across products; and 4) attribution of differences to methodological choices is difficult and may limit the outcomes of these inter-comparisons, particularly from a development viewpoint. Thus, we want to continue to move the community towards frameworks that allow for multiple options throughout the product generation chain and allow for more systematic testing.

Assessing the impact of land use change on hydrology by ensemble modeling (LUCHEM). I: Model intercomparison with current land use

USGS Publications Warehouse

Breuer, L.; Huisman, J.A.; Willems, P.; Bormann, H.; Bronstert, A.; Croke, B.F.W.; Frede, H.-G.; Graff, T.; Hubrechts, L.; Jakeman, A.J.; Kite, G.; Lanini, J.; Leavesley, G.; Lettenmaier, D.P.; Lindstrom, G.; Seibert, J.; Sivapalan, M.; Viney, N.R.

2009-01-01

This paper introduces the project on 'Assessing the impact of land use change on hydrology by ensemble modeling (LUCHEM)' that aims at investigating the envelope of predictions on changes in hydrological fluxes due to land use change. As part of a series of four papers, this paper outlines the motivation and setup of LUCHEM, and presents a model intercomparison for the present-day simulation results. Such an intercomparison provides a valuable basis to investigate the effects of different model structures on model predictions and paves the ground for the analysis of the performance of multi-model ensembles and the reliability of the scenario predictions in companion papers. In this study, we applied a set of 10 lumped, semi-lumped and fully distributed hydrological models that have been previously used in land use change studies to the low mountainous Dill catchment, Germany. Substantial differences in model performance were observed with Nash-Sutcliffe efficiencies ranging from 0.53 to 0.92. Differences in model performance were attributed to (1) model input data, (2) model calibration and (3) the physical basis of the models. The models were applied with two sets of input data: an original and a homogenized data set. This homogenization of precipitation, temperature and leaf area index was performed to reduce the variation between the models. Homogenization improved the comparability of model simulations and resulted in a reduced average bias, although some variation in model data input remained. The effect of the physical differences between models on the long-term water balance was mainly attributed to differences in how models represent evapotranspiration. Semi-lumped and lumped conceptual models slightly outperformed the fully distributed and physically based models. This was attributed to the automatic model calibration typically used for this type of models. Overall, however, we conclude that there was no superior model if several measures of model

SimilarityExplorer: A visual inter-comparison tool for multifaceted climate data

Treesearch

J. Poco; A. Dasgupta; Y. Wei; W. Hargrove; C. Schwalm; R. Cook; E. Bertini; C. Silva

2014-01-01

Inter-comparison and similarity analysis to gauge consensus among multiple simulation models is a critical visualization problem for understanding climate change patterns. Climate models, specifically, Terrestrial Biosphere Models (TBM) represent time and space variable ecosystem processes, for example, simulations of photosynthesis and respiration, using algorithms...

Brief history of agricultural systems modeling

DOE PAGES

Jones, James W.; Antle, John M.; Basso, Bruno; ...

2017-06-21

Agricultural systems science generates knowledge that allows researchers to consider complex problems or take informed agricultural decisions. The rich history of this science exemplifies the diversity of systems and scales over which they operate and have been studied. Modeling, an essential tool in agricultural systems science, has been accomplished by scientists from a wide range of disciplines, who have contributed concepts and tools over more than six decades. As agricultural scientists now consider the "next generation" models, data, and knowledge products needed to meet the increasingly complex systems problems faced by society, it is important to take stock of thismore » history and its lessons to ensure that we avoid re-invention and strive to consider all dimensions of associated challenges. To this end, we summarize here the history of agricultural systems modeling and identify lessons learned that can help guide the design and development of next generation of agricultural system tools and methods. A number of past events combined with overall technological progress in other fields have strongly contributed to the evolution of agricultural system modeling, including development of process-based bio-physical models of crops and livestock, statistical models based on historical observations, and economic optimization and simulation models at household and regional to global scales. Characteristics of agricultural systems models have varied widely depending on the systems involved, their scales, and the wide range of purposes that motivated their development and use by researchers in different disciplines. Recent trends in broader collaboration across institutions, across disciplines, and between the public and private sectors suggest that the stage is set for the major advances in agricultural systems science that are needed for the next generation of models, databases, knowledge products and decision support systems. Furthermore, the lessons from

Brief history of agricultural systems modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jones, James W.; Antle, John M.; Basso, Bruno

Agricultural systems science generates knowledge that allows researchers to consider complex problems or take informed agricultural decisions. The rich history of this science exemplifies the diversity of systems and scales over which they operate and have been studied. Modeling, an essential tool in agricultural systems science, has been accomplished by scientists from a wide range of disciplines, who have contributed concepts and tools over more than six decades. As agricultural scientists now consider the "next generation" models, data, and knowledge products needed to meet the increasingly complex systems problems faced by society, it is important to take stock of thismore » history and its lessons to ensure that we avoid re-invention and strive to consider all dimensions of associated challenges. To this end, we summarize here the history of agricultural systems modeling and identify lessons learned that can help guide the design and development of next generation of agricultural system tools and methods. A number of past events combined with overall technological progress in other fields have strongly contributed to the evolution of agricultural system modeling, including development of process-based bio-physical models of crops and livestock, statistical models based on historical observations, and economic optimization and simulation models at household and regional to global scales. Characteristics of agricultural systems models have varied widely depending on the systems involved, their scales, and the wide range of purposes that motivated their development and use by researchers in different disciplines. Recent trends in broader collaboration across institutions, across disciplines, and between the public and private sectors suggest that the stage is set for the major advances in agricultural systems science that are needed for the next generation of models, databases, knowledge products and decision support systems. Furthermore, the lessons from

Intercomparison of middle-atmospheric wind in observations and models

NASA Astrophysics Data System (ADS)

Rüfenacht, Rolf; Baumgarten, Gerd; Hildebrand, Jens; Schranz, Franziska; Matthias, Vivien; Stober, Gunter; Lübken, Franz-Josef; Kämpfer, Niklaus

2018-04-01

Wind profile information throughout the entire upper stratosphere and lower mesosphere (USLM) is important for the understanding of atmospheric dynamics but became available only recently, thanks to developments in remote sensing techniques and modelling approaches. However, as wind measurements from these altitudes are rare, such products have generally not yet been validated with (other) observations. This paper presents the first long-term intercomparison of wind observations in the USLM by co-located microwave radiometer and lidar instruments at Andenes, Norway (69.3° N, 16.0° E). Good correspondence has been found at all altitudes for both horizontal wind components for nighttime as well as daylight conditions. Biases are mostly within the random errors and do not exceed 5-10 m s-1, which is less than 10 % of the typically encountered wind speeds. Moreover, comparisons of the observations with the major reanalyses and models covering this altitude range are shown, in particular with the recently released ERA5, ECMWF's first reanalysis to cover the whole USLM region. The agreement between models and observations is very good in general, but temporally limited occurrences of pronounced discrepancies (up to 40 m s-1) exist. In the article's Appendix the possibility of obtaining nighttime wind information about the mesopause region by means of microwave radiometry is investigated.

A Spatial Data Model Desing For The Management Of Agricultural Data (Farmer, Agricultural Land And Agricultural Production)

NASA Astrophysics Data System (ADS)

Taşkanat, Talha; İbrahim İnan, Halil

2016-04-01

Since the beginning of the 2000s, it has been conducted many projects such as Agricultural Sector Integrated Management Information System, Agriculture Information System, Agricultural Production Registry System and Farmer Registry System by the Turkish Ministry of Food, Agriculture and Livestock and the Turkish Statistical Institute in order to establish and manage better agricultural policy and produce better agricultural statistics in Turkey. Yet, it has not been carried out any study for the structuring of a system which can meet the requirements of different institutions and organizations that need similar agricultural data. It has been tried to meet required data only within the frame of the legal regulations from present systems. Whereas the developments in GIS (Geographical Information Systems) and standardization, and Turkey National GIS enterprise in this context necessitate to meet the demands of organizations that use the similar data commonly and to act in terms of a data model logic. In this study, 38 institutions or organization which produce and use agricultural data were detected, that and thanks to survey and interviews undertaken, their needs were tried to be determined. In this study which is financially supported by TUBITAK, it was worked out relationship between farmer, agricultural land and agricultural production data and all of the institutions and organizations in Turkey and in this context, it was worked upon the best detailed and effective possible data model. In the model design, UML which provides object-oriented design was used. In the data model, for the management of spatial data, sub-parcel data model was used. Thanks to this data model, declared and undeclared areas can be detected spatially, and thus declarations can be associated to sub-parcels. Within this framework, it will be able to developed agricultural policies as a result of acquiring more extensive, accurate, spatially manageable and easily updatable farmer and

A New Trans-Disciplinary Approach to Regional Integrated Assessment of Climate Impact and Adaptation in Agricultural Systems (Invited)

NASA Astrophysics Data System (ADS)

Antle, J. M.; Valdivia, R. O.; Jones, J.; Rosenzweig, C.; Ruane, A. C.

2013-12-01

This presentation provides an overview of the new methods developed by researchers in the Agricultural Model Inter-comparison and Improvement Project (AgMIP) for regional climate impact assessment and analysis of adaptation in agricultural systems. This approach represents a departure from approaches in the literature in several dimensions. First, the approach is based on the analysis of agricultural systems (not individual crops) and is inherently trans-disciplinary: it is based on a deep collaboration among a team of climate scientists, agricultural scientists and economists to design and implement regional integrated assessments of agricultural systems. Second, in contrast to previous approaches that have imposed future climate on models based on current socio-economic conditions, this approach combines bio-physical and economic models with a new type of pathway analysis (Representative Agricultural Pathways) to parameterize models consistent with a plausible future world in which climate change would be occurring. Third, adaptation packages for the agricultural systems in a region are designed by the research team with a level of detail that is useful to decision makers, such as research administrators and donors, who are making agricultural R&D investment decisions. The approach is illustrated with examples from AgMIP's projects currently being carried out in Africa and South Asia.

Climate change impacts on tree ranges: model intercomparison facilitates understanding and quantification of uncertainty.

PubMed

Cheaib, Alissar; Badeau, Vincent; Boe, Julien; Chuine, Isabelle; Delire, Christine; Dufrêne, Eric; François, Christophe; Gritti, Emmanuel S; Legay, Myriam; Pagé, Christian; Thuiller, Wilfried; Viovy, Nicolas; Leadley, Paul

2012-06-01

Model-based projections of shifts in tree species range due to climate change are becoming an important decision support tool for forest management. However, poorly evaluated sources of uncertainty require more scrutiny before relying heavily on models for decision-making. We evaluated uncertainty arising from differences in model formulations of tree response to climate change based on a rigorous intercomparison of projections of tree distributions in France. We compared eight models ranging from niche-based to process-based models. On average, models project large range contractions of temperate tree species in lowlands due to climate change. There was substantial disagreement between models for temperate broadleaf deciduous tree species, but differences in the capacity of models to account for rising CO(2) impacts explained much of the disagreement. There was good quantitative agreement among models concerning the range contractions for Scots pine. For the dominant Mediterranean tree species, Holm oak, all models foresee substantial range expansion. © 2012 Blackwell Publishing Ltd/CNRS.

The T-REX valley wind intercomparison project

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schmidli, J; Billings, B J; Burton, R

2008-08-07

An accurate simulation of the evolution of the atmospheric boundary layer is very important, as the evolution of the boundary layer sets the stage for many weather phenomena, such as deep convection. Over mountain areas the evolution of the boundary layer is particularly complex, due to the nonlinear interaction between boundary layer turbulence and thermally-induced mesoscale wind systems, such as the slope and valley winds. As the horizontal resolution of operational forecasts progresses to finer and finer resolution, more and more of the thermally-induced mesoscale wind systems can be explicitly resolved, and it is very timely to document the currentmore » state-of-the-art of mesoscale models at simulating the coupled evolution of the mountain boundary layer and the valley wind system. In this paper we present an intercomparison of valley wind simulations for an idealized valley-plain configuration using eight state-of-the-art mesoscale models with a grid spacing of 1 km. Different sets of three-dimensional simulations are used to explore the effects of varying model dynamical cores and physical parameterizations. This intercomparison project was conducted as part of the Terrain-induced Rotor Experiment (T-REX; Grubisic et al., 2008).« less

Community Intercomparison Suite (CIS) v1.4.0: a tool for intercomparing models and observations

NASA Astrophysics Data System (ADS)

Watson-Parris, Duncan; Schutgens, Nick; Cook, Nicholas; Kipling, Zak; Kershaw, Philip; Gryspeerdt, Edward; Lawrence, Bryan; Stier, Philip

2016-09-01

The Community Intercomparison Suite (CIS) is an easy-to-use command-line tool which has been developed to allow the straightforward intercomparison of remote sensing, in situ and model data. While there are a number of tools available for working with climate model data, the large diversity of sources (and formats) of remote sensing and in situ measurements necessitated a novel software solution. Developed by a professional software company, CIS supports a large number of gridded and ungridded data sources "out-of-the-box", including climate model output in NetCDF or the UK Met Office pp file format, CloudSat, CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization), MODIS (MODerate resolution Imaging Spectroradiometer), Cloud and Aerosol CCI (Climate Change Initiative) level 2 satellite data and a number of in situ aircraft and ground station data sets. The open-source architecture also supports user-defined plugins to allow many other sources to be easily added. Many of the key operations required when comparing heterogenous data sets are provided by CIS, including subsetting, aggregating, collocating and plotting the data. Output data are written to CF-compliant NetCDF files to ensure interoperability with other tools and systems. The latest documentation, including a user manual and installation instructions, can be found on our website (http://cistools.net). Here, we describe the need which this tool fulfils, followed by descriptions of its main functionality (as at version 1.4.0) and plugin architecture which make it unique in the field.

The Carbon Dioxide Removal Model Intercomparison Project (CDRMIP): rationale and experimental protocol for CMIP6

NASA Astrophysics Data System (ADS)

Keller, David P.; Lenton, Andrew; Scott, Vivian; Vaughan, Naomi E.; Bauer, Nico; Ji, Duoying; Jones, Chris D.; Kravitz, Ben; Muri, Helene; Zickfeld, Kirsten

2018-03-01

The recent IPCC reports state that continued anthropogenic greenhouse gas emissions are changing the climate, threatening severe, pervasive and irreversible impacts. Slow progress in emissions reduction to mitigate climate change is resulting in increased attention to what is called geoengineering, climate engineering, or climate intervention - deliberate interventions to counter climate change that seek to either modify the Earth's radiation budget or remove greenhouse gases such as CO2 from the atmosphere. When focused on CO2, the latter of these categories is called carbon dioxide removal (CDR). Future emission scenarios that stay well below 2 °C, and all emission scenarios that do not exceed 1.5 °C warming by the year 2100, require some form of CDR. At present, there is little consensus on the climate impacts and atmospheric CO2 reduction efficacy of the different types of proposed CDR. To address this need, the Carbon Dioxide Removal Model Intercomparison Project (or CDRMIP) was initiated. This project brings together models of the Earth system in a common framework to explore the potential, impacts, and challenges of CDR. Here, we describe the first set of CDRMIP experiments, which are formally part of the 6th Coupled Model Intercomparison Project (CMIP6). These experiments are designed to address questions concerning CDR-induced climate reversibility, the response of the Earth system to direct atmospheric CO2 removal (direct air capture and storage), and the CDR potential and impacts of afforestation and reforestation, as well as ocean alkalinization.>

The Carbon Dioxide Removal Model Intercomparison Project (CDRMIP): rationale and experimental protocol for CMIP6

DOE Office of Scientific and Technical Information (OSTI.GOV)

Keller, David P.; Lenton, Andrew; Scott, Vivian

The recent IPCC reports state that continued anthropogenic greenhouse gas emissions are changing the climate, threatening severe, pervasive and irreversible impacts. Slow progress in emissions reduction to mitigate climate change is resulting in increased attention to what is called geoengineering, climate engineering, or climate intervention – deliberate interventions to counter climate change that seek to either modify the Earth's radiation budget or remove greenhouse gases such as CO 2 from the atmosphere. When focused on CO 2, the latter of these categories is called carbon dioxide removal (CDR). Future emission scenarios that stay well below 2 °C, and all emissionmore » scenarios that do not exceed 1.5 °C warming by the year 2100, require some form of CDR. At present, there is little consensus on the climate impacts and atmospheric CO 2 reduction efficacy of the different types of proposed CDR. To address this need, the Carbon Dioxide Removal Model Intercomparison Project (or CDRMIP) was initiated. This project brings together models of the Earth system in a common framework to explore the potential, impacts, and challenges of CDR. Here, we describe the first set of CDRMIP experiments, which are formally part of the 6th Coupled Model Intercomparison Project (CMIP6). These experiments are designed to address questions concerning CDR-induced climate reversibility, the response of the Earth system to direct atmospheric CO 2 removal (direct air capture and storage), and the CDR potential and impacts of afforestation and reforestation, as well as ocean alkalinization.>« less

Worldwide multi-model intercomparison of clear-sky solar irradiance predictions

NASA Astrophysics Data System (ADS)

Ruiz-Arias, Jose A.; Gueymard, Christian A.; Cebecauer, Tomas

2017-06-01

Accurate modeling of solar radiation in the absence of clouds is highly important because solar power production peaks during cloud-free situations. The conventional validation approach of clear-sky solar radiation models relies on the comparison between model predictions and ground observations. Therefore, this approach is limited to locations with availability of high-quality ground observations, which are scarce worldwide. As a consequence, many areas of in-terest for, e.g., solar energy development, still remain sub-validated. Here, a worldwide inter-comparison of the global horizontal irradiance (GHI) and direct normal irradiance (DNI) calculated by a number of appropriate clear-sky solar ra-diation models is proposed, without direct intervention of any weather or solar radiation ground-based observations. The model inputs are all gathered from atmospheric reanalyses covering the globe. The model predictions are compared to each other and only their relative disagreements are quantified. The largest differences between model predictions are found over central and northern Africa, the Middle East, and all over Asia. This coincides with areas of high aerosol optical depth and highly varying aerosol distribution size. Overall, the differences in modeled DNI are found about twice larger than for GHI. It is argued that the prevailing weather regimes (most importantly, aerosol conditions) over regions exhibiting substantial divergences are not adequately parameterized by all models. Further validation and scrutiny using conventional methods based on ground observations should be pursued in priority over those specific regions to correctly evaluate the performance of clear-sky models, and select those that can be recommended for solar concentrating applications in particular.

Intercomparison of Global Precipitation Products: The Third Precipitation Intercomparison Project (PIP-3)

NASA Technical Reports Server (NTRS)

Adler, Robert F.; Kidd, Christopher; Petty, Grant; Morrissey, Mark; Goodman, H. Michael; Einaudi, Franco (Technical Monitor)

2000-01-01

A set of global, monthly rainfall products has been intercompared to understand the quality and utility of the estimates. The products include 25 observational (satellite-based), four model and two climatological products. The results of the intercomparison indicate a very large range (factor of two or three) of values when all products are considered. The range of values is reduced considerably when the set of observational products is limited to those considered quasi-standard. The model products do significantly poorer in the tropics, but are competitive with satellite-based fields in mid-latitudes over land. Over ocean, products are compared to frequency of precipitation from ship observations. The evaluation of the observational products point to merged data products (including rain gauge information) as providing the overall best results.

Accuracy of tretyakov precipitation gauge: Result of wmo intercomparison

USGS Publications Warehouse

Yang, Daqing; Goodison, Barry E.; Metcalfe, John R.; Golubev, Valentin S.; Elomaa, Esko; Gunther, Thilo; Bates, Roy; Pangburn, Timothy; Hanson, Clayton L.; Emerson, Douglas G.; Copaciu, Voilete; Milkovic, Janja

1995-01-01

The Tretyakov non-recording precipitation gauge has been used historically as the official precipitation measurement instrument in the Russian (formerly the USSR) climatic and hydrological station network and in a number of other European countries. From 1986 to 1993, the accuracy and performance of this gauge were evaluated during the WMO Solid Precipitation Measurement Intercomparison at 11 stations in Canada, the USA, Russia, Germany, Finland, Romania and Croatia. The double fence intercomparison reference (DFIR) was the reference standard used at all the Intercomparison stations in the Intercomparison. The Intercomparison data collected at the different sites are compatible with respect to the catch ratio (measured/DFIR) for the same gauge, when compared using mean wind speed at the height of the gauge orifice during the observation period.The Intercomparison data for the Tretyakov gauge were compiled from measurements made at these WMO intercomparison sites. These data represent a variety of climates, terrains and exposures. The effects of environmental factors, such as wind speed, wind direction, type of precipitation and temperature, on gauge catch ratios were investigated. Wind speed was found to be the most important factor determining the gauge catch and air temperature had a secondary effect when precipitation was classified into snow, mixed and rain. The results of the analysis of gauge catch ratio versus wind speed and temperature on a daily time step are presented for various types of precipitation. Independent checks of the correction equations against the DFIR have been conducted at those Intercomparison stations and a good agreement (difference less than 10%) has been obtained. The use of such adjustment procedures should significantly improve the accuracy and homogeneity of gauge-measured precipitation data over large regions of the former USSR and central Europe.

Results of the eruptive column model inter-comparison study

USGS Publications Warehouse

Costa, Antonio; Suzuki, Yujiro; Cerminara, M.; Devenish, Ben J.; Esposti Ongaro, T.; Herzog, Michael; Van Eaton, Alexa; Denby, L.C.; Bursik, Marcus; de' Michieli Vitturi, Mattia; Engwell, S.; Neri, Augusto; Barsotti, Sara; Folch, Arnau; Macedonio, Giovanni; Girault, F.; Carazzo, G.; Tait, S.; Kaminski, E.; Mastin, Larry G.; Woodhouse, Mark J.; Phillips, Jeremy C.; Hogg, Andrew J.; Degruyter, Wim; Bonadonna, Costanza

2016-01-01

This study compares and evaluates one-dimensional (1D) and three-dimensional (3D) numerical models of volcanic eruption columns in a set of different inter-comparison exercises. The exercises were designed as a blind test in which a set of common input parameters was given for two reference eruptions, representing a strong and a weak eruption column under different meteorological conditions. Comparing the results of the different models allows us to evaluate their capabilities and target areas for future improvement. Despite their different formulations, the 1D and 3D models provide reasonably consistent predictions of some of the key global descriptors of the volcanic plumes. Variability in plume height, estimated from the standard deviation of model predictions, is within ~ 20% for the weak plume and ~ 10% for the strong plume. Predictions of neutral buoyancy level are also in reasonably good agreement among the different models, with a standard deviation ranging from 9 to 19% (the latter for the weak plume in a windy atmosphere). Overall, these discrepancies are in the range of observational uncertainty of column height. However, there are important differences amongst models in terms of local properties along the plume axis, particularly for the strong plume. Our analysis suggests that the simplified treatment of entrainment in 1D models is adequate to resolve the general behaviour of the weak plume. However, it is inadequate to capture complex features of the strong plume, such as large vortices, partial column collapse, or gravitational fountaining that strongly enhance entrainment in the lower atmosphere. We conclude that there is a need to more accurately quantify entrainment rates, improve the representation of plume radius, and incorporate the effects of column instability in future versions of 1D volcanic plume models.

Intercomparison of retrospective radon detectors.

PubMed Central

Field, R W; Steck, D J; Parkhurst, M A; Mahaffey, J A; Alavanja, M C

1999-01-01

We performed both a laboratory and a field intercomparison of two novel glass-based retrospective radon detectors previously used in major radon case-control studies performed in Missouri and Iowa. The new detectors estimate retrospective residential radon exposure from the accumulation of a long-lived radon decay product, (210)Pb, in glass. The detectors use track registration material in direct contact with glass surfaces to measure the alpha-emission of a (210)Pb-decay product, (210)Po. The detector's track density generation rate (tracks per square centimeter per hour) is proportional to the surface alpha-activity. In the absence of other strong sources of alpha-emission in the glass, the implanted surface alpha-activity should be proportional to the accumulated (210)Po, and hence to the cumulative radon gas exposure. The goals of the intercomparison were to a) perform collocated measurements using two different glass-based retrospective radon detectors in a controlled laboratory environment to compare their relative response to implanted polonium in the absence of environmental variation, b) perform collocated measurements using two different retrospective radon progeny detectors in a variety of residential settings to compare their detection of glass-implanted polonium activities, and c) examine the correlation between track density rates and contemporary radon gas concentrations. The laboratory results suggested that the materials and methods used by the studies produced similar track densities in detectors exposed to the same implanted (210)Po activity. The field phase of the intercomparison found excellent agreement between the track density rates for the two types of retrospective detectors. The correlation between the track density rates and direct contemporary radon concentration measurements was relatively high, considering that no adjustments were performed to account for either the residential depositional environment or glass surface type

Intercomparison of retrospective radon detectors.

PubMed

Field, R W; Steck, D J; Parkhurst, M A; Mahaffey, J A; Alavanja, M C

1999-11-01

We performed both a laboratory and a field intercomparison of two novel glass-based retrospective radon detectors previously used in major radon case-control studies performed in Missouri and Iowa. The new detectors estimate retrospective residential radon exposure from the accumulation of a long-lived radon decay product, (210)Pb, in glass. The detectors use track registration material in direct contact with glass surfaces to measure the alpha-emission of a (210)Pb-decay product, (210)Po. The detector's track density generation rate (tracks per square centimeter per hour) is proportional to the surface alpha-activity. In the absence of other strong sources of alpha-emission in the glass, the implanted surface alpha-activity should be proportional to the accumulated (210)Po, and hence to the cumulative radon gas exposure. The goals of the intercomparison were to a) perform collocated measurements using two different glass-based retrospective radon detectors in a controlled laboratory environment to compare their relative response to implanted polonium in the absence of environmental variation, b) perform collocated measurements using two different retrospective radon progeny detectors in a variety of residential settings to compare their detection of glass-implanted polonium activities, and c) examine the correlation between track density rates and contemporary radon gas concentrations. The laboratory results suggested that the materials and methods used by the studies produced similar track densities in detectors exposed to the same implanted (210)Po activity. The field phase of the intercomparison found excellent agreement between the track density rates for the two types of retrospective detectors. The correlation between the track density rates and direct contemporary radon concentration measurements was relatively high, considering that no adjustments were performed to account for either the residential depositional environment or glass surface type

Evaluation of Arctic Sea Ice Thickness Simulated by Arctic Ocean Model Intercomparison Project Models

NASA Technical Reports Server (NTRS)

Johnson, Mark; Proshuntinsky, Andrew; Aksenov, Yevgeny; Nguyen, An T.; Lindsay, Ron; Haas, Christian; Zhang, Jinlun; Diansky, Nikolay; Kwok, Ron; Maslowski, Wieslaw;

Intercomparison of TCCON and MUSICA Water Vapour Products

NASA Astrophysics Data System (ADS)

Weaver, D.; Strong, K.; Deutscher, N. M.; Schneider, M.; Blumenstock, T.; Robinson, J.; Notholt, J.; Sherlock, V.; Griffith, D. W. T.; Barthlott, S.; García, O. E.; Smale, D.; Palm, M.; Jones, N. B.; Hase, F.; Kivi, R.; Ramos, Y. G.; Yoshimura, K.; Sepúlveda, E.; Gómez-Peláez, Á. J.; Gisi, M.; Kohlhepp, R.; Warneke, T.; Dohe, S.; Wiegele, A.; Christner, E.; Lejeune, B.; Demoulin, P.

2014-12-01

We present an intercomparison between the water vapour products from the Total Carbon Column Observing Network (TCCON) and the MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water (MUSICA), two datasets from ground-based Fourier Transform InfraRed (FTIR) spectrometers with good global representation. Where possible, comparisons to radiosondes are also included. The near-infrared TCCON measurements are optimized to provide precise monitoring of greenhouse gases for carbon cycle studies; however, TCCON's retrievals also produce water vapour products. The mid-infrared MUSICA products result from retrievals optimized to give precise and accurate information about H2O, HDO, and δD. The MUSICA water vapour products have been validated by extensive intercomparisons with H2O and δD in-situ measurements made from ground, radiosonde, and aircraft (Schneider et al. 2012, 2014), as well as by intercomparisons with satellite-based H2O and δD remote sensing measurements (Wiegele et al., 2014). This dataset provides a valuable reference point for other measurements of water vapour. This study is motivated by the limited intercomparisons performed for TCCON water vapour products and limited characterisation of their uncertainties. We compare MUSICA and TCCON products to assess the potential for TCCON measurements to contribute to studies of the water cycle, water vapour's role in climate and use as a tracer for atmospheric dynamics, and to evaluate the performance of climate models. The TCCON and MUSICA products result from measurements taken using the same FTIR instruments, enabling a comparison with constant instrumentation. The retrieval techniques differ, however, in their method and a priori information. We assess the impact of these differences and characterize the comparability of the TCCON and MUSICA datasets.

Overview of Dust Model Inter-comparison (DMIP) in East Asia

NASA Astrophysics Data System (ADS)

Uno, I.

2004-12-01

Dust transport modeling plays an important role in understanding the recent increase of Asian Dust episodes and its impact to the regional climate system. Several dust models have been developed in several research institutes and government agencies independently since 1990s. Their numerical results either look very similar or different. Those disagreements are caused by difference in dust modules (concepts and basic mechanisms) and atmospheric models (meteorological and transport models). Therefore common understanding of performance and uncertainty of dust erosion and transport models in the Asian region becomes very important. To have a better understanding of dust model application, we proposed the dust model intercomparison under the international cooperation networks as a part of activity of ADEC (Aeolian Dust Experiment on Climate Impact) project research. Current participants are Kyusyu Univ. (Japan), Meteorological Research Institute (Japan), Hong-Kong City Univ. (China), Korean Meteorological Agency METRI (Korea), US Naval Research Laboratory (USA), Chinese Meteorological Agency (China), Institute of Atmospheric Physics (China), Insular Coastal Dynamics (Malta) and Meteorological Service of Canada (Canada). As a case study episode, we set two huge dust storms occurred in March and April 2002. Results from the dust transport model from all the participants are compiled on the same methods and examined the model characteristics against the ground and airborne measurement data. We will also examine the dust model results from the horizontal distribution at specified levels, vertical profiles, concentration at special check point and emission flux at source region, and show the important parameters for dust modeling. In this paper, we will introduce the general overview of this DMIP activity and several important conclusions from this activity.

Comprehensive Australasian multicentre dosimetric intercomparison: issues, logistics and recommendations.

PubMed

Ebert, M A; Harrison, K M; Cornes, D; Howlett, S J; Joseph, D J; Kron, T; Hamilton, C S; Denham, J W

2009-02-01

The present paper describes the logistics of the 2004-2008 Australasian Level III Dosimetry Intercomparison. Dosimetric intercomparisons (or 'audits') can be used in radiotherapy to evaluate the accuracy and quality of radiation delivery. An intercomparison was undertaken in New Zealand and Australia to evaluate the feasibility and logistics of ongoing dosimetric intercomparisons that evaluate all steps in the radiotherapy treatment process, known as a 'Level III' intercomparison. The study commenced in 2002 with the establishment of a study team, definition of the study protocol, acquisition of appropriate equipment and recruitment of participating radiotherapy centres. Measurements were undertaken between October 2004 and March 2008, and included collation of data on time, costs and logistics of the study. Forty independent Australian and New Zealand radiotherapy centres agreed to participate. Measurement visits were made to 37 of these centres. Data is presented on the costs of the study and the level of support required. The study involved the participation of 16 staff at the study centre who invested over 4000 hours in the study, and of over 200 professionals at participating centres. Recommendations are provided for future phantom-based intercomparisons. It is hoped that the present paper will be of benefit to any centres or groups contemplating similar activities by identifying the processes involved in establishing the study, the potential hazards and pitfalls, and expected resource requirements.

The 1995 North American Interagency Intercomparison of Ultraviolet Monitoring Spectroradiometers

PubMed Central

Early, Edward; Thompson, Ambler; Johnson, Carol; DeLuisi, John; Disterhoft, Patrick; Wardle, David; Wu, Edmund; Mou, Wanfeng; Sun, Yongchen; Lucas, Timothy; Mestechkina, Tanya; Harrison, Lee; Berndt, Jerry; Hayes, Douglas S.

1998-01-01

Concern over stratospheric ozone depletion has prompted several government agencies in North America to establish networks of spectroradiometers for monitoring solar ultraviolet irradiance at the surface of the Earth. To assess the ability of spectroradiometers to accurately measure solar ultraviolet irradiance, and to compare the results between instruments of different monitoring networks, the second North American Intercomparison of Ultraviolet Monitoring Spectroradiometers was held June 12 to 23, 1995 at Table Mountain outside Boulder, Colorado, USA. This Intercomparison was coordinated by the National Institute of Standards and Technology (NIST) and the National Oceanic and Atmospheric Administration (NOAA). Participating agencies were the Environmental Protection Agency; the National Science Foundation; the Smithsonian Environmental Research Center; the Department of Agriculture; and the Atmospheric Environment Service, Canada. Instruments were characterized for wavelength uncertainty, bandwidth, stray-light rejection, and spectral irradiance responsivity, the latter with a NIST standard lamp operating in a specially designed field calibration unit. The spectral irradiance responsivity, determined once indoors and twice outdoors, demonstrated that while the responsivities changed upon moving the instruments, they were relatively stable when the instruments remained outdoors. Synchronized spectral scans of the solar irradiance were performed over several days. Using the spectral irradiance responsivities determined with the NIST standard lamp and three different convolution functions to account for the different bandwidths of the instruments, the measured solar irradiances generally agreed to within 3 %. PMID:28009371

Inter-comparison of Computer Codes for TRISO-based Fuel Micro-Modeling and Performance Assessment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brian Boer; Chang Keun Jo; Wen Wu

2010-10-01

The Next Generation Nuclear Plant (NGNP), the Deep Burn Pebble Bed Reactor (DB-PBR) and the Deep Burn Prismatic Block Reactor (DB-PMR) are all based on fuels that use TRISO particles as their fundamental constituent. The TRISO particle properties include very high durability in radiation environments, hence the designs reliance on the TRISO to form the principal barrier to radioactive materials release. This durability forms the basis for the selection of this fuel type for applications such as Deep Bun (DB), which require exposures up to four times those expected for light water reactors. It follows that the study and predictionmore » of the durability of TRISO particles must be carried as part of the safety and overall performance characterization of all the designs mentioned above. Such evaluations have been carried out independently by the performers of the DB project using independently developed codes. These codes, PASTA, PISA and COPA, incorporate models for stress analysis on the various layers of the TRISO particle (and of the intervening matrix material for some of them), model for fission products release and migration then accumulation within the SiC layer of the TRISO particle, just next to the layer, models for free oxygen and CO formation and migration to the same location, models for temperature field modeling within the various layers of the TRISO particle and models for the prediction of failure rates. All these models may be either internal to the code or external. This large number of models and the possibility of different constitutive data and model formulations and the possibility of a variety of solution techniques makes it highly unlikely that the model would give identical results in the modeling of identical situations. The purpose of this paper is to present the results of an inter-comparison between the codes and to identify areas of agreement and areas that need reconciliation. The inter-comparison has been carried out by the

AgMIP's Transdisciplinary Agricultural Systems Approach to Regional Integrated Assessment of Climate Impacts, Vulnerability, and Adaptation

NASA Technical Reports Server (NTRS)

Antle, John M.; Valdivia, Roberto O.; Boote, Kenneth J.; Janssen, Sander; Jones, James W.; Porter, Cheryl H.; Rosenzweig, Cynthia; Ruane, Alexander C.; Thorburn, Peter J.

2015-01-01

This chapter describes methods developed by the Agricultural Model Intercomparison and Improvement Project (AgMIP) to implement a transdisciplinary, systems-based approach for regional-scale (local to national) integrated assessment of agricultural systems under future climate, biophysical, and socio-economic conditions. These methods were used by the AgMIP regional research teams in Sub-Saharan Africa and South Asia to implement the analyses reported in their respective chapters of this book. Additional technical details are provided in Appendix 1.The principal goal that motivates AgMIP's regional integrated assessment (RIA) methodology is to provide scientifically rigorous information needed to support improved decision-making by various stakeholders, ranging from local to national and international non-governmental and governmental organizations.

An intercomparison of nitric oxide measurement techniques

NASA Technical Reports Server (NTRS)

Hoell, J. M., Jr.; Gregory, G. L.; Mcdougal, D. S.; Carroll, M. A.; Mcfarland, M.; Ridley, B. A.; Davis, D. D.; Bradshaw, J.; Rodgers, M. O.; Torres, A. L.

1985-01-01

Results from an intercomparison of techniques to measure tropospheric levels of nitric oxide (NO) are discussed. The intercomparison was part of the National Aeronautics and Space Administration's Global Tropospheric Experiment and was conducted at Wallops Island, VA, in July 1983. Instruments intercompared included a laser-induced fluorescence system and two chemiluminescence instruments. The intercomparisons were performed with ambient air at NO mixing ratios ranging from 10 to 60 pptv and NO-enriched ambient air at mixing ratios from 20 to 170 pptv. All instruments sampled from a common manifold. The techniques exhibited a high degree of correlation among themselves and with changes in the NO mixing ratio. Agreement among the three techniques was placed at approximately + or - 30 percent. Within this level of agreement, no artifacts or species interferences were identified.

INTERCOMPARISON OF OPTICAL REMOTE SENSING SYSTEMS FOR ROADSIDE MEASUREMENTS

EPA Science Inventory

The presentation describes results of an intercomparison of three optical remote sensing systems for measurements of nitric oxide emitted from passenger cars and light-duty trucks. The intercomparison included a standards comparison to establish comparability of standards, follo...

Inter-comparison of time series models of lake levels predicted by several modeling strategies

NASA Astrophysics Data System (ADS)

Khatibi, R.; Ghorbani, M. A.; Naghipour, L.; Jothiprakash, V.; Fathima, T. A.; Fazelifard, M. H.

2014-04-01

Five modeling strategies are employed to analyze water level time series of six lakes with different physical characteristics such as shape, size, altitude and range of variations. The models comprise chaos theory, Auto-Regressive Integrated Moving Average (ARIMA) - treated for seasonality and hence SARIMA, Artificial Neural Networks (ANN), Gene Expression Programming (GEP) and Multiple Linear Regression (MLR). Each is formulated on a different premise with different underlying assumptions. Chaos theory is elaborated in a greater detail as it is customary to identify the existence of chaotic signals by a number of techniques (e.g. average mutual information and false nearest neighbors) and future values are predicted using the Nonlinear Local Prediction (NLP) technique. This paper takes a critical view of past inter-comparison studies seeking a superior performance, against which it is reported that (i) the performances of all five modeling strategies vary from good to poor, hampering the recommendation of a clear-cut predictive model; (ii) the performances of the datasets of two cases are consistently better with all five modeling strategies; (iii) in other cases, their performances are poor but the results can still be fit-for-purpose; (iv) the simultaneous good performances of NLP and SARIMA pull their underlying assumptions to different ends, which cannot be reconciled. A number of arguments are presented including the culture of pluralism, according to which the various modeling strategies facilitate an insight into the data from different vantages.

The Dynamical Core Model Intercomparison Project (DCMIP-2016): Results of the Supercell Test Case

NASA Astrophysics Data System (ADS)

Zarzycki, C. M.; Reed, K. A.; Jablonowski, C.; Ullrich, P. A.; Kent, J.; Lauritzen, P. H.; Nair, R. D.

2016-12-01

The 2016 Dynamical Core Model Intercomparison Project (DCMIP-2016) assesses the modeling techniques for global climate and weather models and was recently held at the National Center for Atmospheric Research (NCAR) in conjunction with a two-week summer school. Over 12 different international modeling groups participated in DCMIP-2016 and focused on the evaluation of the newest non-hydrostatic dynamical core designs for future high-resolution weather and climate models. The paper highlights the results of the third DCMIP-2016 test case, which is an idealized supercell storm on a reduced-radius Earth. The supercell storm test permits the study of a non-hydrostatic moist flow field with strong vertical velocities and associated precipitation. This test assesses the behavior of global modeling systems at extremely high spatial resolution and is used in the development of next-generation numerical weather prediction capabilities. In this regime the effective grid spacing is very similar to the horizontal scale of convective plumes, emphasizing resolved non-hydrostatic dynamics. The supercell test case sheds light on the physics-dynamics interplay and highlights the impact of diffusion on model solutions.

DCMIP2016: a review of non-hydrostatic dynamical core design and intercomparison of participating models

NASA Astrophysics Data System (ADS)

Ullrich, Paul A.; Jablonowski, Christiane; Kent, James; Lauritzen, Peter H.; Nair, Ramachandran; Reed, Kevin A.; Zarzycki, Colin M.; Hall, David M.; Dazlich, Don; Heikes, Ross; Konor, Celal; Randall, David; Dubos, Thomas; Meurdesoif, Yann; Chen, Xi; Harris, Lucas; Kühnlein, Christian; Lee, Vivian; Qaddouri, Abdessamad; Girard, Claude; Giorgetta, Marco; Reinert, Daniel; Klemp, Joseph; Park, Sang-Hun; Skamarock, William; Miura, Hiroaki; Ohno, Tomoki; Yoshida, Ryuji; Walko, Robert; Reinecke, Alex; Viner, Kevin

2017-12-01

Atmospheric dynamical cores are a fundamental component of global atmospheric modeling systems and are responsible for capturing the dynamical behavior of the Earth's atmosphere via numerical integration of the Navier-Stokes equations. These systems have existed in one form or another for over half of a century, with the earliest discretizations having now evolved into a complex ecosystem of algorithms and computational strategies. In essence, no two dynamical cores are alike, and their individual successes suggest that no perfect model exists. To better understand modern dynamical cores, this paper aims to provide a comprehensive review of 11 non-hydrostatic dynamical cores, drawn from modeling centers and groups that participated in the 2016 Dynamical Core Model Intercomparison Project (DCMIP) workshop and summer school. This review includes a choice of model grid, variable placement, vertical coordinate, prognostic equations, temporal discretization, and the diffusion, stabilization, filters, and fixers employed by each system.

Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization

DOE PAGES

Eyring, Veronika; Bony, Sandrine; Meehl, Gerald A.; ...

2016-05-26

By coordinating the design and distribution of global climate model simulations of the past, current, and future climate, the Coupled Model Intercomparison Project (CMIP) has become one of the foundational elements of climate science. However, the need to address an ever-expanding range of scientific questions arising from more and more research communities has made it necessary to revise the organization of CMIP. After a long and wide community consultation, a new and more federated structure has been put in place. It consists of three major elements: (1) a handful of common experiments, the DECK (Diagnostic, Evaluation and Characterization of Klima) andmore » CMIP historical simulations (1850–near present) that will maintain continuity and help document basic characteristics of models across different phases of CMIP; (2) common standards, coordination, infrastructure, and documentation that will facilitate the distribution of model outputs and the characterization of the model ensemble; and (3) an ensemble of CMIP-Endorsed Model Intercomparison Projects (MIPs) that will be specific to a particular phase of CMIP (now CMIP6) and that will build on the DECK and CMIP historical simulations to address a large range of specific questions and fill the scientific gaps of the previous CMIP phases. The DECK and CMIP historical simulations, together with the use of CMIP data standards, will be the entry cards for models participating in CMIP. Participation in CMIP6-Endorsed MIPs by individual modelling groups will be at their own discretion and will depend on their scientific interests and priorities. With the Grand Science Challenges of the World Climate Research Programme (WCRP) as its scientific backdrop, CMIP6 will address three broad questions: – How does the Earth system respond to forcing? – What are the origins and consequences of systematic model biases? – How can we assess future climate changes given internal climate variability, predictability, and

Representation of the Great Lakes in the Coupled Model Intercomparison Project Version 5

NASA Astrophysics Data System (ADS)

Briley, L.; Rood, R. B.

2017-12-01

The U.S. Great Lakes play a significant role in modifying regional temperatures and precipitation, and as the lakes change in response to a warming climate (i.e., warmer surface water temperatures, decreased ice cover, etc) lake-land-atmosphere dynamics are affected. Because the lakes modify regional weather and are a driver of regional climate change, understanding how they are represented in climate models is important to the reliability of model based information for the region. As part of the Great Lakes Integrated Sciences + Assessments (GLISA) Ensemble project, a major effort is underway to evaluate the Coupled Model Intercomparison Project version (CMIP) 5 global climate models for how well they physically represent the Great Lakes and lake-effects. The CMIP models were chosen because they are a primary source of information in many products developed for decision making (i.e., National Climate Assessment, downscaled future climate projections, etc.), yet there is very little description of how well they represent the lakes. This presentation will describe the results of our investigation of if and how the Great Lakes are represented in the CMIP5 models.

A new Geoengineering Model Intercomparison Project (GeoMIP) experiment designed for climate and chemistry models

DOE PAGES

Tilmes, S.; Mills, Mike; Niemeier, Ulrike; ...

2015-01-15

A new Geoengineering Model Intercomparison Project (GeoMIP) experiment "G4 specified stratospheric aerosols" (short name: G4SSA) is proposed to investigate the impact of stratospheric aerosol geoengineering on atmosphere, chemistry, dynamics, climate, and the environment. In contrast to the earlier G4 GeoMIP experiment, which requires an emission of sulfur dioxide (SO₂) into the model, a prescribed aerosol forcing file is provided to the community, to be consistently applied to future model experiments between 2020 and 2100. This stratospheric aerosol distribution, with a total burden of about 2 Tg S has been derived using the ECHAM5-HAM microphysical model, based on a continuous annualmore » tropical emission of 8 Tg SO₂ yr⁻¹. A ramp-up of geoengineering in 2020 and a ramp-down in 2070 over a period of 2 years are included in the distribution, while a background aerosol burden should be used for the last 3 decades of the experiment. The performance of this experiment using climate and chemistry models in a multi-model comparison framework will allow us to better understand the impact of geoengineering and its abrupt termination after 50 years in a changing environment. The zonal and monthly mean stratospheric aerosol input data set is available at https://www2.acd.ucar.edu/gcm/geomip-g4-specified-stratospheric-aerosol-data-set.« less

Intercomparison of General Circulation Models for Hot Extrasolar Planet Atmospheres

NASA Astrophysics Data System (ADS)

Cho, James

2013-11-01

In this collaborative work with I. Polichtchouk, C. Watkins, H. Th. Thrastarson, O. M. Umurhan, and M. de la Torre-Juárez, we compare five general circulation models (GCMs) which have been recently used to study hot extrasolar planet atmospheres (BOB, CAM, IGCM, MITgcm, and PEQMOD), under three test cases useful for assessing model convergence and accuracy. Such a broad, detailed intercomparison has not been performed thus far for extrasolar planets study. The models considered all solve the traditional primitive equations, but employ different numerical algorithms or grids (e.g., pseudospectral and finite volume, with the latter separately in longitude-latitude and ``cubed-sphere'' grids). The test cases are chosen to cleanly address specific aspects of the behaviors typically reported in hot extrasolar planet simulations: 1) steady-state, 2) nonlinearly evolving baroclinic wave, and 3) response to fast timescale thermal relaxation. When initialized with a steady jet, all models maintain the steadiness, as they should--except MITgcm in cubed-sphere grid. A very good agreement is obtained for a baroclinic wave evolving from an initial instability in spectral models (only). However, exact numerical convergence is still not achieved across the spectral models: amplitudes and phases are observably different. When subject to a typical ``hot-Jupiter''-like forcing, all five models show quantitatively different behavior--although qualitatively similar, time-variable, quadrupole-dominated flows are produced. Hence, as have been advocated in several past studies, specific quantitative predictions (such as the location of large vortices and hot regions) by GCMs should be viewed with caution. Overall, in the tests considered here, spectral models in pressure coordinate (PEBOB and PEQMOD) perform the best and MITgcm in cubed-sphere grid performs the worst. This work has been supported by the Science and Technology Facilities Council, Westfield Small Grant, NASA Postdoctoral

The Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP): Overview and Description of Models, Simulations and Climate Diagnostics

NASA Technical Reports Server (NTRS)

Lamarque, J.-F.; Shindell, D. T.; Naik, V.; Plummer, D.; Josse, B.; Righi, M.; Rumbold, S. T.; Schulz, M.; Skeie, R. B.; Strode, S.;

GEOS observation systems intercomparison investigation results

NASA Technical Reports Server (NTRS)

Berbert, J. H.

1974-01-01

The results of an investigation designed to determine the relative accuracy and precision of the different types of geodetic observation systems used by NASA is presented. A collocation technique was used to minimize the effects of uncertainties in the relative station locations and in the earth's gravity field model by installing accurate reference tracking systems close to the systems to be compared, and by precisely determining their relative survey. The Goddard laser and camera systems were shipped to selected sites, where they tracked the GEOS satellite simultaneously with other systems for an intercomparison observation.

"Development of an interactive crop growth web service architecture to review and forecast agricultural sustainability"

NASA Astrophysics Data System (ADS)

Seamon, E.; Gessler, P. E.; Flathers, E.; Walden, V. P.

2014-12-01

As climate change and weather variability raise issues regarding agricultural production, agricultural sustainability has become an increasingly important component for farmland management (Fisher, 2005, Akinci, 2013). Yet with changes in soil quality, agricultural practices, weather, topography, land use, and hydrology - accurately modeling such agricultural outcomes has proven difficult (Gassman et al, 2007, Williams et al, 1995). This study examined agricultural sustainability and soil health over a heterogeneous multi-watershed area within the Inland Pacific Northwest of the United States (IPNW) - as part of a five year, USDA funded effort to explore the sustainability of cereal production systems (Regional Approaches to Climate Change for Pacific Northwest Agriculture - award #2011-68002-30191). In particular, crop growth and soil erosion were simulated across a spectrum of variables and time periods - using the CropSyst crop growth model (Stockle et al, 2002) and the Water Erosion Protection Project Model (WEPP - Flanagan and Livingston, 1995), respectively. A preliminary range of historical scenarios were run, using a high-resolution, 4km gridded dataset of surface meteorological variables from 1979-2010 (Abatzoglou, 2012). In addition, Coupled Model Inter-comparison Project (CMIP5) global climate model (GCM) outputs were used as input to run crop growth model and erosion future scenarios (Abatzoglou and Brown, 2011). To facilitate our integrated data analysis efforts, an agricultural sustainability web service architecture (THREDDS/Java/Python based) is under development, to allow for the programmatic uploading, sharing and processing of variable input data, running model simulations, as well as downloading and visualizing output results. The results of this study will assist in better understanding agricultural sustainability and erosion relationships in the IPNW, as well as provide a tangible server-based tool for use by researchers and farmers - for both

Potential impacts of agricultural drought on crop yield variability under a changing climate in Texas

NASA Astrophysics Data System (ADS)

Lee, K.; Leng, G.; Huang, M.; Sheffield, J.; Zhao, G.; Gao, H.

2017-12-01

Texas has the largest farm area in the U.S, and its revenue from crop production ranks third overall. With the changing climate, hydrological extremes such as droughts are becoming more frequent and intensified, causing significant yield reduction in rainfed agricultural systems. The objective of this study is to investigate the potential impacts of agricultural drought on crop yields (corn, sorghum, and wheat) under a changing climate in Texas. The Variable Infiltration Capacity (VIC) model, which is calibrated and validated over 10 major Texas river basins during the historical period, is employed in this study.The model is forced by a set of statistically downscaled climate projections from Coupled Model Intercomparison Project Phase 5 (CMIP5) model ensembles at a spatial resolution of 1/8°. The CMIP5 projections contain four Representative Concentration Pathways (RCP) that represent different greenhouse gas concentration (4.5 and 8.5 w/m2 are selected in this study). To carry out the analysis, VIC simulations from 1950 to 2099 are first analyzed to investigate how the frequency and severity of agricultural droughts will be altered in Texas (under a changing climate). Second, future crop yields are projected using a statistical crop model. Third, the effects of agricultural drought on crop yields are quantitatively analyzed. The results are expected to contribute to future water resources planning, with a goal of mitigating the negative impacts of future droughts on agricultural production in Texas.

Global Intercomparison of 12 Land Surface Heat Flux Estimates

NASA Technical Reports Server (NTRS)

Jimenez, C.; Prigent, C.; Mueller, B.; Seneviratne, S. I.; McCabe, M. F.; Wood, E. F.; Rossow, W. B.; Balsamo, G.; Betts, A. K.; Dirmeyer, P. A.;

An evaluation of 20th century climate for the Southeastern United States as simulated by Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models

USGS Publications Warehouse

David E. Rupp,

2016-05-05

The 20th century climate for the Southeastern United States and surrounding areas as simulated by global climate models used in the Coupled Model Intercomparison Project Phase 5 (CMIP5) was evaluated. A suite of statistics that characterize various aspects of the regional climate was calculated from both model simulations and observation-based datasets. CMIP5 global climate models were ranked by their ability to reproduce the observed climate. Differences in the performance of the models between regions of the United States (the Southeastern and Northwestern United States) warrant a regional-scale assessment of CMIP5 models.

Impacts of Stratospheric Black Carbon on Agriculture

NASA Astrophysics Data System (ADS)

Xia, L.; Robock, A.; Elliott, J. W.

2017-12-01

A regional nuclear war between India and Pakistan could inject 5 Tg of soot into the stratosphere, which would absorb sunlight, decrease global surface temperature by about 1°C for 5-10 years and have major impacts on precipitation and the amount of solar radiation reaching Earth's surface. Using two global gridded crop models forced by one global climate model simulation, we investigate the impacts on agricultural productivity in various nations. The crop model in the Community Land Model 4.5 (CLM-crop4.5) and the parallel Decision Support System for Agricultural Technology (pDSSAT) in the parallel System for Integrating Impact Models and Sectors are participating in the Global Gridded Crop Model Intercomparison. We force these two crop models with output from the Whole Atmospheric Community Climate Model to characterize the global agricultural impact from climate changes due to a regional nuclear war. Crops in CLM-crop4.5 include maize, rice, soybean, cotton and sugarcane, and crops in pDSSAT include maize, rice, soybean and wheat. Although the two crop models require a different time frequency of weather input, we downscale the climate model output to provide consistent temperature, precipitation and solar radiation inputs. In general, CLM-crop4.5 simulates a larger global average reduction of maize and soybean production relative to pDSSAT. Global rice production shows negligible change with climate anomalies from a regional nuclear war. Cotton and sugarcane benefit from a regional nuclear war from CLM-crop4.5 simulation, and global wheat production would decrease significantly in the pDSSAT simulation. The regional crop yield responses to a regional nuclear conflict are different for each crop, and we present the changes in production on a national basis. These models do not include the crop responses to changes in ozone, ultraviolet radiation, or diffuse radiation, and we would like to encourage more modelers to improve crop models to account for those

Looking beyond general metrics for model comparison - lessons from an international model intercomparison study

NASA Astrophysics Data System (ADS)

de Boer-Euser, Tanja; Bouaziz, Laurène; De Niel, Jan; Brauer, Claudia; Dewals, Benjamin; Drogue, Gilles; Fenicia, Fabrizio; Grelier, Benjamin; Nossent, Jiri; Pereira, Fernando; Savenije, Hubert; Thirel, Guillaume; Willems, Patrick

2017-01-01

International collaboration between research institutes and universities is a promising way to reach consensus on hydrological model development. Although model comparison studies are very valuable for international cooperation, they do often not lead to very clear new insights regarding the relevance of the modelled processes. We hypothesise that this is partly caused by model complexity and the comparison methods used, which focus too much on a good overall performance instead of focusing on a variety of specific events. In this study, we use an approach that focuses on the evaluation of specific events and characteristics. Eight international research groups calibrated their hourly model on the Ourthe catchment in Belgium and carried out a validation in time for the Ourthe catchment and a validation in space for nested and neighbouring catchments. The same protocol was followed for each model and an ensemble of best-performing parameter sets was selected. Although the models showed similar performances based on general metrics (i.e. the Nash-Sutcliffe efficiency), clear differences could be observed for specific events. We analysed the hydrographs of these specific events and conducted three types of statistical analyses on the entire time series: cumulative discharges, empirical extreme value distribution of the peak flows and flow duration curves for low flows. The results illustrate the relevance of including a very quick flow reservoir preceding the root zone storage to model peaks during low flows and including a slow reservoir in parallel with the fast reservoir to model the recession for the studied catchments. This intercomparison enhanced the understanding of the hydrological functioning of the catchment, in particular for low flows, and enabled to identify present knowledge gaps for other parts of the hydrograph. Above all, it helped to evaluate each model against a set of alternative models.

An inter-comparison of PM10 source apportionment using PCA and PMF receptor models in three European sites.

PubMed

Cesari, Daniela; Amato, F; Pandolfi, M; Alastuey, A; Querol, X; Contini, D

2016-08-01

Source apportionment of aerosol is an important approach to investigate aerosol formation and transformation processes as well as to assess appropriate mitigation strategies and to investigate causes of non-compliance with air quality standards (Directive 2008/50/CE). Receptor models (RMs) based on chemical composition of aerosol measured at specific sites are a useful, and widely used, tool to perform source apportionment. However, an analysis of available studies in the scientific literature reveals heterogeneities in the approaches used, in terms of "working variables" such as the number of samples in the dataset and the number of chemical species used as well as in the modeling tools used. In this work, an inter-comparison of PM10 source apportionment results obtained at three European measurement sites is presented, using two receptor models: principal component analysis coupled with multi-linear regression analysis (PCA-MLRA) and positive matrix factorization (PMF). The inter-comparison focuses on source identification, quantification of source contribution to PM10, robustness of the results, and how these are influenced by the number of chemical species available in the datasets. Results show very similar component/factor profiles identified by PCA and PMF, with some discrepancies in the number of factors. The PMF model appears to be more suitable to separate secondary sulfate and secondary nitrate with respect to PCA at least in the datasets analyzed. Further, some difficulties have been observed with PCA in separating industrial and heavy oil combustion contributions. Commonly at all sites, the crustal contributions found with PCA were larger than those found with PMF, and the secondary inorganic aerosol contributions found by PCA were lower than those found by PMF. Site-dependent differences were also observed for traffic and marine contributions. The inter-comparison of source apportionment performed on complete datasets (using the full range of

An overview of sensor calibration inter-comparison and applications

USGS Publications Warehouse

Xiong, Xiaoxiong; Cao, Changyong; Chander, Gyanesh

2010-01-01

Long-term climate data records (CDR) are often constructed using observations made by multiple Earth observing sensors over a broad range of spectra and a large scale in both time and space. These sensors can be of the same or different types operated on the same or different platforms. They can be developed and built with different technologies and are likely operated over different time spans. It has been known that the uncertainty of climate models and data records depends not only on the calibration quality (accuracy and stability) of individual sensors, but also on their calibration consistency across instruments and platforms. Therefore, sensor calibration inter-comparison and validation have become increasingly demanding and will continue to play an important role for a better understanding of the science product quality. This paper provides an overview of different methodologies, which have been successfully applied for sensor calibration inter-comparison. Specific examples using different sensors, including MODIS, AVHRR, and ETM+, are presented to illustrate the implementation of these methodologies.

Climate model uncertainty in impact assessments for agriculture: A multi-ensemble case study on maize in sub-Saharan Africa

NASA Astrophysics Data System (ADS)

Dale, Amy; Fant, Charles; Strzepek, Kenneth; Lickley, Megan; Solomon, Susan

2017-03-01

We present maize production in sub-Saharan Africa as a case study in the exploration of how uncertainties in global climate change, as reflected in projections from a range of climate model ensembles, influence climate impact assessments for agriculture. The crop model AquaCrop-OS (Food and Agriculture Organization of the United Nations) was modified to run on a 2° × 2° grid and coupled to 122 climate model projections from multi-model ensembles for three emission scenarios (Coupled Model Intercomparison Project Phase 3 [CMIP3] SRES A1B and CMIP5 Representative Concentration Pathway [RCP] scenarios 4.5 and 8.5) as well as two "within-model" ensembles (NCAR CCSM3 and ECHAM5/MPI-OM) designed to capture internal variability (i.e., uncertainty due to chaos in the climate system). In spite of high uncertainty, most notably in the high-producing semi-arid zones, we observed robust regional and sub-regional trends across all ensembles. In agreement with previous work, we project widespread yield losses in the Sahel region and Southern Africa, resilience in Central Africa, and sub-regional increases in East Africa and at the southern tip of the continent. Spatial patterns of yield losses corresponded with spatial patterns of aridity increases, which were explicitly evaluated. Internal variability was a major source of uncertainty in both within-model and between-model ensembles and explained the majority of the spatial distribution of uncertainty in yield projections. Projected climate change impacts on maize production in different regions and nations ranged from near-zero or positive (upper quartile estimates) to substantially negative (lower quartile estimates), highlighting a need for risk management strategies that are adaptive and robust to uncertainty.

Intercomparison of different operational oceanographic forecast products in the CMEMS IBI area

NASA Astrophysics Data System (ADS)

Lorente, Pablo; Sotillo, Marcos G.; Dabrowski, Tomasz; Amo-Baladrón, Arancha; Aznar, Roland; De Pascual, Alvaro; Levier, Bruno; Bowyer, Peter; Cossarini, Gianpiero; Salon, Stefano; Tonani, Marina; Alvarez-Fanjul, Enrique

2017-04-01

The development of skill assessment software packages and dedicated web applications is a relatively novel theme in operational oceanography. Within the CMEMS IBI-MFC, the quality of IBI (Iberia-Biscay-Ireland) forecast products is assessed by means of NARVAL (North Atlantic Regional VALidation) web-based tool. The validation of IBI against independent in situ and remote-sensing measurements is routinely conducted to evaluate model's veracity and prognostic capabilities. Noticeable efforts are in progress to define meaningful skill scores and statistical metrics to quantitatively assess the quality and reliability of the IBI model solution. Likewise, the IBI-MFC compares the IBI forecast products with other model solutions by setting up specific intercomparison exercises on overlapping areas at diverse timescales. In this context, NARVAL web tool already includes a specific module to evaluate strengths and weaknesses of IBI versus other CMEMS operational ocean forecasting systems (OOFSs). In particular, the IBI physical ocean solution is compared against the CMEMS MED and NWS OOFSs. These CMEMS regional services delivered for the Mediterranean and the North West Shelves include data assimilation schemes in their respective operational chains and generate analogous ocean forecast products to the IBI ones. A number of physical parameters (i.e. sea surface temperature, salinity and current velocities) are evaluated through NARVAL on a daily basis in the overlapping areas existing between these three regional systems. NARVAL is currently being updated in order to extend this intercomparison of ocean model parameters to the biogeochemical solutions provided by the aforementioned OOFSs. More specifically, the simulated chlorophyll concentration is evaluated over several subregions of particular concern by using as benchmark the CMEMS satellite-derived observational products. In addition to this IBI comparison against other regional CMEMS products on overlapping areas, a

The Model Intercomparison Project on the Climatic Response to Volcanic Forcing (VolMIP): Experimental Design and Forcing Input Data for CMIP6

NASA Technical Reports Server (NTRS)

Zanchettin, Davide; Khodri, Myriam; Timmreck, Claudia; Toohey, Matthew; Schmidt, Anja; Gerber, Edwin P.; Hegerl, Gabriele; Robock, Alan; Pausata, Francesco; Ball, William T.;

OMIP contribution to CMIP6: experimental and diagnostic protocol for the physical component of the Ocean Model Intercomparison Project

NASA Astrophysics Data System (ADS)

Griffies, Stephen M.; Danabasoglu, Gokhan; Durack, Paul J.; Adcroft, Alistair J.; Balaji, V.; Böning, Claus W.; Chassignet, Eric P.; Curchitser, Enrique; Deshayes, Julie; Drange, Helge; Fox-Kemper, Baylor; Gleckler, Peter J.; Gregory, Jonathan M.; Haak, Helmuth; Hallberg, Robert W.; Heimbach, Patrick; Hewitt, Helene T.; Holland, David M.; Ilyina, Tatiana; Jungclaus, Johann H.; Komuro, Yoshiki; Krasting, John P.; Large, William G.; Marsland, Simon J.; Masina, Simona; McDougall, Trevor J.; Nurser, A. J. George; Orr, James C.; Pirani, Anna; Qiao, Fangli; Stouffer, Ronald J.; Taylor, Karl E.; Treguier, Anne Marie; Tsujino, Hiroyuki; Uotila, Petteri; Valdivieso, Maria; Wang, Qiang; Winton, Michael; Yeager, Stephen G.

2016-09-01

The Ocean Model Intercomparison Project (OMIP) is an endorsed project in the Coupled Model Intercomparison Project Phase 6 (CMIP6). OMIP addresses CMIP6 science questions, investigating the origins and consequences of systematic model biases. It does so by providing a framework for evaluating (including assessment of systematic biases), understanding, and improving ocean, sea-ice, tracer, and biogeochemical components of climate and earth system models contributing to CMIP6. Among the WCRP Grand Challenges in climate science (GCs), OMIP primarily contributes to the regional sea level change and near-term (climate/decadal) prediction GCs.OMIP provides (a) an experimental protocol for global ocean/sea-ice models run with a prescribed atmospheric forcing; and (b) a protocol for ocean diagnostics to be saved as part of CMIP6. We focus here on the physical component of OMIP, with a companion paper (Orr et al., 2016) detailing methods for the inert chemistry and interactive biogeochemistry. The physical portion of the OMIP experimental protocol follows the interannual Coordinated Ocean-ice Reference Experiments (CORE-II). Since 2009, CORE-I (Normal Year Forcing) and CORE-II (Interannual Forcing) have become the standard methods to evaluate global ocean/sea-ice simulations and to examine mechanisms for forced ocean climate variability. The OMIP diagnostic protocol is relevant for any ocean model component of CMIP6, including the DECK (Diagnostic, Evaluation and Characterization of Klima experiments), historical simulations, FAFMIP (Flux Anomaly Forced MIP), C4MIP (Coupled Carbon Cycle Climate MIP), DAMIP (Detection and Attribution MIP), DCPP (Decadal Climate Prediction Project), ScenarioMIP, HighResMIP (High Resolution MIP), as well as the ocean/sea-ice OMIP simulations.

Reproducibility in cyclostratigraphy: initiating an intercomparison project

NASA Astrophysics Data System (ADS)

Sinnesael, Matthias; De Vleeschouwer, David; Zeeden, Christian; Claeys, Philippe

2017-04-01

The study of astronomical climate forcing and the application of cyclostratigraphy have experienced a spectacular growth over the last decades. In the field of cyclostratigraphy a broad range in methodological approaches exist. However, comparative study between the different approaches is lacking. Different cases demand different approaches, but with the growing importance of the field, questions arise about reproducibility, uncertainties and standardization of results. The radioisotopic dating community, in particular, has done far-reaching efforts to improve reproducibility and intercomparison of radioisotopic dates and their errors. To satisfy this need in cyclostratigraphy, we initiate a comparable framework for the community. The aims are to investigate and quantify reproducibility of, and uncertainties related to cyclostratigraphic studies and to provide a platform to discuss the merits and pitfalls of different methodologies, and their applicabilities. With this poster, we ask the feedback from the community on how to design this comparative framework in a useful, meaningful and productive manner. In parallel, we would like to discuss how reproducibility should be tested and what uncertainties should stand for in cyclostratigraphy. On the other hand, we intend to trigger interest for a cyclostratigraphic intercomparison project. This intercomparison project would imply the analysis of artificial and genuine geological records by individual researchers. All participants would be free to determine their method of choice. However, a handful of criterions will be required for an outcome to be comparable. The different results would be compared (e.g. during a workshop or a special session), and the lessons learned from the comparison could potentially be reported in a review paper. The aim of an intercomparison project is not to rank the different methods according to their merits, but to get insight into which specific methods are most suitable for which

The Development Model Electronic Commerce of Regional Agriculture

NASA Astrophysics Data System (ADS)

Kang, Jun; Cai, Lecai; Li, Hongchan

With the developing of the agricultural information, it is inevitable trend of the development of agricultural electronic commercial affairs. On the basis of existing study on the development application model of e-commerce, combined with the character of the agricultural information, compared with the developing model from the theory and reality, a new development model electronic commerce of regional agriculture base on the government is put up, and such key issues as problems of the security applications, payment mode, sharing mechanisms, and legal protection are analyzed, etc. The among coordination mechanism of the region is discussed on, it is significance for regulating the development of agricultural e-commerce and promoting the regional economical development.

LS3MIP (v1.0) Contribution to CMIP6: The Land Surface, Snow and Soil Moisture Model Intercomparison Project Aims, Setup and Expected Outcome.

NASA Technical Reports Server (NTRS)

Van Den Hurk, Bart; Kim, Hyungjun; Krinner, Gerhard; Seneviratne, Sonia I.; Derksen, Chris; Oki, Taikan; Douville, Herve; Colin, Jeanne; Ducharne, Agnes; Cheruy, Frederique;

What is the difference between a 2, 3, 4, or 5 °C world and how good are we at telling this difference? Results from ISI-MIP the first Inter-Sectoral Impact Model Intercomparison Project

NASA Astrophysics Data System (ADS)

Frieler, K.; Huber, V.; Piontek, F.; Schewe, J.; Serdeczny, O.; Warszawski, L.

2012-12-01

The Inter-sectoral Impact Model Intercomparison Project (ISI-MIP) aims to synthesize the state-of-the-art knowledge of climate change impacts at different levels of global warming. Over 25 climate impact modelling teams from around the world, working within the agriculture, water, biomes, infrastructure and health sectors, are collaborating to find answers to the question "What is the difference between a 2, 3, 4, or 5 °C world and how good are we at telling this difference?". The analysis is based on common, bias-corrected climate projections, and socio-economic pathways. The first, fast-tracked phase of the ISI-MIP has a focus on global impact models. The project's experimental design is formulated to distinguish the uncertainty introduced by the impact models themselves, from the inherent uncertainty in the climate projections and the variety of plausible socio-economic futures. Novel metrics, developed to emphasize societal impacts, will be used to identify regional 'hot-spots' of climate change impacts, as well as to quantify the cross-sectoral impact of the increasing frequency of extreme events in future climates. We present here first results from the Fast-Track phase of the project covering impact simulations in the biomes, agriculture and water sectors, in which the societal impacts of climate change are quantified for different levels of global warming. We also discuss the design of the scenario set-up and impact indicators chosen to suit the unique cross-sectoral, multi-model nature of the project.

Impacts on Global Agriculture of Stratospheric Sulfate Injection

NASA Astrophysics Data System (ADS)

Robock, A.; Xia, L.

2014-12-01

Impacts on global food supply are one of the most important concerns in the discussion of stratospheric sulfate geoengineering. Stratospheric sulfate injection could reduce surface temperature, precipitation, and insolation, which could affect agricultural production. We use output from climate model simulations using the two most "realistic" scenarios from the Geoengineering Model Intercomparison Project, G3 and G4. G3 posits balancing the increasing radiative forcing from the RCP4.5 business-as-usual scenario with stratospheric sulfate aerosols from 2020 through 2070. The G4 scenario also uses RCP4.5, but models simulate the stratospheric injection of 5 Tg SO2 per year from 2020 to 2070. In total, there are three modeling groups which have completed G3 and four for G4. We use two crop models, the global gridded Decision Support System for Agrotechnology Transfer (gDSSAT) crop model and the crop model in the NCAR Community Land Model (CLM-crop), to predict global maize yield changes. Without changing agricultural technology, we find that compared to the reference run forced by the RCP4.5 scenario, maize yields could increase in both G3 and G4 due to both the cooling effect of stratospheric sulfate injection and the CO2 fertilization effect, with the cooling effect contributing more to the increased productivity. However, the maize yield changes are not much larger than natural variability under G3, since the temperature reduction is smaller in G3 than in G4. Both crop models show similar results.

Crop modeling applications in agricultural water management

USGS Publications Warehouse

Kisekka, Isaya; DeJonge, Kendall C.; Ma, Liwang; Paz, Joel; Douglas-Mankin, Kyle R.

2017-01-01

This article introduces the fourteen articles that comprise the “Crop Modeling and Decision Support for Optimizing Use of Limited Water” collection. This collection was developed from a special session on crop modeling applications in agricultural water management held at the 2016 ASABE Annual International Meeting (AIM) in Orlando, Florida. In addition, other authors who were not able to attend the 2016 ASABE AIM were also invited to submit papers. The articles summarized in this introductory article demonstrate a wide array of applications in which crop models can be used to optimize agricultural water management. The following section titles indicate the topics covered in this collection: (1) evapotranspiration modeling (one article), (2) model development and parameterization (two articles), (3) application of crop models for irrigation scheduling (five articles), (4) coordinated water and nutrient management (one article), (5) soil water management (two articles), (6) risk assessment of water-limited irrigation management (one article), and (7) regional assessments of climate impact (two articles). Changing weather and climate, increasing population, and groundwater depletion will continue to stimulate innovations in agricultural water management, and crop models will play an important role in helping to optimize water use in agriculture.

A process-based agricultural model for the irrigated agriculture sector in Alberta, Canada

NASA Astrophysics Data System (ADS)

Ammar, M. E.; Davies, E. G.

2015-12-01

Connections between land and water, irrigation, agricultural productivity and profitability, policy alternatives, and climate change and variability are complex, poorly understood, and unpredictable. Policy assessment for agriculture presents a large potential for development of broad-based simulation models that can aid assessment and quantification of policy alternatives over longer temporal scales. The Canadian irrigated agriculture sector is concentrated in Alberta, where it represents two thirds of the irrigated land-base in Canada and is the largest consumer of surface water. Despite interest in irrigation expansion, its potential in Alberta is uncertain given a constrained water supply, significant social and economic development and increasing demands for both land and water, and climate change. This paper therefore introduces a system dynamics model as a decision support tool to provide insights into irrigation expansion in Alberta, and into trade-offs and risks associated with that expansion. It is intended to be used by a wide variety of users including researchers, policy analysts and planners, and irrigation managers. A process-based cropping system approach is at the core of the model and uses a water-driven crop growth mechanism described by AquaCrop. The tool goes beyond a representation of crop phenology and cropping systems by permitting assessment and quantification of the broader, long-term consequences of agricultural policies for Alberta's irrigation sector. It also encourages collaboration and provides a degree of transparency that gives confidence in simulation results. The paper focuses on the agricultural component of the systems model, describing the process involved; soil water and nutrients balance, crop growth, and water, temperature, salinity, and nutrients stresses, and how other disciplines can be integrated to account for the effects of interactions and feedbacks in the whole system. In later stages, other components such as

Evaluation of the annual Canadian biodosimetry network intercomparisons

PubMed Central

Wilkins, Ruth C.; Beaton-Green, Lindsay A.; Lachapelle, Sylvie; Kutzner, Barbara C.; Ferrarotto, Catherine; Chauhan, Vinita; Marro, Leonora; Livingston, Gordon K.; Boulay Greene, Hillary; Flegal, Farrah N.

2015-01-01

Abstract Purpose: To evaluate the importance of annual intercomparisons for maintaining the capacity and capabilities of a well-established biodosimetry network in conjunction with assessing efficient and effective analysis methods for emergency response. Materials and methods: Annual intercomparisons were conducted between laboratories in the Canadian National Biological Dosimetry Response Plan. Intercomparisons were performed over a six-year period and comprised of the shipment of 10–12 irradiated, blinded blood samples for analysis by each of the participating laboratories. Dose estimates were determined by each laboratory using the dicentric chromosome assay (conventional and QuickScan scoring) and where possible the cytokinesis block micronucleus (CBMN) assay. Dose estimates were returned to the lead laboratory for evaluation and comparison. Results: Individual laboratories performed comparably from year to year with only slight fluctuations in performance. Dose estimates using the dicentric chromosome assay were accurate about 80% of the time and the QuickScan method for scoring the dicentric chromosome assay was proven to reduce the time of analysis without having a significant effect on the dose estimates. Although analysis with the CBMN assay was comparable to QuickScan scoring with respect to speed, the accuracy of the dose estimates was greatly reduced. Conclusions: Annual intercomparisons are necessary to maintain a network of laboratories for emergency response biodosimetry as they evoke confidence in their capabilities. PMID:25670072

Comparison of N2O Emissions from Soils at Three Temperate Agricultural Sites

NASA Technical Reports Server (NTRS)

Frolking, S. E.; Moiser, A. R.; Ojima, D. S.; Li, C.; Parton, W. J.; Potter, C. S.; Priesack, E.; Stenger, R.; Haberbosch, C.; Dorsch, P.;

Water vapour intercomparison effort in the frame of HyMeX-SOP1

NASA Astrophysics Data System (ADS)

Summa, Donato; Di Girolamo, Paolo; Stelitano, Dario; Cacciani, Marco; Flamant, Cyrille; Chazette, Patrick; Ducrocq, Véronique; Nuret, Mathieu; Fourié, Nadia; Richard, Evelyne

2014-05-01

A water vapour intercomparison effort, involving airborne and ground-based water vapour lidar systems and mesoscale models, was carried out in the framework of the international HyMeX (Hydrological cycle in the Mediterranean Experiment) dedicated to the hydrological cycle and related high-impact events. Within HyMeX, a major field campaign was dedicated to heavy precipitation and flash flood events from 5 September to 6 November 2012. The 2 month field campaign took place over the Northwestern Mediterranean Sea and its surrounding coastal regions in France, Italy, and Spain. The main objective of this work is to provide accurate error estimates for the lidar systems i.e. the ground-based Raman lidar BASIL and the CNRS DIAL Leandre 2 on board the ATR42, as well as use BASIL data to validate mesoscale model results from the MESO NH and Arome WMED. The effort will benefit from the few dedicated ATR42 flights in the frame of the EUFAR Project "WaLiTemp". In the present work our attention was focused on two specific case studies: 13 September and 2 October in the altitude region 0.5 - 5.5 km. Comparisons between the ground-based Raman lidar BASIL and the airborne CNRS DIAL indicate a mean relative bias between the two sensors of 6.5%, while comparisons between BASIL and CNRS DIAL vs. the radiosondes indicate a bias of 2.6 and -3.5 %, respectively. The bias of BASIL vs. the ATR insitu sensor indicate a bias of -20.4 %. Specific attention will also be dedicated to the WALI/BASIL intercomparison effort which took place in Candillargues on 30 October 2012. Specific results from this intercomparison effort and from the intercomparison between BASIL and Meso-NH/AROME-WMed will be illustrated and discussed at the Conference.

Design of the MISMIP+, ISOMIP+, and MISOMIP ice-sheet, ocean, and coupled ice sheet-ocean intercomparison projects

NASA Astrophysics Data System (ADS)

Asay-Davis, Xylar; Cornford, Stephen; Martin, Daniel; Gudmundsson, Hilmar; Holland, David; Holland, Denise

2015-04-01

The MISMIP and MISMIP3D marine ice sheet model intercomparison exercises have become popular benchmarks, and several modeling groups have used them to show how their models compare to both analytical results and other models. Similarly, the ISOMIP (Ice Shelf-Ocean Model Intercomparison Project) experiments have acted as a proving ground for ocean models with sub-ice-shelf cavities.As coupled ice sheet-ocean models become available, an updated set of benchmark experiments is needed. To this end, we propose sequel experiments, MISMIP+ and ISOMIP+, with an end goal of coupling the two in a third intercomparison exercise, MISOMIP (the Marine Ice Sheet-Ocean Model Intercomparison Project). Like MISMIP3D, the MISMIP+ experiments take place in an idealized, three-dimensional setting and compare full 3D (Stokes) and reduced, hydrostatic models. Unlike the earlier exercises, the primary focus will be the response of models to sub-shelf melting. The chosen configuration features an ice shelf that experiences substantial lateral shear and buttresses the upstream ice, and so is well suited to melting experiments. Differences between the steady states of each model are minor compared to the response to melt-rate perturbations, reflecting typical real-world applications where parameters are chosen so that the initial states of all models tend to match observations. The three ISOMIP+ experiments have been designed to to make use of the same bedrock topography as MISMIP+ and using ice-shelf geometries from MISMIP+ results produced by the BISICLES ice-sheet model. The first two experiments use static ice-shelf geometries to simulate the evolution of ocean dynamics and resulting melt rates to a quasi-steady state when far-field forcing changes in either from cold to warm or from warm to cold states. The third experiment prescribes 200 years of dynamic ice-shelf geometry (with both retreating and advancing ice) based on a BISICLES simulation along with similar flips between warm and

Comparing crop growth and carbon budgets simulated across AmeriFlux agricultural sites using the community land model (CLM)

USDA-ARS?s Scientific Manuscript database

Improving process-based crop models is needed to achieve high fidelity forecasts of regional energy, water, and carbon exchange. However, most state-of-the-art Land Surface Models (LSMs) assessed in the fifth phase of the Coupled Model Inter-comparison project (CMIP5) simulated crops as simple C3 or...

BRDF Characterization and Calibration Inter-Comparison between Terra MODIS, Aqua MODIS, and S-NPP VIIRS

NASA Technical Reports Server (NTRS)

Chang, Tiejun; Xiong, Xiaoxiong (Jack); Angal, Amit; Wu, Aisheng

2016-01-01

The inter-comparison of reflective solar bands (RSB) between Terra MODIS, Aqua MODIS, and SNPP VIIRS is very important for assessment of each instrument's calibration and to identify calibration improvements. One of the limitations of using their ground observations for the assessment is a lack of the simultaneous nadir overpasses (SNOs) over selected pseudo-invariant targets. In addition, their measurements over a selected Earth view target have significant difference in solar and view angles, and these differences magnify the effects of Bidirectional Reflectance Distribution Function (BRDF). In this work, an inter-comparison technique using a semi-empirical BRDF model is developed for reflectance correction. BRDF characterization requires a broad coverage of solar and view angles in the measurements over selected pseudo-invariant targets. Reflectance measurements over Libya 1, 2, and 4 desert sites from both the Aqua and Terra MODIS are regressed to a BRDF model with an adjustable coefficient accounting for the calibration difference between the two instruments. The BRDF coefficients for three desert sites for MODIS bands 1 to 9 are derived and the wavelength dependencies are presented. The analysis and inter-comparison are for MODIS bands 1 to 9 and VIIRS moderate resolution radiometric bands (M bands) M1, M2, M4, M5, M7, M8, M10 and imaging bands (I bands) I1-I3. Results show that the ratios from different sites are in good agreement. The ratios between Terra and Aqua MODIS from year 2003 to 2014 are presented. The inter-comparison between MODIS and VIIRS are analyzed for year 2014.

Global dust model intercomparison in AeroCom phase I

NASA Astrophysics Data System (ADS)

Huneeus, N.; Schulz, M.; Balkanski, Y.; Griesfeller, J.; Prospero, J.; Kinne, S.; Bauer, S.; Boucher, O.; Chin, M.; Dentener, F.; Diehl, T.; Easter, R.; Fillmore, D.; Ghan, S.; Ginoux, P.; Grini, A.; Horowitz, L.; Koch, D.; Krol, M. C.; Landing, W.; Liu, X.; Mahowald, N.; Miller, R.; Morcrette, J.-J.; Myhre, G.; Penner, J.; Perlwitz, J.; Stier, P.; Takemura, T.; Zender, C. S.

2011-08-01

This study presents the results of a broad intercomparison of a total of 15 global aerosol models within the AeroCom project. Each model is compared to observations related to desert dust aerosols, their direct radiative effect, and their impact on the biogeochemical cycle, i.e., aerosol optical depth (AOD) and dust deposition. Additional comparisons to Angström exponent (AE), coarse mode AOD and dust surface concentrations are included to extend the assessment of model performance and to identify common biases present in models. These data comprise a benchmark dataset that is proposed for model inspection and future dust model development. There are large differences among the global models that simulate the dust cycle and its impact on climate. In general, models simulate the climatology of vertically integrated parameters (AOD and AE) within a factor of two whereas the total deposition and surface concentration are reproduced within a factor of 10. In addition, smaller mean normalized bias and root mean square errors are obtained for the climatology of AOD and AE than for total deposition and surface concentration. Characteristics of the datasets used and their uncertainties may influence these differences. Large uncertainties still exist with respect to the deposition fluxes in the southern oceans. Further measurements and model studies are necessary to assess the general model performance to reproduce dust deposition in ocean regions sensible to iron contributions. Models overestimate the wet deposition in regions dominated by dry deposition. They generally simulate more realistic surface concentration at stations downwind of the main sources than at remote ones. Most models simulate the gradient in AOD and AE between the different dusty regions. However the seasonality and magnitude of both variables is better simulated at African stations than Middle East ones. The models simulate the offshore transport of West Africa throughout the year but they

Intercomparison of Operational Ocean Forecasting Systems in the framework of GODAE

NASA Astrophysics Data System (ADS)

Hernandez, F.

2009-04-01

representation, either due to model and forcing fields errors, or assimilation scheme efficiency. Comparisons to sea-ice satellite products also evidence discrepancies linked to model, forcing and assimilation strategies of each forecasting system. Key words: Intercomparison, ocean analysis, operational oceanography, system assessment, metrics, validation GODAE Intercomparison Team: L. Bertino (NERSC/Norway), G. Brassington (BMRC/Australia), E. Chassignet (FSU/USA), J. Cummings (NRL/USA), F. Davidson (DFO/Canda), M. Drévillon (CERFACS/France), P. Hacker (IPRC/USA), M. Kamachi (MRI/Japan), J.-M. Lellouche (CERFACS/France), K. A. Lisæter (NERSC/Norway), R. Mahdon (UKMO/UK), M. Martin (UKMO/UK), A. Ratsimandresy (DFO/Canada), and C. Regnier (Mercator Ocean/France)

Manufacture and calibration of optical supersmooth roughness artifacts for intercomparisons

NASA Astrophysics Data System (ADS)

Ringel, Gabriele A.; Kratz, Frank; Schmitt, Dirk-Roger; Mangelsdorf, Juergen; Creuzet, Francois; Garratt, John D.

1995-09-01

Intercomparison roughness measurements have been carried out on supersmooth artifacts fabricated from BK7, fused silica, and Zerodur. The surface parameters were determined using the optical heterodyne profiler Z5500 (Zygo), a special prototype of the mechanical profiler Nanostep (Rank Taylor Hobson), and an Atomic Force Microscope (Park Scientific Instruments) with an improved acquisition technique. The intercomparison was performed after the range of collected spatial wavelengths for each instrument was adjusted using digital filtering techniques. It is demonstrated for different roughness ranges that the applied superpolishing techniques yield supersmooth artifacts which can be used for more intercomparisons. More than 100 samples were investigated. Criteria were developed to select artifacts from the sample stock.

Future water supply and demand in response to climate change and agricultural expansion in Texas

NASA Astrophysics Data System (ADS)

Lee, K.; Zhou, T.; Gao, H.; Huang, M.

2016-12-01

With ongoing global environmental change and an increasing population, it is challenging (to say the least) to understand the complex interactions of irrigation and reservoir systems. Irrigation is critical to agricultural production and food security, and is a vital component of Texas' agricultural economy. Agricultural irrigation currently accounts for about 60% of total water demand in Texas, and recent occurrences of severe droughts has brought attention to the availability and use of water in the future. In this study, we aim to assess future agricultural irrigation water demand, and to estimate how changes in the fraction of crop irrigated land will affect future water availability in Texas, which has the largest farm area and the highest value of livestock production in the United States. The Variable Infiltration Capacity (VIC) model, which has been calibrated and validated over major Texas river basins during the historical period, is employed for this study. The VIC model, coupling with an irrigation scheme and a reservoir module, is adopted to simulate the water management and regulations. The evolution on agricultural land is also considered in the model as a changing fraction of crop for each grid cell. The reservoir module is calibrated and validated based on the historical (1915-2011) storage records of major reservoirs in Texas. The model is driven by statistically downscaled climate projections from Coupled Model Intercomparison Project Phase 5 (CMIP5) model ensembles at a spatial resolution of 1/8°. The lowest (RCP 2.6) and highest (RC P8.5) greenhouse-gas concentration scenarios are adopted for future projections to provide an estimate of uncertainty bounds. We expect that our results will be helpful to assist decision making related to reservoir operations and agricultural water planning for Texas under future climate and environmental changes.

Comparing impacts of climate change and mitigation on global agriculture by 2050

NASA Astrophysics Data System (ADS)

van Meijl, Hans; Havlik, Petr; Lotze-Campen, Hermann; Stehfest, Elke; Witzke, Peter; Pérez Domínguez, Ignacio; Bodirsky, Benjamin Leon; van Dijk, Michiel; Doelman, Jonathan; Fellmann, Thomas; Humpenöder, Florian; Koopman, Jason F. L.; Müller, Christoph; Popp, Alexander; Tabeau, Andrzej; Valin, Hugo; van Zeist, Willem-Jan

2018-06-01

Systematic model inter-comparison helps to narrow discrepancies in the analysis of the future impact of climate change on agricultural production. This paper presents a set of alternative scenarios by five global climate and agro-economic models. Covering integrated assessment (IMAGE), partial equilibrium (CAPRI, GLOBIOM, MAgPIE) and computable general equilibrium (MAGNET) models ensures a good coverage of biophysical and economic agricultural features. These models are harmonized with respect to basic model drivers, to assess the range of potential impacts of climate change on the agricultural sector by 2050. Moreover, they quantify the economic consequences of stringent global emission mitigation efforts, such as non-CO2 emission taxes and land-based mitigation options, to stabilize global warming at 2 °C by the end of the century under different Shared Socioeconomic Pathways. A key contribution of the paper is a vis-à-vis comparison of climate change impacts relative to the impact of mitigation measures. In addition, our scenario design allows assessing the impact of the residual climate change on the mitigation challenge. From a global perspective, the impact of climate change on agricultural production by mid-century is negative but small. A larger negative effect on agricultural production, most pronounced for ruminant meat production, is observed when emission mitigation measures compliant with a 2 °C target are put in place. Our results indicate that a mitigation strategy that embeds residual climate change effects (RCP2.6) has a negative impact on global agricultural production relative to a no-mitigation strategy with stronger climate impacts (RCP6.0). However, this is partially due to the limited impact of the climate change scenarios by 2050. The magnitude of price changes is different amongst models due to methodological differences. Further research to achieve a better harmonization is needed, especially regarding endogenous food and feed

iMarNet: an ocean biogeochemistry model intercomparison project within a common physical ocean modelling framework

NASA Astrophysics Data System (ADS)

Kwiatkowski, L.; Yool, A.; Allen, J. I.; Anderson, T. R.; Barciela, R.; Buitenhuis, E. T.; Butenschön, M.; Enright, C.; Halloran, P. R.; Le Quéré, C.; de Mora, L.; Racault, M.-F.; Sinha, B.; Totterdell, I. J.; Cox, P. M.

2014-12-01

Ocean biogeochemistry (OBGC) models span a wide variety of complexities, including highly simplified nutrient-restoring schemes, nutrient-phytoplankton-zooplankton-detritus (NPZD) models that crudely represent the marine biota, models that represent a broader trophic structure by grouping organisms as plankton functional types (PFTs) based on their biogeochemical role (dynamic green ocean models) and ecosystem models that group organisms by ecological function and trait. OBGC models are now integral components of Earth system models (ESMs), but they compete for computing resources with higher resolution dynamical setups and with other components such as atmospheric chemistry and terrestrial vegetation schemes. As such, the choice of OBGC in ESMs needs to balance model complexity and realism alongside relative computing cost. Here we present an intercomparison of six OBGC models that were candidates for implementation within the next UK Earth system model (UKESM1). The models cover a large range of biological complexity (from 7 to 57 tracers) but all include representations of at least the nitrogen, carbon, alkalinity and oxygen cycles. Each OBGC model was coupled to the ocean general circulation model Nucleus for European Modelling of the Ocean (NEMO) and results from physically identical hindcast simulations were compared. Model skill was evaluated for biogeochemical metrics of global-scale bulk properties using conventional statistical techniques. The computing cost of each model was also measured in standardised tests run at two resource levels. No model is shown to consistently outperform all other models across all metrics. Nonetheless, the simpler models are broadly closer to observations across a number of fields and thus offer a high-efficiency option for ESMs that prioritise high-resolution climate dynamics. However, simpler models provide limited insight into more complex marine biogeochemical processes and ecosystem pathways, and a parallel approach of

Cloud radiative effects and changes simulated by the Coupled Model Intercomparison Project Phase 5 models

NASA Astrophysics Data System (ADS)

Shin, Sun-Hee; Kim, Ok-Yeon; Kim, Dongmin; Lee, Myong-In

2017-07-01

Using 32 CMIP5 (Coupled Model Intercomparison Project Phase 5) models, this study examines the veracity in the simulation of cloud amount and their radiative effects (CREs) in the historical run driven by observed external radiative forcing for 1850-2005, and their future changes in the RCP (Representative Concentration Pathway) 4.5 scenario runs for 2006-2100. Validation metrics for the historical run are designed to examine the accuracy in the representation of spatial patterns for climatological mean, and annual and interannual variations of clouds and CREs. The models show large spread in the simulation of cloud amounts, specifically in the low cloud amount. The observed relationship between cloud amount and the controlling large-scale environment are also reproduced diversely by various models. Based on the validation metrics, four models—ACCESS1.0, ACCESS1.3, HadGEM2-CC, and HadGEM2-ES—are selected as best models, and the average of the four models performs more skillfully than the multimodel ensemble average. All models project global-mean SST warming at the increase of the greenhouse gases, but the magnitude varies across the simulations between 1 and 2 K, which is largely attributable to the difference in the change of cloud amount and distribution. The models that simulate more SST warming show a greater increase in the net CRE due to reduced low cloud and increased incoming shortwave radiation, particularly over the regions of marine boundary layer in the subtropics. Selected best-performing models project a significant reduction in global-mean cloud amount of about -0.99% K-1 and net radiative warming of 0.46 W m-2 K-1, suggesting a role of positive feedback to global warming.

A comparison of two Stokes ice sheet models applied to the Marine Ice Sheet Model Intercomparison Project for plan view models (MISMIP3d)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Tong; Price, Stephen F.; Ju, Lili

Here, we present a comparison of the numerics and simulation results for two "full" Stokes ice sheet models, FELIX-S (Leng et al. 2012) and Elmer/Ice. The models are applied to the Marine Ice Sheet Model Intercomparison Project for plan view models (MISMIP3d). For the diagnostic experiment (P75D) the two models give similar results (< 2 % difference with respect to along-flow velocities) when using identical geometries and computational meshes, which we interpret as an indication of inherent consistencies and similarities between the two models. For the standard (Stnd), P75S, and P75R prognostic experiments, we find that FELIX-S (Elmer/Ice) grounding linesmore » are relatively more retreated (advanced), results that are consistent with minor differences observed in the diagnostic experiment results and that we show to be due to different choices in the implementation of basal boundary conditions in the two models. While we are not able to argue for the relative favorability of either implementation, we do show that these differences decrease with increasing horizontal (i.e., both along- and across-flow) grid resolution and that grounding-line positions for FELIX-S and Elmer/Ice converge to within the estimated truncation error for Elmer/Ice. Stokes model solutions are often treated as an accuracy metric in model intercomparison experiments, but computational cost may not always allow for the use of model resolution within the regime of asymptotic convergence. In this case, we propose that an alternative estimate for the uncertainty in the grounding-line position is the span of grounding-line positions predicted by multiple Stokes models.« less

A comparison of two Stokes ice sheet models applied to the Marine Ice Sheet Model Intercomparison Project for plan view models (MISMIP3d)

DOE PAGES

Zhang, Tong; Price, Stephen F.; Ju, Lili; ...

2017-01-25

Here, we present a comparison of the numerics and simulation results for two "full" Stokes ice sheet models, FELIX-S (Leng et al. 2012) and Elmer/Ice. The models are applied to the Marine Ice Sheet Model Intercomparison Project for plan view models (MISMIP3d). For the diagnostic experiment (P75D) the two models give similar results (< 2 % difference with respect to along-flow velocities) when using identical geometries and computational meshes, which we interpret as an indication of inherent consistencies and similarities between the two models. For the standard (Stnd), P75S, and P75R prognostic experiments, we find that FELIX-S (Elmer/Ice) grounding linesmore » are relatively more retreated (advanced), results that are consistent with minor differences observed in the diagnostic experiment results and that we show to be due to different choices in the implementation of basal boundary conditions in the two models. While we are not able to argue for the relative favorability of either implementation, we do show that these differences decrease with increasing horizontal (i.e., both along- and across-flow) grid resolution and that grounding-line positions for FELIX-S and Elmer/Ice converge to within the estimated truncation error for Elmer/Ice. Stokes model solutions are often treated as an accuracy metric in model intercomparison experiments, but computational cost may not always allow for the use of model resolution within the regime of asymptotic convergence. In this case, we propose that an alternative estimate for the uncertainty in the grounding-line position is the span of grounding-line positions predicted by multiple Stokes models.« less

Integrating seasonal climate prediction and agricultural models for insights into agricultural practice

PubMed Central

Hansen, James W

2005-01-01

Interest in integrating crop simulation models with dynamic seasonal climate forecast models is expanding in response to a perceived opportunity to add value to seasonal climate forecasts for agriculture. Integrated modelling may help to address some obstacles to effective agricultural use of climate information. First, modelling can address the mismatch between farmers' needs and available operational forecasts. Probabilistic crop yield forecasts are directly relevant to farmers' livelihood decisions and, at a different scale, to early warning and market applications. Second, credible ex ante evidence of livelihood benefits, using integrated climate–crop–economic modelling in a value-of-information framework, may assist in the challenge of obtaining institutional, financial and political support; and inform targeting for greatest benefit. Third, integrated modelling can reduce the risk and learning time associated with adaptation and adoption, and related uncertainty on the part of advisors and advocates. It can provide insights to advisors, and enhance site-specific interpretation of recommendations when driven by spatial data. Model-based ‘discussion support systems’ contribute to learning and farmer–researcher dialogue. Integrated climate–crop modelling may play a genuine, but limited role in efforts to support climate risk management in agriculture, but only if they are used appropriately, with understanding of their capabilities and limitations, and with cautious evaluation of model predictions and of the insights that arises from model-based decision analysis. PMID:16433092

ACIX: Atmospheric Correction Inter-comparison Exercise

NASA Astrophysics Data System (ADS)

Doxani, Georgia; Gascon, Ferran; Vermote, Éric; Roger, Jean-Claude

2017-04-01

The free and open data access policy to Sentinel-2 (S-2) and Landsat-8 (L-8) satellite imagery has stimulated the development of atmospheric correction (AC) processors for generating Bottom-of-Atmosphere (BOA) products. Several entities have started to generate (or plan to generate in the short term) BOA reflectance products at global scale for S-2 and L-8 missions. To this end, the European Space Agency (ESA) and NASA are organizing an exercise on AC processors inter-comparison. The results of the exercise are expected to point out the strengths and weaknesses, as well as communalities and discrepancies of various AC processors, in order to suggest and define ways for their further improvement. In particular, 13 atmospheric processors from five different countries participate in ACIX with the aim to inter-compare their performance when applied to L-8 and S-2 data. A protocol describing the inter-comparison process and the test dataset, which is based on the AERONET sites, will be presented. The protocol has been defined according to what was agreed among the participants during the 1st ACIX workshop held in June 2016. It includes the comparison of aerosol optical thickness and water vapour products of the processors with the AERONET measurements. Moreover, concerning the surface reflectances, the protocol describes the inter-comparison among the processors, as well as the comparison with the MODIS surface reflectance and with a reference surface reflectance product. Such a reference product will be obtained using the AERONET characterization of the aerosol (size distribution and refractive indices) and an accurate radiative transfer code. The inter-comparison outcomes will be presented and discussed among the participants in the 2nd ACIX workshop, which will be held on 11-12 April 2017 (ESRIN/ESA). The proposed presentation is an opportunity for the user community to be informed for the first time about the ACIX results and conclusions.

Cloud-resolving model intercomparison of an MC3E squall line case: Part I-Convective updrafts: CRM Intercomparison of a Squall Line

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fan, Jiwen; Han, Bin; Varble, Adam

A constrained model intercomparison study of a mid-latitude mesoscale squall line is performed using the Weather Research & Forecasting (WRF) model at 1-km horizontal grid spacing with eight cloud microphysics schemes, to understand specific processes that lead to the large spread of simulated cloud and precipitation at cloud-resolving scales, with a focus of this paper on convective cores. Various observational data are employed to evaluate the baseline simulations. All simulations tend to produce a wider convective area than observed, but a much narrower stratiform area, with most bulk schemes overpredicting radar reflectivity. The magnitudes of the virtual potential temperature drop,more » pressure rise, and the peak wind speed associated with the passage of the gust front are significantly smaller compared with the observations, suggesting simulated cool pools are weaker. Simulations also overestimate the vertical velocity and Ze in convective cores as compared with observational retrievals. The modeled updraft velocity and precipitation have a significant spread across the eight schemes even in this strongly dynamically-driven system. The spread of updraft velocity is attributed to the combined effects of the low-level perturbation pressure gradient determined by cold pool intensity and buoyancy that is not necessarily well correlated to differences in latent heating among the simulations. Variability of updraft velocity between schemes is also related to differences in ice-related parameterizations, whereas precipitation variability increases in no-ice simulations because of scheme differences in collision-coalescence parameterizations.« less

The forest and agricultural sector optimization model (FASOM): model structure and policy applications.

Treesearch

Darius M. Adams; Ralph J. Alig; J.M. Callaway; Bruce A. McCarl; Steven M. Winnett

1996-01-01

The Forest and Agricultural Sector Optimization Model (FASOM) is a dynamic, nonlinear programming model of the forest and agricultural sectors in the United States. The FASOM model initially was developed to evaluate welfare and market impacts of alternative policies for sequestering carbon in trees but also has been applied to a wider range of forest and agricultural...

Setting up a model intercomparison project for the last deglaciation

NASA Astrophysics Data System (ADS)

Ivanovic, R. F.; Gregoire, L. J.; Valdes, P. J.; Roche, D. M.; Kageyama, M.

2014-12-01

The last deglaciation (~ 21-9 ka) presents a series of opportunities to study the underlying mechanisms of abrupt climate changes and long-term trends in the Earth System. Most of the forcings are relatively well constrained and geological archives record responses over a range of timescales. Despite this, large uncertainties remain over the feedback loops that culminated in the collapse of the great Northern Hemisphere ice sheets, and a consensus has yet to be reached on the chains of events that led to rapid surface warming and cooling during this period.Climate models are powerful tools for quantitatively assessing these outstanding issues through their ability to temporally resolve cause and effect, as well as break down the contributions from different forcings. This is well demonstrated by pioneering work; for example by Liu et al. (2009), Roche et al. (2011), Gregoire et al. (2012) and Menviel et al. (2011). However, such work is not without challenges; model-geological data mismatches remain unsolved and it is difficult to compare results from different models with unique experiment designs. Therefore, we have established a multidisciplinary Paleoclimate Model Intercomparison Project working group to coordinate transient climate model simulations and geological archive compilations of the last deglaciation. Here, we present the plans and progress of the working group in its first phase of activity; the investigation of Heinrich Stadial 1 and the lead into the Bolling warming event. We describe the set-up of the core deglacial experiment, explain our approach for dealing with uncertain climate forcings and outline our solutions to challenges posed by this research. By defining a common experiment design, we have built a framework to include models of different speeds, complexities and resolution, maximising the reward of this varied approach. One of the next challenges is to compile transient proxy records and develop a methodology for dealing with

Introduction of the 2nd Phase of the Integrated Hydrologic Model Intercomparison Project

NASA Astrophysics Data System (ADS)

Kollet, Stefan; Maxwell, Reed; Dages, Cecile; Mouche, Emmanuel; Mugler, Claude; Paniconi, Claudio; Park, Young-Jin; Putti, Mario; Shen, Chaopeng; Stisen, Simon; Sudicky, Edward; Sulis, Mauro; Ji, Xinye

2015-04-01

The 2nd Phase of the Integrated Hydrologic Model Intercomparison Project commenced in June 2013 with a workshop at Bonn University funded by the German Science Foundation and US National Science Foundation. Three test cases were defined and compared that are available online at www.hpsc-terrsys.de including a tilted v-catchment case; a case called superslab based on multiple slab-heterogeneities in the hydraulic conductivity along a hillslope; and the Borden site case, based on a published field experiment. The goal of this phase is to further interrogate the coupling of surface-subsurface flow implemented in various integrated hydrologic models; and to understand and quantify the impact of differences in the conceptual and technical implementations on the simulation results, which may constitute an additional source of uncertainty. The focus has been broadened considerably including e.g. saturated and unsaturated subsurface storages, saturated surface area, ponded surface storage in addition to discharge, and pressure/saturation profiles and cross-sections. Here, first results are presented and discussed demonstrating the conceptual and technical challenges in implementing essentially the same governing equations describing highly non-linear moisture redistribution processes and surface-groundwater interactions.

LS3MIP (v1.0) contribution to CMIP6: the Land Surface, Snow and Soilmoisture Model Intercomparison Project – aims, setup and expected outcome

DOE PAGES

van den Hurk, Bart; Kim, Hyungjun; Krinner, Gerhard; ...

2016-08-24

The Land Surface, Snow and Soil Moisture Model Intercomparison Project (LS3MIP) is designed to provide a comprehensive assessment of land surface, snow and soil moisture feedbacks on climate variability and climate change, and to diagnose systematic biases in the land modules of current Earth system models (ESMs). Furthermore, the solid and liquid water stored at the land surface has a large influence on the regional climate, its variability and predictability, including effects on the energy, water and carbon cycles. Notably, snow and soil moisture affect surface radiation and flux partitioning properties, moisture storage and land surface memory. They both stronglymore » affect atmospheric conditions, in particular surface air temperature and precipitation, but also large-scale circulation patterns. But, models show divergent responses and representations of these feedbacks as well as systematic biases in the underlying processes. LS3MIP will provide the means to quantify the associated uncertainties and better constrain climate change projections, which is of particular interest for highly vulnerable regions (densely populated areas, agricultural regions, the Arctic, semi-arid and other sensitive terrestrial ecosystems). The experiments are subdivided in two components, the first addressing systematic land biases in offline mode (“LMIP”, building upon the 3rd phase of Global Soil Wetness Project; GSWP3) and the second addressing land feedbacks attributed to soil moisture and snow in an integrated framework (“LFMIP”, building upon the GLACE-CMIP blueprint).« less

LS3MIP (v1.0) contribution to CMIP6: the Land Surface, Snow and Soilmoisture Model Intercomparison Project – aims, setup and expected outcome

DOE Office of Scientific and Technical Information (OSTI.GOV)

van den Hurk, Bart; Kim, Hyungjun; Krinner, Gerhard

The Land Surface, Snow and Soil Moisture Model Intercomparison Project (LS3MIP) is designed to provide a comprehensive assessment of land surface, snow and soil moisture feedbacks on climate variability and climate change, and to diagnose systematic biases in the land modules of current Earth system models (ESMs). Furthermore, the solid and liquid water stored at the land surface has a large influence on the regional climate, its variability and predictability, including effects on the energy, water and carbon cycles. Notably, snow and soil moisture affect surface radiation and flux partitioning properties, moisture storage and land surface memory. They both stronglymore » affect atmospheric conditions, in particular surface air temperature and precipitation, but also large-scale circulation patterns. But, models show divergent responses and representations of these feedbacks as well as systematic biases in the underlying processes. LS3MIP will provide the means to quantify the associated uncertainties and better constrain climate change projections, which is of particular interest for highly vulnerable regions (densely populated areas, agricultural regions, the Arctic, semi-arid and other sensitive terrestrial ecosystems). The experiments are subdivided in two components, the first addressing systematic land biases in offline mode (“LMIP”, building upon the 3rd phase of Global Soil Wetness Project; GSWP3) and the second addressing land feedbacks attributed to soil moisture and snow in an integrated framework (“LFMIP”, building upon the GLACE-CMIP blueprint).« less

The Community Intercomparison Suite (CIS)

NASA Astrophysics Data System (ADS)

Watson-Parris, Duncan; Schutgens, Nick; Cook, Nick; Kipling, Zak; Kershaw, Phil; Gryspeerdt, Ed; Lawrence, Bryan; Stier, Philip

2017-04-01

Earth observations (both remote and in-situ) create vast amounts of data providing invaluable constraints for the climate science community. Efficient exploitation of these complex and highly heterogeneous datasets has been limited however by the lack of suitable software tools, particularly for comparison of gridded and ungridded data, thus reducing scientific productivity. CIS (http://cistools.net) is an open-source, command line tool and Python library which allows the straight-forward quantitative analysis, intercomparison and visualisation of remote sensing, in-situ and model data. The CIS can read gridded and ungridded remote sensing, in-situ and model data - and many other data sources 'out-of-the-box', such as ESA Aerosol and Cloud CCI product, MODIS, Cloud CCI, Cloudsat, AERONET. Perhaps most importantly however CIS also employs a modular plugin architecture to allow for the reading of limitless different data types. Users are able to write their own plugins for reading the data sources which they are familiar with, and share them within the community, allowing all to benefit from their expertise. To enable the intercomparison of this data the CIS provides a number of operations including: the aggregation of ungridded and gridded datasets to coarser representations using a number of different built in averaging kernels; the subsetting of data to reduce its extent or dimensionality; the co-location of two distinct datasets onto a single set of co-ordinates; the visualisation of the input or output data through a number of different plots and graphs; the evaluation of arbitrary mathematical expressions against any number of datasets; and a number of other supporting functions such as a statistical comparison of two co-located datasets. These operations can be performed efficiently on local machines or large computing clusters - and is already available on the JASMIN computing facility. A case-study using the GASSP collection of in-situ aerosol observations

Global dust model intercomparison in AeroCom phase I

NASA Astrophysics Data System (ADS)

Huneeus, N.; Schulz, M.; Balkanski, Y.; Griesfeller, J.; Kinne, S.; Prospero, J.; Bauer, S.; Boucher, O.; Chin, M.; Dentener, F.; Diehl, T.; Easter, R.; Fillmore, D.; Ghan, S.; Ginoux, P.; Grini, A.; Horowitz, L.; Koch, D.; Krol, M. C.; Landing, W.; Liu, X.; Mahowald, N.; Miller, R.; Morcrette, J.-J.; Myhre, G.; Penner, J. E.; Perlwitz, J.; Stier, P.; Takemura, T.; Zender, C.

2010-10-01

Desert dust plays an important role in the climate system through its impact on Earth's radiative budget and its role in the biogeochemical cycle as a source of iron in high-nutrient-low-chlorophyll regions. A large degree of diversity exists between the many global models that simulate the dust cycle to estimate its impact on climate. We present the results of a broad intercomparison of a total of 15 global aerosol models within the AeroCom project. Each model is compared to observations focusing on variables responsible for the uncertainties in estimating the direct radiative effect and the dust impact on the biogeochemical cycle, i.e., aerosol optical depth (AOD) and dust deposition. Additional comparisons to Angström Exponent (AE), coarse mode AOD and dust surface concentration are included to extend the assessment of model performance. These datasets form a benchmark data set which is proposed for model inspection and future dust model developments. In general, models perform better in simulating climatology of vertically averaged integrated parameters (AOD and AE) in dusty sites than they do with total deposition and surface concentration. Almost all models overestimate deposition fluxes over Europe, the Indian Ocean, the Atlantic Ocean and ice core data. Differences among the models arise when simulating deposition at remote sites with low fluxes over the Pacific and the Southern Atlantic Ocean. This study also highlights important differences in models ability to reproduce the deposition flux over Antarctica. The cause of this discrepancy could not be identified but different dust regimes at each site and issues with data quality should be considered. Models generally simulate better surface concentration at stations downwind of the main sources than at remote ones. Likewise, they simulate better surface concentration at stations affected by Saharan dust than at stations affected by Asian dust. Most models simulate the gradient in AOD and AE between the

Evolution Model and Simulation of Profit Model of Agricultural Products Logistics Financing

NASA Astrophysics Data System (ADS)

Yang, Bo; Wu, Yan

2018-03-01

Agricultural products logistics financial warehousing business mainly involves agricultural production and processing enterprises, third-party logistics enterprises and financial institutions tripartite, to enable the three parties to achieve win-win situation, the article first gives the replication dynamics and evolutionary stability strategy between the three parties in business participation, and then use NetLogo simulation platform, using the overall modeling and simulation method of Multi-Agent, established the evolutionary game simulation model, and run the model under different revenue parameters, finally, analyzed the simulation results. To achieve the agricultural products logistics financial financing warehouse business to participate in tripartite mutually beneficial win-win situation, thus promoting the smooth flow of agricultural products logistics business.

Toward a new generation of agricultural system data, models, and knowledge products: State of agricultural systems science.

PubMed

Jones, James W; Antle, John M; Basso, Bruno; Boote, Kenneth J; Conant, Richard T; Foster, Ian; Godfray, H Charles J; Herrero, Mario; Howitt, Richard E; Janssen, Sander; Keating, Brian A; Munoz-Carpena, Rafael; Porter, Cheryl H; Rosenzweig, Cynthia; Wheeler, Tim R

2017-07-01

We review the current state of agricultural systems science, focusing in particular on the capabilities and limitations of agricultural systems models. We discuss the state of models relative to five different Use Cases spanning field, farm, landscape, regional, and global spatial scales and engaging questions in past, current, and future time periods. Contributions from multiple disciplines have made major advances relevant to a wide range of agricultural system model applications at various spatial and temporal scales. Although current agricultural systems models have features that are needed for the Use Cases, we found that all of them have limitations and need to be improved. We identified common limitations across all Use Cases, namely 1) a scarcity of data for developing, evaluating, and applying agricultural system models and 2) inadequate knowledge systems that effectively communicate model results to society. We argue that these limitations are greater obstacles to progress than gaps in conceptual theory or available methods for using system models. New initiatives on open data show promise for addressing the data problem, but there also needs to be a cultural change among agricultural researchers to ensure that data for addressing the range of Use Cases are available for future model improvements and applications. We conclude that multiple platforms and multiple models are needed for model applications for different purposes. The Use Cases provide a useful framework for considering capabilities and limitations of existing models and data.

Toward a New Generation of Agricultural System Data, Models, and Knowledge Products: State of Agricultural Systems Science

NASA Technical Reports Server (NTRS)

Jones, James W.; Antle, John M.; Basso, Bruno; Boote, Kenneth J.; Conant, Richard T.; Foster, Ian; Godfray, H. Charles J.; Herrero, Mario; Howitt, Richard E.; Janssen, Sander;

Toward a new generation of agricultural system data, models, and knowledge products: State of agricultural systems science

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jones, James W.; Antle, John M.; Basso, Bruno

We review the current state of agricultural systems science, focusing in particular on the capabilities and limitations of agricultural systems models. We discuss the state of models relative to five different Use Cases spanning field, farm, landscape, regional, and global spatial scales and engaging questions in past, current, and future time periods. Contributions from multiple disciplines have made major advances relevant to a wide range of agricultural system model applications at various spatial and temporal scales. Although current agricultural systems models have features that are needed for the Use Cases, we found that all of them have limitations and needmore » to be improved. We identified common limitations across all Use Cases, namely 1) a scarcity of data for developing, evaluating, and applying agricultural system models and 2) inadequate knowledge systems that effectively communicate model results to society. We argue that these limitations are greater obstacles to progress than gaps in conceptual theory or available methods for using system models. New initiatives on open data show promise for addressing the data problem, but there also needs to be a cultural change among agricultural researchers to ensure that data for addressing the range of Use Cases are available for future model improvements and applications. We conclude that multiple platforms and multiple models are needed for model applications for different purposes. The Use Cases provide a useful framework for considering capabilities and limitations of existing models and data.« less

The Radiative Forcing Model Intercomparison Project (RFMIP): Experimental protocol for CMIP6

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pincus, Robert; Forster, Piers M.; Stevens, Bjorn

The phrasing of the first of three questions motivating CMIP6 – “How does the Earth system respond to forcing?” – suggests that forcing is always well-known, yet the radiative forcing to which this question refers has historically been uncertain in coordinated experiments even as understanding of how best to infer radiative forcing has evolved. The Radiative Forcing Model Intercomparison Project (RFMIP) endorsed by CMIP6 seeks to provide a foundation for answering the question through three related activities: (i) accurate characterization of the effective radiative forcing relative to a near-preindustrial baseline and careful diagnosis of the components of this forcing; (ii) assessment ofmore » the absolute accuracy of clear-sky radiative transfer parameterizations against reference models on the global scales relevant for climate modeling; and (iii) identification of robust model responses to tightly specified aerosol radiative forcing from 1850 to present. Complete characterization of effective radiative forcing can be accomplished with 180 years (Tier 1) of atmosphere-only simulation using a sea-surface temperature and sea ice concentration climatology derived from the host model's preindustrial control simulation. Assessment of parameterization error requires trivial amounts of computation but the development of small amounts of infrastructure: new, spectrally detailed diagnostic output requested as two snapshots at present-day and preindustrial conditions, and results from the model's radiation code applied to specified atmospheric conditions. In conclusion, the search for robust responses to aerosol changes relies on the CMIP6 specification of anthropogenic aerosol properties; models using this specification can contribute to RFMIP with no additional simulation, while those using a full aerosol model are requested to perform at least one and up to four 165-year coupled ocean–atmosphere simulations at Tier 1.« less

The Radiative Forcing Model Intercomparison Project (RFMIP): Experimental protocol for CMIP6

DOE PAGES

Pincus, Robert; Forster, Piers M.; Stevens, Bjorn

2016-09-27

The phrasing of the first of three questions motivating CMIP6 – “How does the Earth system respond to forcing?” – suggests that forcing is always well-known, yet the radiative forcing to which this question refers has historically been uncertain in coordinated experiments even as understanding of how best to infer radiative forcing has evolved. The Radiative Forcing Model Intercomparison Project (RFMIP) endorsed by CMIP6 seeks to provide a foundation for answering the question through three related activities: (i) accurate characterization of the effective radiative forcing relative to a near-preindustrial baseline and careful diagnosis of the components of this forcing; (ii) assessment ofmore » the absolute accuracy of clear-sky radiative transfer parameterizations against reference models on the global scales relevant for climate modeling; and (iii) identification of robust model responses to tightly specified aerosol radiative forcing from 1850 to present. Complete characterization of effective radiative forcing can be accomplished with 180 years (Tier 1) of atmosphere-only simulation using a sea-surface temperature and sea ice concentration climatology derived from the host model's preindustrial control simulation. Assessment of parameterization error requires trivial amounts of computation but the development of small amounts of infrastructure: new, spectrally detailed diagnostic output requested as two snapshots at present-day and preindustrial conditions, and results from the model's radiation code applied to specified atmospheric conditions. In conclusion, the search for robust responses to aerosol changes relies on the CMIP6 specification of anthropogenic aerosol properties; models using this specification can contribute to RFMIP with no additional simulation, while those using a full aerosol model are requested to perform at least one and up to four 165-year coupled ocean–atmosphere simulations at Tier 1.« less

Intercomparison of Multiscale Modeling Approaches in Simulating Subsurface Flow and Transport

NASA Astrophysics Data System (ADS)

Yang, X.; Mehmani, Y.; Barajas-Solano, D. A.; Song, H. S.; Balhoff, M.; Tartakovsky, A. M.; Scheibe, T. D.

2016-12-01

Hybrid multiscale simulations that couple models across scales are critical to advance predictions of the larger system behavior using understanding of fundamental processes. In the current study, three hybrid multiscale methods are intercompared: multiscale loose-coupling method, multiscale finite volume (MsFV) method and multiscale mortar method. The loose-coupling method enables a parallel workflow structure based on the Swift scripting environment that manages the complex process of executing coupled micro- and macro-scale models without being intrusive to the at-scale simulators. The MsFV method applies microscale and macroscale models over overlapping subdomains of the modeling domain and enforces continuity of concentration and transport fluxes between models via restriction and prolongation operators. The mortar method is a non-overlapping domain decomposition approach capable of coupling all permutations of pore- and continuum-scale models with each other. In doing so, Lagrange multipliers are used at interfaces shared between the subdomains so as to establish continuity of species/fluid mass flux. Subdomain computations can be performed either concurrently or non-concurrently depending on the algorithm used. All the above methods have been proven to be accurate and efficient in studying flow and transport in porous media. However, there has not been any field-scale applications and benchmarking among various hybrid multiscale approaches. To address this challenge, we apply all three hybrid multiscale methods to simulate water flow and transport in a conceptualized 2D modeling domain of the hyporheic zone, where strong interactions between groundwater and surface water exist across multiple scales. In all three multiscale methods, fine-scale simulations are applied to a thin layer of riverbed alluvial sediments while the macroscopic simulations are used for the larger subsurface aquifer domain. Different numerical coupling methods are then applied between

The fourth radiation transfer model intercomparison (RAMI-IV): Proficiency testing of canopy reflectance models with ISO-13528

NASA Astrophysics Data System (ADS)

Widlowski, J.-L.; Pinty, B.; Lopatka, M.; Atzberger, C.; Buzica, D.; Chelle, M.; Disney, M.; Gastellu-Etchegorry, J.-P.; Gerboles, M.; Gobron, N.; Grau, E.; Huang, H.; Kallel, A.; Kobayashi, H.; Lewis, P. E.; Qin, W.; Schlerf, M.; Stuckens, J.; Xie, D.

2013-07-01

The radiation transfer model intercomparison (RAMI) activity aims at assessing the reliability of physics-based radiative transfer (RT) models under controlled experimental conditions. RAMI focuses on computer simulation models that mimic the interactions of radiation with plant canopies. These models are increasingly used in the development of satellite retrieval algorithms for terrestrial essential climate variables (ECVs). Rather than applying ad hoc performance metrics, RAMI-IV makes use of existing ISO standards to enhance the rigor of its protocols evaluating the quality of RT models. ISO-13528 was developed "to determine the performance of individual laboratories for specific tests or measurements." More specifically, it aims to guarantee that measurement results fall within specified tolerance criteria from a known reference. Of particular interest to RAMI is that ISO-13528 provides guidelines for comparisons where the true value of the target quantity is unknown. In those cases, "truth" must be replaced by a reliable "conventional reference value" to enable absolute performance tests. This contribution will show, for the first time, how the ISO-13528 standard developed by the chemical and physical measurement communities can be applied to proficiency testing of computer simulation models. Step by step, the pre-screening of data, the identification of reference solutions, and the choice of proficiency statistics will be discussed and illustrated with simulation results from the RAMI-IV "abstract canopy" scenarios. Detailed performance statistics of the participating RT models will be provided and the role of the accuracy of the reference solutions as well as the choice of the tolerance criteria will be highlighted.

The Continuous Intercomparison of Radiation Codes (CIRC): Phase I Cases

NASA Technical Reports Server (NTRS)

Oreopoulos, Lazaros; Mlawer, Eli; Delamere, Jennifer; Shippert, Timothy; Turner, David D.; Miller, Mark A.; Minnis, Patrick; Clough, Shepard; Barker, Howard; Ellingson, Robert

2007-01-01

CIRC aspires to be the successor to ICRCCM (Intercomparison of Radiation Codes in Climate Models). It is envisioned as an evolving and regularly updated reference source for GCM-type radiative transfer (RT) code evaluation with the principle goal to contribute in the improvement of RT parameterizations. CIRC is jointly endorsed by DOE's Atmospheric Radiation Measurement (ARM) program and the GEWEX Radiation Panel (GRP). CIRC's goal is to provide test cases for which GCM RT algorithms should be performing at their best, i.e, well characterized clear-sky and homogeneous, overcast cloudy cases. What distinguishes CIRC from previous intercomparisons is that its pool of cases is based on observed datasets. The bulk of atmospheric and surface input as well as radiative fluxes come from ARM observations as documented in the Broadband Heating Rate Profile (BBHRP) product. BBHRP also provides reference calculations from AER's RRTM RT algorithms that can be used to select the most optimal set of cases and to provide a first-order estimate of our ability to achieve radiative flux closure given the limitations in our knowledge of the atmospheric state.

Atmospheric Correction Inter-comparison Exercise (ACIX)

NASA Astrophysics Data System (ADS)

Vermote, E.; Doxani, G.; Gascon, F.; Roger, J. C.; Skakun, S.

2017-12-01

The free and open data access policy to Landsat-8 (L-8) and Sentinel-2 (S-2) satellite imagery has encouraged the development of atmospheric correction (AC) approaches for generating Bottom-of-Atmosphere (BOA) products. Several entities have started to generate (or plan to generate in the short term) BOA reflectance products at global scale for L-8 and S-2 missions. To this end, the European Space Agency (ESA) and National Aeronautics and Space Administration (NASA) have initiated an exercise on the inter-comparison of the available AC processors. The results of the exercise are expected to point out the strengths and weaknesses, as well as communalities and discrepancies of various AC processors, in order to suggest and define ways for their further improvement. In particular, 11 atmospheric processors from five different countries participate in ACIX with the aim to inter-compare their performance when applied to L-8 and S-2 data. All the processors should be operational without requiring parametrization when applied on different areas. A protocol describing in details the inter-comparison metrics and the test dataset based on the AERONET sites has been agreed unanimously during the 1st ACIX workshop in June 2016. In particular, a basic and an advanced run of each of the processor were requested in the frame of ACIX, with the aim to draw robust and reliable conclusions on the processors' performance. The protocol also describes the comparison metrics of the aerosol optical thickness and water vapour products of the processors with the corresponding AERONET measurements. Moreover, concerning the surface reflectances, the inter-comparison among the processors is defined, as well as the comparison with the MODIS surface reflectance and with a reference surface reflectance product. Such a reference product will be obtained using the AERONET characterization of the aerosol (size distribution and refractive indices) and an accurate radiative transfer code. The inter-comparison

Inter-comparison of automatic rain gauges

NASA Technical Reports Server (NTRS)

Nystuen, Jeffrey A.

1994-01-01

The Ocean Acoustics Division (OAD) of the Atlantic Oceanographic and Meteorological Laboratory (AOML), in cooperation with NOAA/NESDIS and NASA, has deployed six rain gauges for calibration and intercomparison purposes. These instruments include: (1) a weighing rain gauge, (2) a RM Young Model 50202 capacitance rain gauge, (3) a ScTI ORG-705 (long path) optical rain gauge, (4) a ScTI ORG-105 (mini-ORG) optical rain gauge, (5) a Belfort Model 382 tipping bucket rain gauge, and (6) a Distromet RD-69 disdrometer. The system has been running continuously since July 1993. During this time period, roughly 150 events with maximum rainfall rate over 10 mm/hr and 25 events with maximum rainfall rates over 100 mm/hr have been recorded. All rain gauge types have performed well, with intercorrelations 0.9 or higher. However, limitations for each type of rain gauge have been observed.

The Soil Model Development and Intercomparison Panel (SoilMIP) of the International Soil Modeling Consortium (ISMC)

NASA Astrophysics Data System (ADS)

Vanderborght, Jan; Priesack, Eckart

2017-04-01

The Soil Model Development and Intercomparison Panel (SoilMIP) is an initiative of the International Soil Modeling Consortium. Its mission is to foster the further development of soil models that can predict soil functions and their changes (i) due to soil use and land management and (ii) due to external impacts of climate change and pollution. Since soil functions and soil threats are diverse but linked with each other, the overall aim is to develop holistic models that represent the key functions of the soil system and the links between them. These models should be scaled up and integrated in terrestrial system models that describe the feedbacks between processes in the soil and the other terrestrial compartments. We propose and illustrate a few steps that could be taken to achieve these goals. A first step is the development of scenarios that compare simulations by models that predict the same or different soil services. Scenarios can be considered at three different levels of comparisons: scenarios that compare the numerics (accuracy but also speed) of models, scenarios that compare the effect of differences in process descriptions, and scenarios that compare simulations with experimental data. A second step involves the derivation of metrics or summary statistics that effectively compare model simulations and disentangle parameterization from model concept differences. These metrics can be used to evaluate how more complex model simulations can be represented by simpler models using an appropriate parameterization. A third step relates to the parameterization of models. Application of simulation models implies that appropriate model parameters have to be defined for a range of environmental conditions and locations. Spatial modelling approaches are used to derive parameter distributions. Considering that soils and their properties emerge from the interaction between physical, chemical and biological processes, the combination of spatial models with process

Consistency of climate change projections from multiple global and regional model intercomparison projects

NASA Astrophysics Data System (ADS)

Fernández, J.; Frías, M. D.; Cabos, W. D.; Cofiño, A. S.; Domínguez, M.; Fita, L.; Gaertner, M. A.; García-Díez, M.; Gutiérrez, J. M.; Jiménez-Guerrero, P.; Liguori, G.; Montávez, J. P.; Romera, R.; Sánchez, E.

2018-03-01

We present an unprecedented ensemble of 196 future climate projections arising from different global and regional model intercomparison projects (MIPs): CMIP3, CMIP5, ENSEMBLES, ESCENA, EURO- and Med-CORDEX. This multi-MIP ensemble includes all regional climate model (RCM) projections publicly available to date, along with their driving global climate models (GCMs). We illustrate consistent and conflicting messages using continental Spain and the Balearic Islands as target region. The study considers near future (2021-2050) changes and their dependence on several uncertainty sources sampled in the multi-MIP ensemble: GCM, future scenario, internal variability, RCM, and spatial resolution. This initial work focuses on mean seasonal precipitation and temperature changes. The results show that the potential GCM-RCM combinations have been explored very unevenly, with favoured GCMs and large ensembles of a few RCMs that do not respond to any ensemble design. Therefore, the grand-ensemble is weighted towards a few models. The selection of a balanced, credible sub-ensemble is challenged in this study by illustrating several conflicting responses between the RCM and its driving GCM and among different RCMs. Sub-ensembles from different initiatives are dominated by different uncertainty sources, being the driving GCM the main contributor to uncertainty in the grand-ensemble. For this analysis of the near future changes, the emission scenario does not lead to a strong uncertainty. Despite the extra computational effort, for mean seasonal changes, the increase in resolution does not lead to important changes.

Merging remote sensing data and national agricultural statistics to model change in irrigated agriculture

USGS Publications Warehouse

Brown, Jesslyn; Pervez, Md Shahriar

2014-01-01

Over 22 million hectares (ha) of U.S. croplands are irrigated. Irrigation is an intensified agricultural land use that increases crop yields and the practice affects water and energy cycles at, above, and below the land surface. Until recently, there has been a scarcity of geospatially detailed information about irrigation that is comprehensive, consistent, and timely to support studies tying agricultural land use change to aquifer water use and other factors. This study shows evidence for a recent overall net expansion of 522 thousand ha across the U.S. (2.33%) and 519 thousand ha (8.7%) in irrigated cropped area across the High Plains Aquifer (HPA) from 2002 to 2007. In fact, over 97% of the net national expansion in irrigated agriculture overlays the HPA. We employed a modeling approach implemented at two time intervals (2002 and 2007) for mapping irrigated agriculture across the conterminous U.S. (CONUS). We utilized U.S. Department of Agriculture (USDA) county statistics, satellite imagery, and a national land cover map in the model. The model output, called the Moderate Resolution Imaging Spectroradiometer (MODIS) Irrigated Agriculture Dataset for the U.S. (MIrAD-US), was then used to reveal relatively detailed spatial patterns of irrigation change across the nation and the HPA. Causes for the irrigation increase in the HPA are complex, but factors include crop commodity price increases, the corn ethanol industry, and government policies related to water use. Impacts of more irrigation may include shifts in local and regional climate, further groundwater depletion, and increasing crop yields and farm income.

Perspectives on Climate Effects on Agriculture: The International Efforts of AgMIP in Sub-Saharan Africa

NASA Technical Reports Server (NTRS)

Kihara, Job; MacCarthy, Dilys S.; Bationo, Andre; Koala, Saidou; Hickman, Jonathon; Koo, Jawoo; Vanya, Charles; Adiku, Samuel; Beletse, Yacob; Masikate, Patricia;

Impacts of Stratospheric Sulfate Geoengineering on Chinese Agricultural Production

NASA Astrophysics Data System (ADS)

Xia, L.; Robock, A.

2012-12-01

Possible food supply change is one of the most important concerns in the discussion of stratospheric sulfate geoengineering. In China, the high population density and strong summer monsoon influence on agriculture make this region sensitive to climate changes, such as reductions of precipitation, temperature, and solar radiation spurred by stratospheric sulfate injection. We used results from the Geoengineering Model Intercomparison Project G2 scenario to force the Decision Support System for Agrotechnology Transfer (DSSAT) crop model to predict crop yield changes from rice, maize, and winter wheat. We first evaluated the DSSAT model by forcing it with daily observed weather data and management practices for the period 1978-2008 for all the provinces in China, and compared the results to observations of the yields of the three major crops in China. We then created two 50-year sets of climate anomalies using the results from eight climate models, for 1%/year increase of CO2 and for G2 (1%/year increase of CO2 balanced by insolation reduction), and compared the resulting agricultural responses. Considering that geoengineering could happen in the future, we used two geoengineering starting years, 2020 and 2060. For 2020, we increased the mean temperature by 1°C and started the CO2 concentration at 410 ppm. For 2060, we increased temperature by 2°C and started the CO2 concentration at 550 ppm. Without changing agriculture technology, we find that compared to the control run, geoengineering with the G2 scenario starting in 2020 or 2060 would both moderately increase rice and winter wheat production due to the CO2 fertilization effect, but the increasing rates are different. However, as a C4 crop, without a significant CO2 fertilization effect, maize production would decrease slightly because of regional drought. Compared to the reference run, the three crops all have less heat stress in southern China and their yields increase, but in northern China cooler

A model inter-comparison study to examine limiting factors in modelling Australian tropical savannas

NASA Astrophysics Data System (ADS)

Whitley, Rhys; Beringer, Jason; Hutley, Lindsay B.; Abramowitz, Gab; De Kauwe, Martin G.; Duursma, Remko; Evans, Bradley; Haverd, Vanessa; Li, Longhui; Ryu, Youngryel; Smith, Benjamin; Wang, Ying-Ping; Williams, Mathew; Yu, Qiang

2016-06-01

The savanna ecosystem is one of the most dominant and complex terrestrial biomes, deriving from a distinct vegetative surface comprised of co-dominant tree and grass populations. While these two vegetation types co-exist functionally, demographically they are not static but are dynamically changing in response to environmental forces such as annual fire events and rainfall variability. Modelling savanna environments with the current generation of terrestrial biosphere models (TBMs) has presented many problems, particularly describing fire frequency and intensity, phenology, leaf biochemistry of C3 and C4 photosynthesis vegetation, and root-water uptake. In order to better understand why TBMs perform so poorly in savannas, we conducted a model inter-comparison of six TBMs and assessed their performance at simulating latent energy (LE) and gross primary productivity (GPP) for five savanna sites along a rainfall gradient in northern Australia. Performance in predicting LE and GPP was measured using an empirical benchmarking system, which ranks models by their ability to utilise meteorological driving information to predict the fluxes. On average, the TBMs performed as well as a multi-linear regression of the fluxes against solar radiation, temperature and vapour pressure deficit but were outperformed by a more complicated nonlinear response model that also included the leaf area index (LAI). This identified that the TBMs are not fully utilising their input information effectively in determining savanna LE and GPP and highlights that savanna dynamics cannot be calibrated into models and that there are problems in underlying model processes. We identified key weaknesses in a model's ability to simulate savanna fluxes and their seasonal variation, related to the representation of vegetation by the models and root-water uptake. We underline these weaknesses in terms of three critical areas for development. First, prescribed tree-rooting depths must be deep enough

The AgMIP Wheat Pilot: A multi-model approach for climate change impact assessments.

NASA Astrophysics Data System (ADS)

Asseng, S.

2012-12-01

Asseng S., F. Ewert, C. Rosenzweig, J.W. Jones, J.L. Hatfield, A. Ruane, K.J. Boote, P. Thorburn, R.P. Rötter, D. Cammarano, N. Brisson, B. Basso, P. Martre, D. Ripoche, P. Bertuzzi, P. Steduto, L. Heng, M.A. Semenov, P. Stratonovitch, C. Stockle, G. O'Leary, P.K. Aggarwal, S. Naresh Kumar, C. Izaurralde, J.W. White, L.A. Hunt, R. Grant, K.C. Kersebaum, T. Palosuo, J. Hooker, T. Osborne, J. Wolf, I. Supit, J.E. Olesen, J. Doltra, C. Nendel, S. Gayler, J. Ingwersen, E. Priesack, T. Streck, F. Tao, C. Müller, K. Waha, R. Goldberg, C. Angulo, I. Shcherbak, C. Biernath, D. Wallach, M. Travasso, A. Challinor. Abstract: Crop simulation models have been used to assess the impact of climate change on agriculture. These assessments are often carried out with a single model in a limited number of environments and without determining the uncertainty of simulated impacts. There is a need for a coordinated effort bringing together multiple modeling teams which has been recognized by the Agricultural Model Intercomparison and Improvement Project (AgMIP; www.agmip.org). AgMIP aims to provide more robust estimates of climate impacts on crop yields and agricultural trade, including estimates of associated uncertainties. Here, we present the AgMIP Wheat Pilot Study, the most comprehensive model intercomparison of the response of wheat crops to climate change to date, including 27 wheat models. Crop model uncertainties in assessing climate change impacts are explored and compared with field experimental and Global Circulation Model uncertainties. Causes of impact uncertainties and ways to reduce these are discussed.

Invited Article: Radon and thoron intercomparison experiments for integrated monitors at NIRS, Japan

DOE Office of Scientific and Technical Information (OSTI.GOV)

Janik, M., E-mail: mirek@fml.nirs.go.jp; Ishikawa, T.; Omori, Y.

Inhalation of radon ({sup 222}Rn) and its short-lived decay products and of products of the thoron ({sup 220}Rn) series accounts for more than half of the effective dose from natural radiation sources. At this time, many countries have begun large-scale radon and thoron surveys and many different measurement methods and instruments are used in these studies. Consequently, it is necessary to improve and standardize technical methods of measurements and to verify quality assurance by intercomparisons between laboratories. Four international intercomparisons for passive integrating radon and thoron monitors were conducted at the NIRS (National Institute of Radiological Sciences, Japan). Radon exercisesmore » were carried out in the 24.4 m{sup 3} inner volume walk-in radon chamber that has systems to control radon concentration, temperature, and humidity. Moreover, the NIRS thoron chamber with a 150 dm{sup 3} inner volume was utilized to provide three thoron intercomparisons. At present, the NIRS is the only laboratory world-wide that has carried out periodic thoron intercomparison of passive monitors. Fifty laboratories from 26 countries participated in the radon intercomparison, using six types of detectors (charcoal, CR-39, LR 115, polycarbonate film, electret plate, and silicon photodiode). Eighteen laboratories from 12 countries participated in the thoron intercomparisons, using two etch-track types (CR-39 and polycarbonate) detectors. The tests were made under one to three different exposures to radon and thoron. The data presented in this paper indicated that the performance quality of laboratories for radon measurement has been gradually increasing. Results of thoron exercises showed that the quality for thoron measurements still needs further development and additional studies are needed to improve its measuring methods. The present paper provides a summary of all radon and thoron international intercomparisons done at NIRS from 2007 to date and it describes

iMarNet: an ocean biogeochemistry model inter-comparison project within a common physical ocean modelling framework

NASA Astrophysics Data System (ADS)

Kwiatkowski, L.; Yool, A.; Allen, J. I.; Anderson, T. R.; Barciela, R.; Buitenhuis, E. T.; Butenschön, M.; Enright, C.; Halloran, P. R.; Le Quéré, C.; de Mora, L.; Racault, M.-F.; Sinha, B.; Totterdell, I. J.; Cox, P. M.

2014-07-01

Ocean biogeochemistry (OBGC) models span a wide range of complexities from highly simplified, nutrient-restoring schemes, through nutrient-phytoplankton-zooplankton-detritus (NPZD) models that crudely represent the marine biota, through to models that represent a broader trophic structure by grouping organisms as plankton functional types (PFT) based on their biogeochemical role (Dynamic Green Ocean Models; DGOM) and ecosystem models which group organisms by ecological function and trait. OBGC models are now integral components of Earth System Models (ESMs), but they compete for computing resources with higher resolution dynamical setups and with other components such as atmospheric chemistry and terrestrial vegetation schemes. As such, the choice of OBGC in ESMs needs to balance model complexity and realism alongside relative computing cost. Here, we present an inter-comparison of six OBGC models that were candidates for implementation within the next UK Earth System Model (UKESM1). The models cover a large range of biological complexity (from 7 to 57 tracers) but all include representations of at least the nitrogen, carbon, alkalinity and oxygen cycles. Each OBGC model was coupled to the Nucleus for the European Modelling of the Ocean (NEMO) ocean general circulation model (GCM), and results from physically identical hindcast simulations were compared. Model skill was evaluated for biogeochemical metrics of global-scale bulk properties using conventional statistical techniques. The computing cost of each model was also measured in standardised tests run at two resource levels. No model is shown to consistently outperform or underperform all other models across all metrics. Nonetheless, the simpler models that are easier to tune are broadly closer to observations across a number of fields, and thus offer a high-efficiency option for ESMs that prioritise high resolution climate dynamics. However, simpler models provide limited insight into more complex marine

International NMR-based Environmental Metabolomics Intercomparison Exercise

EPA Science Inventory

Several fundamental requirements must be met so that NMR-based metabolomics and the related technique of metabonomics can be formally adopted into environmental monitoring and chemical risk assessment. Here we report an intercomparison exercise which has evaluated the effectivene...

Inter-comparison of network measurements of non-methane organic compounds with model simulations

NASA Astrophysics Data System (ADS)

Chen, Sheng-Po; Su, Yuan-Chang; Chiu, Ching-Jui; Lin, Ching-Ho; Chang, Julius S.; Chang, Chih-Chung; Wang, Jia-Lin

2015-12-01

Ambient levels of total non-methane organic carbons (NMOCs) at air quality stations (AQSs, called AQS NMOCs) are compared with the summed concentrations of 56 NMHCs obtained from the Photochemical Assessment Monitoring Stations (called total PAMS). For mutual validation of the two networks, the total PAMS were compared with the AQS NMOCs at four sites on the island of Taiwan for the period 2007-2012. The inter-comparison of total PAMS and AQS NMOCs has been discussed previously, which reported that the total PAMS accounted for approximately 30% of the AQS NMOCs on average (Chen et al., 2014b). In this study, both the observed total PAMS and AQS NMOCs were further compared with the emissions and model simulations for mutual validation. A three-dimensional Eulerian air quality model was used to simulate total PAMS and total VOCs, which were then inter-compared with the observed total PAMS and AQS NMOCs, respectively. We found closely agreeing results between the observed and simulated total PAMS, affirming that the treatment of meteorology and VOC emissions in the model was sufficiently robust. Further, although the modeled VOC data agreed with the AQS NMOC observations for the sites in urban settings, a significant discrepancy existed for the industrial sites, particularly at the concentration spikes. Such a discrepancy was presumably attributed to high emissions of OVOCs from industrial complexes compounded by the lower sensitivity of AQS measurements for OVOCs compared with hydrocarbons. Consequently, using AQS NMOCs to represent ambient VOC levels should be limited to environments where the amounts of OVOCs are relatively small relative to total VOCs.

Modelling Mediterranean agro-ecosystems by including agricultural trees in the LPJmL model

NASA Astrophysics Data System (ADS)

Fader, M.; von Bloh, W.; Shi, S.; Bondeau, A.; Cramer, W.

2015-06-01

Climate and land use change in the Mediterranean region is expected to affect natural and agricultural ecosystems by decreases in precipitation, increases in temperature as well as biodiversity loss and anthropogenic degradation of natural resources. Demographic growth in the Eastern and Southern shores will require increases in food production and put additional pressure on agro-ecosystems and water resources. Coping with these challenges requires informed decisions that, in turn, require assessments by means of a comprehensive agro-ecosystem and hydrological model. This study presents the inclusion of 10 Mediterranean agricultural plants, mainly perennial crops, in an agro-ecosystem model (LPJmL): nut trees, date palms, citrus trees, orchards, olive trees, grapes, cotton, potatoes, vegetables and fodder grasses. The model was successfully tested in three model outputs: agricultural yields, irrigation requirements and soil carbon density. With the development presented in this study, LPJmL is now able to simulate in good detail and mechanistically the functioning of Mediterranean agriculture with a comprehensive representation of ecophysiological processes for all vegetation types (natural and agricultural) and in a consistent framework that produces estimates of carbon, agricultural and hydrological variables for the entire Mediterranean basin. This development pave the way for further model extensions aiming at the representation of alternative agro-ecosystems (e.g. agroforestry), and opens the door for a large number of applications in the Mediterranean region, for example assessments on the consequences of land use transitions, the influence of management practices and climate change impacts.

PNNL Results from 2010 CALIBAN Criticality Accident Dosimeter Intercomparison Exercise

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hill, Robin L.; Conrady, Matthew M.

2011-10-28

This document reports the results of the Hanford personnel nuclear accident dosimeter (PNAD) and fixed nuclear accident dosimeter (FNAD) during a criticality accident dosimeter intercomparison exercise at the CEA Valduc Center on September 20-23, 2010. Pacific Northwest National Laboratory (PNNL) participated in a criticality accident dosimeter intercomparison exercise at the Commissariat a Energie Atomique (CEA) Valduc Center near Dijon, France on September 20-23, 2010. The intercomparison exercise was funded by the U.S. Department of Energy, Nuclear Criticality Safety Program, with Lawrence Livermore National Laboratory as the lead Laboratory. PNNL was one of six invited DOE Laboratory participants. The other participatingmore » Laboratories were: Lawrence Livermore National Laboratory (LLNL), Los Alamos National Laboratory (LANL), Savannah River Site (SRS), the Y-12 National Security Complex at Oak Ridge, and Sandia National Laboratory (SNL). The goals of PNNL's participation in the intercomparison exercise were to test and validate the procedures and algorithm currently used for the Hanford personnel nuclear accident dosimeters (PNADs) on the metallic reactor, CALIBAN, to test exposures to PNADs from the side and from behind a phantom, and to test PNADs that were taken from a historical batch of Hanford PNADs that had varying degrees of degradation of the bare indium foil. Similar testing of the PNADs was done on the Valduc SILENE test reactor in 2009 (Hill and Conrady, 2010). The CALIBAN results are reported here.« less

Evaluation of Tropospheric Water Vapor Simulations from the Atmospheric Model Intercomparison Project

NASA Technical Reports Server (NTRS)

Gaffen, Dian J.; Rosen, Richard D.; Salstein, David A.; Boyle, James S.

1997-01-01

Simulations of humidity from 28 general circulation models for the period 1979-88 from the Atmospheric Model Intercomparison Project are compared with observations from radiosondes over North America and the globe and with satellite microwave observations over the Pacific basin. The simulations of decadal mean values of precipitable water (W) integrated over each of these regions tend to be less moist than the real atmosphere in all three cases; the median model values are approximately 5% less than the observed values. The spread among the simulations is larger over regions of high terrain, which suggests that differences in methods of resolving topographic features are important. The mean elevation of the North American continent is substantially higher in the models than is observed, which may contribute to the overall dry bias of the models over that area. The authors do not find a clear association between the mean topography of a model and its mean W simulation, however, which suggests that the bias over land is not purely a matter of orography. The seasonal cycle of W is reasonably well simulated by the models, although over North America they have a tendency to become moister more quickly in the spring than is observed. The interannual component of the variability of W is not well captured by the models over North America. Globally, the simulated W values show a signal correlated with the Southern Oscillation index but the observations do not. This discrepancy may be related to deficiencies in the radiosonde network, which does not sample the tropical ocean regions well. Overall, the interannual variability of W, as well as its climatology and mean seasonal cycle, are better described by the median of the 28 simulations than by individual members of the ensemble. Tests to learn whether simulated precipitable water, evaporation, and precipitation values may be related to aspects of model formulation yield few clear signals, although the authors find, for

Radon intercomparisons at EML, January 1983 and February 1984

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fisenne, I.M.; George, A.C.; Keller, H.W.

1985-02-01

This report summarizes the results of two radon measurement intercomparison exercises held at the Environmental Measurements Laboratory (EML) in January 1983 and February 1984. Nineteen organizations, including five US federal facilities, one national laboratory, two state laboratories, six universities, three private sector laboratories and two non-US facilities participated in these exercises. The results indicate good agreement among the participants at /sup 222/Rn concentration levels of 50 and 80 pCi.L/sup -1/. Improvements in the EML calibration facilities, and the participation of two US laboratories in a Nuclear Energy Agency intercomparison program are also discussed. 8 references, 6 figures, 8 tables.

Methods for Validation and Intercomparison of Remote Sensing and In situ Ice Water Measurements: Case Studies from CRYSTAL-FACE and Model Results

NASA Technical Reports Server (NTRS)

Sayres, D.S.; Pittman, J. V.; Smith, J. B.; Weinstock, E. M.; Anderson, J. G.; Heymsfield, G.; Li, L.; Fridlind, A.; Ackerman, A. S.

2004-01-01

Remote sensing observations, such as those from AURA, are necessary to understand the role of cirrus in determining the radiative and humidity budgets of the upper troposphere. Using these measurements quantitatively requires comparisons with in situ measurements that have previously been validated. However, a direct comparison of remote and in situ measurements is difficult due to the requirement that the spatial and temporal overlap be sufficient in order to guarantee that both instruments are measuring the same air parcel. A difficult as this might be for gas phase intercomparisons, cloud inhomogeneities significantly exacerbate the problem for cloud ice water content measurements. The CRYSTAL-FACE mission provided an opportunity to assess how well such intercomparisons can be performed and to establish flight plans that will be necessary for validation of future satellite instruments. During CRYSTAL-FACE, remote and in situ instruments were placed on different aircraft (NASA's ER-2 and WB-59, and the two planes flew in tandem so that the in situ payload flew in the field of view of the remote instruments. We show here that, even with this type of careful flight planning, it is not always possible to guarantee that remote and in situ instruments are viewing the same air parcel. We use ice water data derived from the in situ Harvard Total Water (HV-TW) instrument, and the remote Goddard Cloud Radar System (CRS) and show that agreement between HV-TW and CRS is a strong function of the horizontal separation and the time delay between the aircraft transects. We also use a cloud model to simulate possible trajectories through a cloud and evaluate the use of statistical analysis in determining the agreement between the two instruments. This type of analysis should guide flight planning for future intercomparison efforts, whether for aircraft or satellite-borne instrumentation.

Stratospheric Ozone Intercomparison Campaign (STOIC) 1989: Overview

NASA Technical Reports Server (NTRS)

Margitan, J. J.; Barnes, R. A.; Brothers, G. B.; Butler, J.; Burris, J.; Connor, B. J.; Ferrare, R. A.; Kerr, J. B.; Komhyr, W. D.; McCormick, M. P.;

The Climate-Agriculture-Modeling and Decision Tool (CAMDT) for Climate Risk Management in Agriculture

NASA Astrophysics Data System (ADS)

Ines, A. V. M.; Han, E.; Baethgen, W.

2017-12-01

Advances in seasonal climate forecasts (SCFs) during the past decades have brought great potential to improve agricultural climate risk managements associated with inter-annual climate variability. In spite of popular uses of crop simulation models in addressing climate risk problems, the models cannot readily take seasonal climate predictions issued in the format of tercile probabilities of most likely rainfall categories (i.e, below-, near- and above-normal). When a skillful SCF is linked with the crop simulation models, the informative climate information can be further translated into actionable agronomic terms and thus better support strategic and tactical decisions. In other words, crop modeling connected with a given SCF allows to simulate "what-if" scenarios with different crop choices or management practices and better inform the decision makers. In this paper, we present a decision support tool, called CAMDT (Climate Agriculture Modeling and Decision Tool), which seamlessly integrates probabilistic SCFs to DSSAT-CSM-Rice model to guide decision-makers in adopting appropriate crop and agricultural water management practices for given climatic conditions. The CAMDT has a functionality to disaggregate a probabilistic SCF into daily weather realizations (either a parametric or non-parametric disaggregation method) and to run DSSAT-CSM-Rice with the disaggregated weather realizations. The convenient graphical user-interface allows easy implementation of several "what-if" scenarios for non-technical users and visualize the results of the scenario runs. In addition, the CAMDT also translates crop model outputs to economic terms once the user provides expected crop price and cost. The CAMDT is a practical tool for real-world applications, specifically for agricultural climate risk management in the Bicol region, Philippines, having a great flexibility for being adapted to other crops or regions in the world. CAMDT GitHub: https://github.com/Agro-Climate/CAMDT

Impact of Spatial Scales on the Intercomparison of Climate Scenarios

DOE Office of Scientific and Technical Information (OSTI.GOV)

Luo, Wei; Steptoe, Michael; Chang, Zheng

2017-01-01

Scenario analysis has been widely applied in climate science to understand the impact of climate change on the future human environment, but intercomparison and similarity analysis of different climate scenarios based on multiple simulation runs remain challenging. Although spatial heterogeneity plays a key role in modeling climate and human systems, little research has been performed to understand the impact of spatial variations and scales on similarity analysis of climate scenarios. To address this issue, the authors developed a geovisual analytics framework that lets users perform similarity analysis of climate scenarios from the Global Change Assessment Model (GCAM) using a hierarchicalmore » clustering approach.« less

Benchmarking carbon-nitrogen interactions in Earth System Models to observations: An inter-comparison of nitrogen limitation in global land surface models with carbon and nitrogen cycles (CLM-CN and O-CN)

NASA Astrophysics Data System (ADS)

Thomas, R. Q.; Zaehle, S.; Templer, P. H.; Goodale, C. L.

2011-12-01

Predictions of climate change depend on accurately modeling the feedbacks among the carbon cycle, nitrogen cycle, and climate system. Several global land surface models have shown that nitrogen limitation determines how land carbon fluxes respond to rising CO2, nitrogen deposition, and climate change, thereby influencing predictions of climate change. However, the magnitude of the carbon-nitrogen-climate feedbacks varies considerably by model, leading to critical and timely questions of why they differ and how they compare to field observations. To address these questions, we initiated a model inter-comparison of spatial patterns and drivers of nitrogen limitation. The experiment assessed the regional consequences of sustained nitrogen additions in a set of 25-year global nitrogen fertilization simulations. The model experiments were designed to cover effects from small changes in nitrogen inputs associated with plausible increases in nitrogen deposition to large changes associated with field-based nitrogen fertilization experiments. The analyses of model simulations included assessing the geographically varying degree of nitrogen limitation on plant and soil carbon cycling and the mechanisms underlying model differences. Here, we present results from two global land-surface models (CLM-CN and O-CN) with differing approaches to modeling carbon-nitrogen interactions. The predictions from each model were compared to a set of globally distributed observational data that includes nitrogen fertilization experiments, 15N tracer studies, small catchment nitrogen input-output studies, and syntheses across nitrogen deposition gradients. Together these datasets test many aspects of carbon-nitrogen coupling and are able to differentiate between the two models. Overall, this study is the first to explicitly benchmark carbon and nitrogen interactions in Earth System Models using a range of observations and is a foundation for future inter-comparisons.

WETCHIMP-WSL: Intercomparison of wetland methane emissions models over West Siberia

DOE PAGES

Bohn, T. J.; Melton, J. R.; Ito, A.; ...

2015-06-03

Wetlands are the world's largest natural source of methane, a powerful greenhouse gas. The strong sensitivity of methane emissions to environmental factors such as soil temperature and moisture has led to concerns about potential positive feedbacks to climate change. This risk is particularly relevant at high latitudes, which have experienced pronounced warming and where thawing permafrost could potentially liberate large amounts of labile carbon over the next 100 years. However, global models disagree as to the magnitude and spatial distribution of emissions, due to uncertainties in wetland area and emissions per unit area and a scarcity of in situ observations.more » Recent intensive field campaigns across the West Siberian Lowland (WSL) make this an ideal region over which to assess the performance of large-scale process-based wetland models in a high-latitude environment. Here we present the results of a follow-up to the Wetland and Wetland CH 4 Intercomparison of Models Project (WETCHIMP), focused on the West Siberian Lowland (WETCHIMP-WSL). We assessed 21 models and 5 inversions over this domain in terms of total CH 4 emissions, simulated wetland areas, and CH 4 fluxes per unit wetland area and compared these results to an intensive in situ CH 4 flux data set, several wetland maps, and two satellite surface water products. We found that (a) despite the large scatter of individual estimates, 12-year mean estimates of annual total emissions over the WSL from forward models (5.34 ± 0.54 Tg CH 4 yr⁻¹), inversions (6.06 ± 1.22 Tg CH 4 yr⁻¹), and in situ observations (3.91 ± 1.29 Tg CH 4 yr⁻¹) largely agreed; (b) forward models using surface water products alone to estimate wetland areas suffered from severe biases in CH 4 emissions; (c) the interannual time series of models that lacked either soil thermal physics appropriate to the high latitudes or realistic emissions from unsaturated peatlands tended to be dominated by a single environmental driver

PM 2.5 ORGANIC SPECIATION INTERCOMPARISON RESULTS

EPA Science Inventory

This abstract describes a poster on results to a laboratory intercomparison of organic aerosol speciation analysis to be presented at the 2006 International Aerosol Conference sponsored by the American Association for Aerosol Research in St. Paul, Minnesota on September 10-15. T...

Satellite Derived Volcanic Ash Product Inter-Comparison in Support to SCOPE-Nowcasting

NASA Astrophysics Data System (ADS)

Siddans, Richard; Thomas, Gareth; Pavolonis, Mike; Bojinski, Stephan

2016-04-01

In support of aeronautical meteorological services, WMO organized a satellite-based volcanic ash retrieval algorithm inter-comparison activity, to improve the consistency of quantitative volcanic ash products from satellites, under the Sustained, Coordinated Processing of Environmental Satellite Data for Nowcasting (SCOPEe Nowcasting) initiative (http:/ jwww.wmo.int/pagesjprogjsatjscopee nowcasting_en.php). The aims of the intercomparison were as follows: 1. Select cases (Sarychev Peak 2009, Eyjafyallajökull 2010, Grimsvötn 2011, Puyehue-Cordón Caulle 2011, Kirishimayama 2011, Kelut 2014), and quantify the differences between satellite-derived volcanic ash cloud properties derived from different techniques and sensors; 2. Establish a basic validation protocol for satellite-derived volcanic ash cloud properties; 3. Document the strengths and weaknesses of different remote sensing approaches as a function of satellite sensor; 4. Standardize the units and quality flags associated with volcanic cloud geophysical parameters; 5. Provide recommendations to Volcanic Ash Advisory Centers (VAACs) and other users on how to best to utilize quantitative satellite products in operations; 6. Create a "road map" for future volcanic ash related scientific developments and inter-comparison/validation activities that can also be applied to SO2 clouds and emergent volcanic clouds. Volcanic ash satellite remote sensing experts from operational and research organizations were encouraged to participate in the inter-comparison activity, to establish the plans for the inter-comparison and to submit data sets. RAL was contracted by EUMETSAT to perform a systematic inter-comparison of all submitted datasets and results were reported at the WMO International Volcanic Ash Inter-comparison Meeting to held on 29 June - 2 July 2015 in Madison, WI, USA (http:/ /cimss.ssec.wisc.edujmeetings/vol_ash14). 26 different data sets were submitted, from a range of passive imagers and spectrometers and

Modelling Mediterranean agro-ecosystems by including agricultural trees in the LPJmL model

NASA Astrophysics Data System (ADS)

Fader, M.; von Bloh, W.; Shi, S.; Bondeau, A.; Cramer, W.

2015-11-01

In the Mediterranean region, climate and land use change are expected to impact on natural and agricultural ecosystems by warming, reduced rainfall, direct degradation of ecosystems and biodiversity loss. Human population growth and socioeconomic changes, notably on the eastern and southern shores, will require increases in food production and put additional pressure on agro-ecosystems and water resources. Coping with these challenges requires informed decisions that, in turn, require assessments by means of a comprehensive agro-ecosystem and hydrological model. This study presents the inclusion of 10 Mediterranean agricultural plants, mainly perennial crops, in an agro-ecosystem model (Lund-Potsdam-Jena managed Land - LPJmL): nut trees, date palms, citrus trees, orchards, olive trees, grapes, cotton, potatoes, vegetables and fodder grasses. The model was successfully tested in three model outputs: agricultural yields, irrigation requirements and soil carbon density. With the development presented in this study, LPJmL is now able to simulate in good detail and mechanistically the functioning of Mediterranean agriculture with a comprehensive representation of ecophysiological processes for all vegetation types (natural and agricultural) and in a consistent framework that produces estimates of carbon, agricultural and hydrological variables for the entire Mediterranean basin. This development paves the way for further model extensions aiming at the representation of alternative agro-ecosystems (e.g. agroforestry), and opens the door for a large number of applications in the Mediterranean region, for example assessments of the consequences of land use transitions, the influence of management practices and climate change impacts.

Agricultural Model for the Nile Basin Decision Support System

NASA Astrophysics Data System (ADS)

van der Bolt, Frank; Seid, Abdulkarim

2014-05-01

To analyze options for increasing food supply in the Nile basin the Nile Agricultural Model (AM) was developed. The AM includes state-of-the-art descriptions of biophysical, hydrological and economic processes and realizes a coherent and consistent integration of hydrology, agronomy and economics. The AM covers both the agro-ecological domain (water, crop productivity) and the economic domain (food supply, demand, and trade) and allows to evaluate the macro-economic and hydrological impacts of scenarios for agricultural development. Starting with the hydrological information from the NileBasin-DSS the AM calculates the available water for agriculture, the crop production and irrigation requirements with the FAO-model AquaCrop. With the global commodity trade model MAGNET scenarios for land development and conversion are evaluated. The AM predicts consequences for trade, food security and development based on soil and water availability, crop allocation, food demand and food policy. The model will be used as a decision support tool to contribute to more productive and sustainable agriculture in individual Nile countries and the whole region.

The AgMIP Coordinated Climate-Crop Modeling Project (C3MP): Methods and Protocols

NASA Technical Reports Server (NTRS)

Shukla, Sonali P.; Ruane, Alexander Clark

2014-01-01

Climate change is expected to alter a multitude of factors important to agricultural systems, including pests, diseases, weeds, extreme climate events, water resources, soil degradation, and socio-economic pressures. Changes to carbon dioxide concentration ([CO2]), temperature, and water (CTW) will be the primary drivers of change in crop growth and agricultural systems. Therefore, establishing the CTW-change sensitivity of crop yields is an urgent research need and warrants diverse methods of investigation. Crop models provide a biophysical, process-based tool to investigate crop responses across varying environmental conditions and farm management techniques, and have been applied in climate impact assessment by using a variety of methods (White et al., 2011, and references therein). However, there is a significant amount of divergence between various crop models' responses to CTW changes (Rotter et al., 2011). While the application of a site-based crop model is relatively simple, the coordination of such agricultural impact assessments on larger scales requires consistent and timely contributions from a large number of crop modelers, each time a new global climate model (GCM) scenario or downscaling technique is created. A coordinated, global effort to rapidly examine CTW sensitivity across multiple crops, crop models, and sites is needed to aid model development and enhance the assessment of climate impacts (Deser et al., 2012). To fulfill this need, the Coordinated Climate-Crop Modeling Project (C3MP) (Ruane et al., 2014) was initiated within the Agricultural Model Intercomparison and Improvement Project (AgMIP; Rosenzweig et al., 2013). The submitted results from C3MP Phase 1 (February 15, 2013-December 31, 2013) are currently being analyzed. This chapter serves to present and update the C3MP protocols, discuss the initial participation and general findings, comment on needed adjustments, and describe continued and future development. AgMIP aims to improve

Nuclear accident dosimetry intercomparison studies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sims, C.S.

1989-09-01

Twenty-two nuclear accident dosimetry intercomparison studies utilizing the fast-pulse Health Physics Research Reactor at the Oak Ridge National Laboratory have been conducted since 1965. These studies have provided a total of 62 different organizations a forum for discussion of criticality accident dosimetry, an opportunity to test their neutron and gamma-ray dosimetry systems under a variety of simulated criticality accident conditions, and the experience of comparing results with reference dose values as well as with the measured results obtained by others making measurements under identical conditions. Sixty-nine nuclear accidents (27 with unmoderated neutron energy spectra and 42 with eight different shieldedmore » spectra) have been simulated in the studies. Neutron doses were in the 0.2-8.5 Gy range and gamma doses in the 0.1-2.0 Gy range. A total of 2,289 dose measurements (1,311 neutron, 978 gamma) were made during the intercomparisons. The primary methods of neutron dosimetry were activation foils, thermoluminescent dosimeters, and blood sodium activation. The main methods of gamma dose measurement were thermoluminescent dosimeters, radiophotoluminescent glass, and film. About 68% of the neutron measurements met the accuracy guidelines (+/- 25%) and about 52% of the gamma measurements met the accuracy criterion (+/- 20%) for accident dosimetry.« less

Climate Change Impacts on Agriculture and Food Security in 2050 under a Range of Plausible Socioeconomic and Emissions Scenarios

NASA Astrophysics Data System (ADS)

Wiebe, K.; Lotze-Campen, H.; Bodirsky, B.; Kavallari, A.; Mason-d'Croz, D.; van der Mensbrugghe, D.; Robinson, S.; Sands, R.; Tabeau, A.; Willenbockel, D.; Islam, S.; van Meijl, H.; Mueller, C.; Robertson, R.

2014-12-01

Previous studies have combined climate, crop and economic models to examine the impact of climate change on agricultural production and food security, but results have varied widely due to differences in models, scenarios and data. Recent work has examined (and narrowed) these differences through systematic model intercomparison using a high-emissions pathway to highlight the differences. New work extends that analysis to cover a range of plausible socioeconomic scenarios and emission pathways. Results from three general circulation models are combined with one crop model and five global economic models to examine the global and regional impacts of climate change on yields, area, production, prices and trade for coarse grains, rice, wheat, oilseeds and sugar to 2050. Results show that yield impacts vary with changes in population, income and technology as well as emissions, but are reduced in all cases by endogenous changes in prices and other variables.

Representing agriculture in Earth System Models: Approaches and priorities for development

NASA Astrophysics Data System (ADS)

McDermid, S. S.; Mearns, L. O.; Ruane, A. C.

2017-09-01

Earth System Model (ESM) advances now enable improved representations of spatially and temporally varying anthropogenic climate forcings. One critical forcing is global agriculture, which is now extensive in land-use and intensive in management, owing to 20th century development trends. Agriculture and food systems now contribute nearly 30% of global greenhouse gas emissions and require copious inputs and resources, such as fertilizer, water, and land. Much uncertainty remains in quantifying important agriculture-climate interactions, including surface moisture and energy balances and biogeochemical cycling. Despite these externalities and uncertainties, agriculture is increasingly being leveraged to function as a net sink of anthropogenic carbon, and there is much emphasis on future sustainable intensification. Given its significance as a major environmental and climate forcing, there now exist a variety of approaches to represent agriculture in ESMs. These approaches are reviewed herein, and range from idealized representations of agricultural extent to the development of coupled climate-crop models that capture dynamic feedbacks. We highlight the robust agriculture-climate interactions and responses identified by these modeling efforts, as well as existing uncertainties and model limitations. To this end, coordinated and benchmarking assessments of land-use-climate feedbacks can be leveraged for further improvements in ESM's agricultural representations. We suggest key areas for continued model development, including incorporating irrigation and biogeochemical cycling in particular. Last, we pose several critical research questions to guide future work. Our review focuses on ESM representations of climate-surface interactions over managed agricultural lands, rather than on ESMs as an estimation tool for crop yields and productivity.

Quality assurance of weather data for agricultural system model input

USDA-ARS?s Scientific Manuscript database

It is well known that crop production and hydrologic variation on watersheds is weather related. Rarely, however, is meteorological data quality checks reported for agricultural systems model research. We present quality assurance procedures for agricultural system model weather data input. Problems...

Experimental design for three interrelated marine ice sheet and ocean model intercomparison projects: MISMIP v. 3 (MISMIP +), ISOMIP v. 2 (ISOMIP +) and MISOMIP v. 1 (MISOMIP1)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Asay-Davis, Xylar S.; Cornford, Stephen L.; Durand, Gaël

Coupled ice sheet-ocean models capable of simulating moving grounding lines are just becoming available. Such models have a broad range of potential applications in studying the dynamics of marine ice sheets and tidewater glaciers, from process studies to future projections of ice mass loss and sea level rise. The Marine Ice Sheet-Ocean Model Intercomparison Project (MISOMIP) is a community effort aimed at designing and coordinating a series of model intercomparison projects (MIPs) for model evaluation in idealized setups, model verification based on observations, and future projections for key regions of the West Antarctic Ice Sheet (WAIS). Here we describe computationalmore » experiments constituting three interrelated MIPs for marine ice sheet models and regional ocean circulation models incorporating ice shelf cavities. These consist of ice sheet experiments under the Marine Ice Sheet MIP third phase (MISMIP+), ocean experiments under the Ice Shelf-Ocean MIP second phase (ISOMIP+) and coupled ice sheet-ocean experiments under the MISOMIP first phase (MISOMIP1). All three MIPs use a shared domain with idealized bedrock topography and forcing, allowing the coupled simulations (MISOMIP1) to be compared directly to the individual component simulations (MISMIP+ and ISOMIP+). The experiments, which have qualitative similarities to Pine Island Glacier Ice Shelf and the adjacent region of the Amundsen Sea, are designed to explore the effects of changes in ocean conditions, specifically the temperature at depth, on basal melting and ice dynamics. In future work, differences between model results will form the basis for the evaluation of the participating models.« less

Evaluating the Effectiveness of Agricultural Management Practices under Climate Change for Water Quality Improvement in a Rural Agricultural Watershed of Oklahoma, USA

NASA Astrophysics Data System (ADS)

Rasoulzadeh Gharibdousti, S.; Kharel, G.; Stoecker, A.; Storm, D.

2016-12-01

One of the main causes of water quality impairment in the United States is human induced Non-Point Source (NPS) pollution through intensive agriculture. Fort Cobb Reservoir (FCR) watershed located in west-central Oklahoma, United States is a rural agricultural catchment with known issues of NPS pollution including suspended solids, siltation, nutrients, and pesticides. The FCR watershed with an area of 813 km2 includes one major lake fed by four tributaries. Recently, several Best Management Practices (BMPs) have been implemented in the watershed (such as no-tillage and cropland to grassland conversion) to improve water quality. In this study we aim to estimate the effectiveness of different BMPs in improving watershed health under future climate projections. We employed the Soil and Water Assessment Tool (SWAT) to develop the hydrological model of the FCR watershed. The watershed was delineated using the 10 m USGS Digital Elevation Model and divided into 43 sub-basins with an average area of 8 km2 (min. 0.2 km2 - max. 28 km2). Through a combination of Soil Survey Geographic Database- SSURGO soil data, the US Department of Agriculture crop layer and the slope information, the watershed was further divided into 1,217 hydrologic response units. The historical climate pattern in the watershed was represented by two different weather stations. The model was calibrated (1991 - 2000) and validated (2001 - 2010) against the monthly USGS observations of streamflow recorded at the watershed outlet using three statistical matrices: coefficient of determination (R2), Nash-Sutcliffe efficiency (NS) and percentage bias (PB). Model parametrization resulted into satisfactory values of R2 (0.56) and NS (0.56) in calibration period and an excellent model performance (R2 = 0.75; NS = 0.75; PB = <1) in validation period. We have selected 19 BMPs to estimate their efficacy in terms of water and sediment yields under a combination of three Coupled Model Intercomparison Project-5 Global

The hydrological impact of geoengineering in the Geoengineering Model Intercomparison Project (GeoMIP)

NASA Astrophysics Data System (ADS)

Tilmes, Simone; Fasullo, John; Lamarque, Jean-Francois; Marsh, Daniel R.; Mills, Michael; Alterskjær, Kari; Muri, Helene; Kristjánsson, Jón E.; Boucher, Olivier; Schulz, Michael; Cole, Jason N. S.; Curry, Charles L.; Jones, Andy; Haywood, Jim; Irvine, Peter J.; Ji, Duoying; Moore, John C.; Karam, Diana B.; Kravitz, Ben; Rasch, Philip J.; Singh, Balwinder; Yoon, Jin-Ho; Niemeier, Ulrike; Schmidt, Hauke; Robock, Alan; Yang, Shuting; Watanabe, Shingo

2013-10-01

The hydrological impact of enhancing Earth's albedo by solar radiation management is investigated using simulations from 12 Earth System models contributing to the Geoengineering Model Intercomparison Project (GeoMIP). We contrast an idealized experiment, G1, where the global mean radiative forcing is kept at preindustrial conditions by reducing insolation while the CO2 concentration is quadrupled to a 4×CO2 experiment. The reduction of evapotranspiration over land with instantaneously increasing CO2 concentrations in both experiments largely contributes to an initial reduction in evaporation. A warming surface associated with the transient adjustment in 4×CO2 generates an increase of global precipitation by around 6.9% with large zonal and regional changes in both directions, including a precipitation increase of 10% over Asia and a reduction of 7% for the North American summer monsoon. Reduced global evaporation persists in G1 with temperatures close to preindustrial conditions. Global precipitation is reduced by around 4.5%, and significant reductions occur over monsoonal land regions: East Asia (6%), South Africa (5%), North America (7%), and South America (6%). The general precipitation performance in models is discussed in comparison to observations. In contrast to the 4×CO2 experiment, where the frequency of months with heavy precipitation intensity is increased by over 50% in comparison to the control, a reduction of up to 20% is simulated in G1. These changes in precipitation in both total amount and frequency of extremes point to a considerable weakening of the hydrological cycle in a geoengineered world.

Modelling carbon dioxide emissions from agricultural soils in Canada.

PubMed

Yadav, Dhananjay; Wang, Junye

2017-11-01

Agricultural soils are a leading source of atmospheric greenhouse gas (GHG) emissions and are major contributors to global climate change. Carbon dioxide (CO 2 ) makes up 20% of the total GHG emitted from agricultural soil. Therefore, an evaluation of CO 2 emissions from agricultural soil is necessary in order to make mitigation strategies for environmental efficiency and economic planning possible. However, quantification of CO 2 emissions through experimental methods is constrained due to the large time and labour requirements for analysis. Therefore, a modelling approach is needed to achieve this objective. In this paper, the DeNitrification-DeComposition (DNDC), a process-based model, was modified to predict CO 2 emissions for Canada from regional conditions. The modified DNDC model was applied at three experimental sites in the province of Saskatchewan. The results indicate that the simulations of the modified DNDC model are in good agreement with observations. The agricultural management of fertilization and irrigation were evaluated using scenario analysis. The simulated total annual CO 2 flux changed on average by ±13% and ±1% following a ±50% variance of the total amount of N applied by fertilising and the total amount of water through irrigation applications, respectively. Therefore, careful management of irrigation and applications of fertiliser can help to reduce CO 2 emissions from the agricultural sector. Copyright © 2017 Elsevier Ltd. All rights reserved.

The Impact of Abrupt Suspension of Solar Radiation Management (Termination Effect) in Experiment G2 of the Geoengineering Model Intercomparison Project (GeoMIP)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jones, Andrew; Haywood, J.; Alterskjaer, Kari

2013-09-11

We have examined changes in climate which result from the sudden termination of geoengineering after 50 years of offsetting a 1% per annum increase in CO2 concentra- tions as simulated by 11 different climate models in experiment G2 of the Geoengineering Model Intercomparison Project. The models agree on a rapid rate of global-mean warming following termination, accompanied by increases in global-mean precipitation rate and in plant net primary productivity, and decreases in sea-ice cover. While there is a considerable degree of consensus for the geographical distribution of warming, there is much less of an agreement regarding the patterns of changemore » in the other quantities.« less

Quantifying the importance of model-to-model variability in integrated assessments of 21st century climate

NASA Astrophysics Data System (ADS)

Bond-Lamberty, B. P.; Jones, A. D.; Shi, X.; Calvin, K. V.

2016-12-01

The C4MIP and CMIP5 model intercomparison projects (MIPs) highlighted uncertainties in climate projections, driven to a large extent by interactions between the terrestrial carbon cycle and climate feedbacks. In addition, the importance of feedbacks between human (energy and economic) systems and natural (carbon and climate) systems is poorly understood, and not considered in the previous MIP protocols. The experiments conducted under the previous Integrated Earth System Model (iESM) project, which coupled a earth system model with an integrated assessment model (GCAM), found that the inclusion of climate feedbacks on the terrestrial system in an RCP4.5 scenario increased ecosystem productivity, resulting in declines in cropland extent and increases in bioenergy production and forest cover. As a follow-up to these studies and to further understand climate-carbon cycle interactions and feedbacks, we examined the robustness of these results by running a suite of GCAM-only experiments using changes in ecosystem productivity derived from both the CMIP5 archive and the Agricultural Model Intercomparison Project. In our results, the effects of climate on yield in an RCP8.5 scenario tended to be more positive than those of AgMIP, but more negative than those of the other CMIP models. We discuss these results and the implications of model-to-model variability for integrated coupling studies of the future earth system.

Environmental sub models for a macroeconomic model: agricultural contribution to climate change and acidification in Denmark.

PubMed

Jensen, Trine S; Jensen, Jørgen D; Hasler, Berit; Illerup, Jytte B; Andersen, Frits M

2007-01-01

Integrated modelling of the interaction between environmental pressure and economic development is a useful tool to evaluate environmental consequences of policy initiatives. However, the usefulness of such models is often restricted by the fact that these models only include a limited set of environmental impacts, which are often energy-related emissions. In order to evaluate the development in the overall environmental pressure correctly, these model systems must be extended. In this article an integrated macroeconomic model system of the Danish economy with environmental modules of energy related emissions is extended to include the agricultural contribution to climate change and acidification. Next to the energy sector, the agricultural sector is the most important contributor to these environmental themes and subsequently the extended model complex calculates more than 99% of the contribution to both climate change and acidification. Environmental sub-models are developed for agriculture-related emissions of CH(4), N(2)O and NH(3). Agricultural emission sources related to the production specific activity variables are mapped and emission dependent parameters are identified in order to calculate emission coefficients. The emission coefficients are linked to the economic activity variables of the Danish agricultural production. The model system is demonstrated by projections of agriculture-related emissions in Denmark under two alternative sets of assumptions: a baseline projection of the general economic development and a policy scenario for changes in the husbandry sector within the agricultural sector.

Intercomparison of land-surface parameterizations launched

NASA Astrophysics Data System (ADS)

Henderson-Sellers, A.; Dickinson, R. E.

One of the crucial tasks for climatic and hydrological scientists over the next several years will be validating land surface process parameterizations used in climate models. There is not, necessarily, a unique set of parameters to be used. Different scientists will want to attempt to capture processes through various methods “for example, Avissar and Verstraete, 1990”. Validation of some aspects of the available (and proposed) schemes' performance is clearly required. It would also be valuable to compare the behavior of the existing schemes [for example, Dickinson et al., 1991; Henderson-Sellers, 1992a].The WMO-CAS Working Group on Numerical Experimentation (WGNE) and the Science Panel of the GEWEX Continental-Scale International Project (GCIP) [for example, Chahine, 1992] have agreed to launch the joint WGNE/GCIP Project for Intercomparison of Land-Surface Parameterization Schemes (PILPS). The principal goal of this project is to achieve greater understanding of the capabilities and potential applications of existing and new land-surface schemes in atmospheric models. It is not anticipated that a single “best” scheme will emerge. Rather, the aim is to explore alternative models in ways compatible with their authors' or exploiters' goals and to increase understanding of the characteristics of these models in the scientific community.

The Effects of Liberalizing World Agricultural Trade: A Review of Modeling Studies

DTIC Science & Technology

2006-06-01

agricultural policy issues. Like the LINKAGE model analysis, the GTAP-AGR model analysis uses version 6.05 of the GTAP database with a base year of...the 2006 study—fully liberal- izing agricultural policy in equal increments from 2005 through 2010—would increase world economic welfare in 2015 by...Burfisher, ed., Agricultural Policy Reform in the WTO—The Road Ahead, Agricultural Economic Report No. 802 (U.S. Department of Agriculture, Economic

Past and future weather-induced risk in crop production

NASA Astrophysics Data System (ADS)

Elliott, J. W.; Glotter, M.; Russo, T. A.; Sahoo, S.; Foster, I.; Benton, T.; Mueller, C.

2016-12-01

Drought-induced agricultural loss is one of the most costly impacts of extreme weather and may harm more people than any other consequence of climate change. Improvements in farming practices have dramatically increased crop productivity, but yields today are still tightly linked to climate variation. We report here on a number of recent studies evaluating extreme event risk and impacts under historical and near future conditions, including studies conducted as part of the Agricultural Modeling Intercomparison and Improvement Project (AgMIP), the Inter-Sectoral Impacts Model Intercomparison Project (ISI-MIP) and the UK-US Taskforce on Extreme Weather and Global Food System Resilience.

The Cloud Feedback Model Intercomparison Project (CFMIP) contribution to CMIP6.

NASA Technical Reports Server (NTRS)

Webb, Mark J.; Andrews, Timothy; Bodas-Salcedo, Alejandro; Bony, Sandrine; Bretherton, Christopher S.; Chadwick, Robin; Chepfer, Helene; Douville, Herve; Good, Peter; Kay, Jennifer E.;

The System Dynamics Model for Development of Organic Agriculture

NASA Astrophysics Data System (ADS)

Rozman, Črtomir; Škraba, Andrej; Kljajić, Miroljub; Pažek, Karmen; Bavec, Martina; Bavec, Franci

2008-10-01

Organic agriculture is the highest environmentally valuable agricultural system, and has strategic importance at national level that goes beyond the interests of agricultural sector. In this paper we address development of organic farming simulation model based on a system dynamics methodology (SD). The system incorporates relevant variables, which affect the development of the organic farming. The group decision support system (GDSS) was used in order to identify most relevant variables for construction of causal loop diagram and further model development. The model seeks answers to strategic questions related to the level of organically utilized area, levels of production and crop selection in a long term dynamic context and will be used for simulation of different policy scenarios for organic farming and their impact on economic and environmental parameters of organic production at an aggregate level.

Interannual Tropical Rainfall Variability in General Circulation Model Simulations Associated with the Atmospheric Model Intercomparison Project.

NASA Astrophysics Data System (ADS)

Sperber, K. R.; Palmer, T. N.

1996-11-01

The interannual variability of rainfall over the Indian subcontinent, the African Sahel, and the Nordeste region of Brazil have been evaluated in 32 models for the period 1979-88 as part of the Atmospheric Model Intercomparison Project (AMIP). The interannual variations of Nordeste rainfall are the most readily captured, owing to the intimate link with Pacific and Atlantic sea surface temperatures. The precipitation variations over India and the Sahel are less well simulated. Additionally, an Indian monsoon wind shear index was calculated for each model. Evaluation of the interannual variability of a wind shear index over the summer monsoon region indicates that the models exhibit greater fidelity in capturing the large-scale dynamic fluctuations than the regional-scale rainfall variations. A rainfall/SST teleconnection quality control was used to objectively stratify model performance. Skill scores improved for those models that qualitatively simulated the observed rainfall/El Niño- Southern Oscillation SST correlation pattern. This subset of models also had a rainfall climatology that was in better agreement with observations, indicating a link between systematic model error and the ability to simulate interannual variations.A suite of six European Centre for Medium-Range Weather Forecasts (ECMWF) AMIP runs (differing only in their initial conditions) have also been examined. As observed, all-India rainfall was enhanced in 1988 relative to 1987 in each of these realizations. All-India rainfall variability during other years showed little or no predictability, possibly due to internal chaotic dynamics associated with intraseasonal monsoon fluctuations and/or unpredictable land surface process interactions. The interannual variations of Nordeste rainfall were best represented. The State University of New York at Albany/National Center for Atmospheric Research Genesis model was run in five initial condition realizations. In this model, the Nordeste rainfall

The AgMIP GRIDded Crop Modeling Initiative (AgGRID) and the Global Gridded Crop Model Intercomparison (GGCMI)

NASA Technical Reports Server (NTRS)

Elliott, Joshua; Muller, Christoff

2015-01-01

Climate change is a significant risk for agricultural production. Even under optimistic scenarios for climate mitigation action, present-day agricultural areas are likely to face significant increases in temperatures in the coming decades, in addition to changes in precipitation, cloud cover, and the frequency and duration of extreme heat, drought, and flood events (IPCC, 2013). These factors will affect the agricultural system at the global scale by impacting cultivation regimes, prices, trade, and food security (Nelson et al., 2014a). Global-scale evaluation of crop productivity is a major challenge for climate impact and adaptation assessment. Rigorous global assessments that are able to inform planning and policy will benefit from consistent use of models, input data, and assumptions across regions and time that use mutually agreed protocols designed by the modeling community. To ensure this consistency, large-scale assessments are typically performed on uniform spatial grids, with spatial resolution of typically 10 to 50 km, over specified time-periods. Many distinct crop models and model types have been applied on the global scale to assess productivity and climate impacts, often with very different results (Rosenzweig et al., 2014). These models are based to a large extent on field-scale crop process or ecosystems models and they typically require resolved data on weather, environmental, and farm management conditions that are lacking in many regions (Bondeau et al., 2007; Drewniak et al., 2013; Elliott et al., 2014b; Gueneau et al., 2012; Jones et al., 2003; Liu et al., 2007; M¨uller and Robertson, 2014; Van den Hoof et al., 2011;Waha et al., 2012; Xiong et al., 2014). Due to data limitations, the requirements of consistency, and the computational and practical limitations of running models on a large scale, a variety of simplifying assumptions must generally be made regarding prevailing management strategies on the grid scale in both the baseline and

GEO-LEO reflectance band inter-comparison with BRDF and atmospheric scattering corrections

NASA Astrophysics Data System (ADS)

Chang, Tiejun; Xiong, Xiaoxiong Jack; Keller, Graziela; Wu, Xiangqian

2017-09-01

The inter-comparison of the reflective solar bands between the instruments onboard a geostationary orbit satellite and onboard a low Earth orbit satellite is very helpful to assess their calibration consistency. GOES-R was launched on November 19, 2016 and Himawari 8 was launched October 7, 2014. Unlike the previous GOES instruments, the Advanced Baseline Imager on GOES-16 (GOES-R became GOES-16 after November 29 when it reached orbit) and the Advanced Himawari Imager (AHI) on Himawari 8 have onboard calibrators for the reflective solar bands. The assessment of calibration is important for their product quality enhancement. MODIS and VIIRS, with their stringent calibration requirements and excellent on-orbit calibration performance, provide good references. The simultaneous nadir overpass (SNO) and ray-matching are widely used inter-comparison methods for reflective solar bands. In this work, the inter-comparisons are performed over a pseudo-invariant target. The use of stable and uniform calibration sites provides comparison with appropriate reflectance level, accurate adjustment for band spectral coverage difference, reduction of impact from pixel mismatching, and consistency of BRDF and atmospheric correction. The site in this work is a desert site in Australia (latitude -29.0 South; longitude 139.8 East). Due to the difference in solar and view angles, two corrections are applied to have comparable measurements. The first is the atmospheric scattering correction. The satellite sensor measurements are top of atmosphere reflectance. The scattering, especially Rayleigh scattering, should be removed allowing the ground reflectance to be derived. Secondly, the angle differences magnify the BRDF effect. The ground reflectance should be corrected to have comparable measurements. The atmospheric correction is performed using a vector version of the Second Simulation of a Satellite Signal in the Solar Spectrum modeling and BRDF correction is performed using a semi

Modeling of pesticide emissions from agricultural ecosystems

NASA Astrophysics Data System (ADS)

Li, Rong

2012-04-01

Pesticides are applied to crops and soils to improve agricultural yields, but the use of pesticides has become highly regulated because of concerns about their adverse effects on human health and environment. Estimating pesticide emission rates from soils and crops is a key component for risk assessment for pesticide registration, identification of pesticide sources to the contamination of sensitive ecosystems, and appreciation of transport and fate of pesticides in the environment. Pesticide emission rates involve processes occurring in the soil, in the atmosphere, and on vegetation surfaces and are highly dependent on soil texture, agricultural practices, and meteorology, which vary significantly with location and/or time. To take all these factors into account for simulating pesticide emissions from large agricultural ecosystems, this study coupled a comprehensive meteorological model with a dynamic pesticide emission model. The combined model calculates hourly emission rates from both emission sources: current applications and soil residues resulting from historical use. The coupled modeling system is used to compute a gridded (36 × 36 km) hourly toxaphene emission inventory for North America for the year 2000 using a published U.S. toxaphene residue inventory and a Mexican toxaphene residue inventory developed using its historical application rates and a cropland inventory. To my knowledge, this is the first such hourly toxaphene emission inventory for North America. Results show that modeled emission rates have strong diurnal and seasonal variations at a given location and over the entire domain. The simulated total toxaphene emission from contaminated agricultural soils in North America in 2000 was about 255 t, which compares reasonably well to a published annual estimate. Most emissions occur in spring and summer, with domain-wide emission rates in April, May and, June of 36, 51, and 35 t/month, respectively. The spatial distribution of emissions depends

Assessing doses to terrestrial wildlife at a radioactive waste disposal site: inter-comparison of modelling approaches.

PubMed

Johansen, M P; Barnett, C L; Beresford, N A; Brown, J E; Černe, M; Howard, B J; Kamboj, S; Keum, D-K; Smodiš, B; Twining, J R; Vandenhove, H; Vives i Batlle, J; Wood, M D; Yu, C

2012-06-15

Radiological doses to terrestrial wildlife were examined in this model inter-comparison study that emphasised factors causing variability in dose estimation. The study participants used varying modelling approaches and information sources to estimate dose rates and tissue concentrations for a range of biota types exposed to soil contamination at a shallow radionuclide waste burial site in Australia. Results indicated that the dominant factor causing variation in dose rate estimates (up to three orders of magnitude on mean total dose rates) was the soil-to-organism transfer of radionuclides that included variation in transfer parameter values as well as transfer calculation methods. Additional variation was associated with other modelling factors including: how participants conceptualised and modelled the exposure configurations (two orders of magnitude); which progeny to include with the parent radionuclide (typically less than one order of magnitude); and dose calculation parameters, including radiation weighting factors and dose conversion coefficients (typically less than one order of magnitude). Probabilistic approaches to model parameterisation were used to encompass and describe variable model parameters and outcomes. The study confirms the need for continued evaluation of the underlying mechanisms governing soil-to-organism transfer of radionuclides to improve estimation of dose rates to terrestrial wildlife. The exposure pathways and configurations available in most current codes are limited when considering instances where organisms access subsurface contamination through rooting, burrowing, or using different localised waste areas as part of their habitual routines. Crown Copyright © 2012. Published by Elsevier B.V. All rights reserved.

Intercomparison of terrestrial carbon fluxes and carbon use efficiency simulated by CMIP5 Earth System Models

NASA Astrophysics Data System (ADS)

Kim, Dongmin; Lee, Myong-In; Jeong, Su-Jong; Im, Jungho; Cha, Dong Hyun; Lee, Sanggyun

2017-12-01

This study compares historical simulations of the terrestrial carbon cycle produced by 10 Earth System Models (ESMs) that participated in the fifth phase of the Coupled Model Intercomparison Project (CMIP5). Using MODIS satellite estimates, this study validates the simulation of gross primary production (GPP), net primary production (NPP), and carbon use efficiency (CUE), which depend on plant function types (PFTs). The models show noticeable deficiencies compared to the MODIS data in the simulation of the spatial patterns of GPP and NPP and large differences among the simulations, although the multi-model ensemble (MME) mean provides a realistic global mean value and spatial distributions. The larger model spreads in GPP and NPP compared to those of surface temperature and precipitation suggest that the differences among simulations in terms of the terrestrial carbon cycle are largely due to uncertainties in the parameterization of terrestrial carbon fluxes by vegetation. The models also exhibit large spatial differences in their simulated CUE values and at locations where the dominant PFT changes, primarily due to differences in the parameterizations. While the MME-simulated CUE values show a strong dependence on surface temperatures, the observed CUE values from MODIS show greater complexity, as well as non-linear sensitivity. This leads to the overall underestimation of CUE using most of the PFTs incorporated into current ESMs. The results of this comparison suggest that more careful and extensive validation is needed to improve the terrestrial carbon cycle in terms of ecosystem-level processes.

Airborne sulfur trace species intercomparison campaign: Sulfur dioxide, dimethylsulfide, hydrogen sulfide, carbon disulfide, and carbonyl sulfide

NASA Technical Reports Server (NTRS)

Gregory, Gerald L.; Hoell, James M., Jr.; Davis, Douglas D.

1991-01-01

Results from an airborne intercomparison of techniques to measure tropospheric levels of sulfur trace gases are presented. The intercomparison was part of the NASA Global Tropospheric Experiment (GTE) and was conducted during the summer of 1989. The intercomparisons were conducted on the Wallops Electra aircraft during flights from Wallops Island, Virginia, and Natal, Brazil. Sulfur measurements intercompared included sulfur dioxide (SO2), dimethylsulfide (DMS), hydrogen sulfide (H2S), carbon disulfide (CS2), and carbonyl sulfide (OCS). Measurement techniques ranged from filter collection systems with post-flight analyses to mass spectrometer and gas chromatograph systems employing various methods for measuring and identifying the sulfur gases during flight. Sampling schedules for the techniques ranged from integrated collections over periods as long as 50 minutes to one- to three-minute samples every ten or fifteen minutes. Several of the techniques provided measurements of more than one sulfur gas. Instruments employing different detection principles were involved in each of the sulfur intercomparisons. Also included in the intercomparison measurement scenario were a host of supporting measurements (i.e., ozone, nitrogen oxides, carbon monoxide, total sulfur, aerosols, etc.) for purposes of: (1) interpreting results (i.e., correlation of any noted instrument disagreement with the chemical composition of the measurement environment); and (2) providing supporting chemical data to meet CITE-3 science objectives of studying ozone/sulfur photochemistry, diurnal cycles, etc. The results of the intercomparison study are briefly discussed.

Representing Extremes in Agricultural Models

NASA Technical Reports Server (NTRS)

Ruane, Alex

2015-01-01

AgMIP and related projects are conducting several activities to understand and improve crop model response to extreme events. This involves crop model studies as well as the generation of climate datasets and scenarios more capable of capturing extremes. Models are typically less responsive to extreme events than we observe, and miss several forms of extreme events. Models also can capture interactive effects between climate change and climate extremes. Additional work is needed to understand response of markets and economic systems to food shocks. AgMIP is planning a Coordinated Global and Regional Assessment of Climate Change Impacts on Agricultural Production and Food Security with an aim to inform the IPCC Sixth Assessment Report.

Simulating wind energy resources with mesoscale models: Intercomparison of state-of-the-art models over Northern Europe

NASA Astrophysics Data System (ADS)

Hahmann, A. N.

2015-12-01

Mesoscale models are increasingly being used to estimate wind conditions to identify perspective areas and sites where to develop wind farm projects. Mesoscale models are useful because they give information over extensive areas with various terrain complexities where measurements are scarce and measurement campaigns costly. Various mesoscale models and families of mesoscale models are being used, with thousands of setup options. Since long-term integrations are expensive and tedious to carry out, only limited comparisons exist. We have carried out a blind benchmarking study to evaluate the capabilities of mesoscale models used in wind energy to estimate site wind conditions: to highlight common issues on mesoscale modeling of wind conditions on sites with different characteristics, and to identify gaps and strengths of models and understand the root conditions for further evaluating uncertainties. Three experimental sites with tall mast measurements were selected: FINO3 (offshore), Høvsøre (coastal), and Cabauw (land-based). The participants were asked to provide hourly time series of wind speed and direction, temperature, etc., at various heights for 2011. The methods used were left to the choice of the participants, but they were asked for a detailed description of their model and many other parameters (e.g., horizontal and vertical resolution, model parameterizations, surface roughness length) that could be used to group the models and interpret the results of the intercomparison. The analysis of the time series includes comparison to observations, summarized with well-known measures such as biases, RMSE, correlations, and of sector-wise statistics, and the temporal spectra. The statistics were grouped by the models, their spatial resolution, forcing data, various integration methods, etc. The results show high fidelity of the various entries in simulating the wind climate at the offshore and coastal site. Over land and the statistics of other derived fields

Inter-comparison between AIRS and IASI through Retrieved Parameters

NASA Technical Reports Server (NTRS)

Zhou, Daniel K.; Larar, Allen M.; Smith, William L.; Taylor, Jonathan P.; Schluessel, Peter; Strow, L. Larrabee; Mango, Steve

2008-01-01

A State-of-the-art retrieval algorithm dealing with all-weather conditions has been applied to satellite/aircraft instruments retrieving cloud/surface and atmospheric conditions. High quality retrievals have been achieved from IASI data. Surface, cloud, and atmospheric structure and variation are well captured by IASI measurements and/or retrievals. The same retrieval algorithm is also applied to AIRS for retrieval inter-comparison. Both AIRS and IASI have a similar FOV size but AIRS has a higher horizontal resolution. AIRS data can be interpolated to IASI horizontal resolution for inter-comparison at the same geophysical locations, however a temporal variation between AIRS and IASI observations need to be considered. JAIVEx has employed aircraft to obtain the atmospheric variation filling the temporal gap between two satellites. First results show that both AIRS and IASI have a very similar vertical resolving power, atmospheric conditions are well captured by both instruments, and radiances are well calibrated. AIRS data shown in retrievals (e.g., surface emissivity and moisture) have a relatively higher noise level. Since the this type of retrieval is very sensitive to its radiance quality, retrieval products inter-comparison is an effective way to identify/compare their radiance quality, in terms of a combination of spectral resolution and noise level, and to assess instrument performance. Additional validation analyses are needed to provide more-definitive conclusions.

The Economic Impacts of Climate Change on Agriculture: New Damage Functions from a Meta-Analsis and the GGCMI

NASA Astrophysics Data System (ADS)

Moore, F. C.; Baldos, U. L. C.; Hertel, T. W.; Diaz, D.

2016-12-01

Substantial advances have been made in recent years in understanding the effects of climate change on agriculture, but this is not currently represented in economic models used to quantify the benefits of reducing greenhouse gas emissions. In fact, the science regarding climate change impacts on agriculture in these models dates to the early 1990s or before. In this paper we derive new economic damage functions for the agricultural sector based on two methods for aggregating current scientific understanding of the impacts of warming on yields. We first present a new meta-analysis based on a review of the agronomic literature performed for the IPCC 5th Assessment Report and compare results from this approach with findings from the AgMIP Global Gridded Crop Model Intercomparison (GGCMI). We find yield impacts implied by the meta-analysis are generally more negative than those from the GGCMI, particularly at higher latitudes, but show substantial agreement in many areas. We then use both yield products as input to the Global Trade Analysis Project (GTAP) computable general equilibrium (CGE) model in order to estimate the welfare consequences of these yield shocks and to produce two new economic damage functions. These damage functions are consistently more negative than the current representation of agricultural damages in Integrated Asessment Models (IAMs), in some cases substantially so. Replacing the existing damage functions with those based on more recent science increases the social cost of carbon (SCC) by between 43% (GGCMI) and 143% (Meta-Analysis). In addition to presenting a new mutli-crop, multi-model gridded yield impact prouct that complements the GGCMI, this is also the first end-to-end study that directly links the biophysical impacts of climate change to the SCC, something we believe essential to improving the integrity of IAMs going forward.

Improving National Water Modeling: An Intercomparison of two High-Resolution, Continental Scale Models, CONUS-ParFlow and the National Water Model

NASA Astrophysics Data System (ADS)

Tijerina, D.; Gochis, D.; Condon, L. E.; Maxwell, R. M.

2017-12-01

Development of integrated hydrology modeling systems that couple atmospheric, land surface, and subsurface flow is growing trend in hydrologic modeling. Using an integrated modeling framework, subsurface hydrologic processes, such as lateral flow and soil moisture redistribution, are represented in a single cohesive framework with surface processes like overland flow and evapotranspiration. There is a need for these more intricate models in comprehensive hydrologic forecasting and water management over large spatial areas, specifically the Continental US (CONUS). Currently, two high-resolution, coupled hydrologic modeling applications have been developed for this domain: CONUS-ParFlow built using the integrated hydrologic model ParFlow and the National Water Model that uses the NCAR Weather Research and Forecasting hydrological extension package (WRF-Hydro). Both ParFlow and WRF-Hydro include land surface models, overland flow, and take advantage of parallelization and high-performance computing (HPC) capabilities; however, they have different approaches to overland subsurface flow and groundwater-surface water interactions. Accurately representing large domains remains a challenge considering the difficult task of representing complex hydrologic processes, computational expense, and extensive data needs; both models have accomplished this, but have differences in approach and continue to be difficult to validate. A further exploration of effective methodology to accurately represent large-scale hydrology with integrated models is needed to advance this growing field. Here we compare the outputs of CONUS-ParFlow and the National Water Model to each other and with observations to study the performance of hyper-resolution models over large domains. Models were compared over a range of scales for major watersheds within the CONUS with a specific focus on the Mississippi, Ohio, and Colorado River basins. We use a novel set of approaches and analysis for this comparison

Phosphorus modeling in tile drained agricultural systems using APEX

USDA-ARS?s Scientific Manuscript database

Phosphorus losses through tile drained systems in agricultural landscapes may be causing the persistent eutrophication problems observed in surface water. The purpose of this paper is to evaluate the state of the science in the Agricultural Policy/Environmental eXtender (APEX) model related to surf...

RAMI4PILPS: An intercomparison of formulations for the partitioning of solar radiation in land surface models

NASA Astrophysics Data System (ADS)

Widlowski, J.-L.; Pinty, B.; Clerici, M.; Dai, Y.; de Kauwe, M.; De Ridder, K.; Kallel, A.; Kobayashi, H.; Lavergne, T.; Ni-Meister, W.; Olchev, A.; Quaife, T.; Wang, S.; Yang, W.; Yang, Y.; Yuan, H.

2011-06-01

Remotely sensed, multiannual data sets of shortwave radiative surface fluxes are now available for assimilation into land surface schemes (LSSs) of climate and/or numerical weather prediction models. The RAMI4PILPS suite of virtual experiments assesses the accuracy and consistency of the radiative transfer formulations that provide the magnitudes of absorbed, reflected, and transmitted shortwave radiative fluxes in LSSs. RAMI4PILPS evaluates models under perfectly controlled experimental conditions in order to eliminate uncertainties arising from an incomplete or erroneous knowledge of the structural, spectral and illumination related canopy characteristics typical for model comparison with in situ observations. More specifically, the shortwave radiation is separated into a visible and near-infrared spectral region, and the quality of the simulated radiative fluxes is evaluated by direct comparison with a 3-D Monte Carlo reference model identified during the third phase of the Radiation transfer Model Intercomparison (RAMI) exercise. The RAMI4PILPS setup thus allows to focus in particular on the numerical accuracy of shortwave radiative transfer formulations and to pinpoint to areas where future model improvements should concentrate. The impact of increasing degrees of structural and spectral subgrid variability on the simulated fluxes is documented and the relevance of any thus emerging biases with respect to gross primary production estimates and shortwave radiative forcings due to snow and fire events are investigated.

The ASSET intercomparison of stratosphere and lower mesosphere humidity analyses

NASA Astrophysics Data System (ADS)

Thornton, H. E.; Jackson, D. R.; Bekki, S.; Bormann, N.; Errera, Q.; Geer, A. J.; Lahoz, W. A.; Rharmili, S.

2008-07-01

This paper presents results from the first detailed intercomparison of stratosphere-lower mesosphere water vapour analyses; it builds on earlier results from the "Assimilation of ENVISAT Data" (ASSET) project. With the availability of high resolution, good quality Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) water vapour profiles, the ability of four different atmospheric models to assimilate these data is tested. MIPAS data have been assimilated over September 2003 into the models of the European Centre for Medium Range Weather Forecasts (ECMWF), the Belgian Institute for Space and Aeronomy (BIRA-IASB), the French Service d'Aéronomie (SA-IPSL) and the UK Met Office. The resultant middle atmosphere humidity analyses are compared against independent satellite data from the Halogen Occultation Experiment (HALOE), the Polar Ozone and Aerosol Measurement (POAM III) and the Stratospheric Aerosol and Gas Experiment (SAGE II). The MIPAS water vapour profiles are generally well assimilated in the ECMWF, BIRA-IASB and SA systems, producing stratosphere-mesosphere water vapour fields where the main features compare favourably with the independent observations. However, the models are less capable of assimilating the MIPAS data where water vapour values are locally extreme or in regions of strong humidity gradients, such as the Southern Hemisphere lower stratosphere polar vortex. Differences in the analyses can be attributed to the choice of humidity control variable, how the background error covariance matrix is generated, the model resolution and its complexity, the degree of quality control of the observations and the use of observations near the model boundaries. Due to the poor performance of the Met Office analyses the results are not included in the intercomparison, but are discussed separately. The Met Office results highlight the pitfalls in humidity assimilation, and provide lessons that should be learnt by developers of stratospheric humidity

Spectroradiometer Intercomparison and Impact on Characterizing Photovoltaic Device Performance: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Habte, A.; Andreas, A.; Ottoson, L.

2014-11-01

Indoor and outdoor testing of photovoltaic (PV) device performance requires the use of solar simulators and natural solar radiation, respectively. This performance characterization requires accurate knowledge of spectral irradiance distribution that is incident on the devices. Spectroradiometers are used to measure the spectral distribution of solar simulators and solar radiation. On September 17, 2013, a global spectral irradiance intercomparison using spectroradiometers was organized by the Solar Radiation Research Laboratory (SRRL) at the National Renewable Energy Laboratory (NREL). This paper presents highlights of the results of this first intercomparison, which will help to decrease systematic inter-laboratory differences in the measurements ofmore » the outputs or efficiencies of PV devices and harmonize laboratory experimental procedures.« less

Intercomparison of three microwave/infrared high resolution line-by-line radiative transfer codes

NASA Astrophysics Data System (ADS)

Schreier, F.; Garcia, S. Gimeno; Milz, M.; Kottayil, A.; Höpfner, M.; von Clarmann, T.; Stiller, G.

2013-05-01

An intercomparison of three line-by-line (lbl) codes developed independently for atmospheric sounding - ARTS, GARLIC, and KOPRA - has been performed for a thermal infrared nadir sounding application assuming a HIRS-like (High resolution Infrared Radiation Sounder) setup. Radiances for the HIRS infrared channels and a set of 42 atmospheric profiles from the "Garand dataset" have been computed. Results of this intercomparison and a discussion of reasons of the observed differences are presented.

"Intelligent Ensemble" Projections of Precipitation and Surface Radiation in Support of Agricultural Climate Change Adaptation

NASA Technical Reports Server (NTRS)

Taylor, Patrick C.; Baker, Noel C.

2015-01-01

Earth's climate is changing and will continue to change into the foreseeable future. Expected changes in the climatological distribution of precipitation, surface temperature, and surface solar radiation will significantly impact agriculture. Adaptation strategies are, therefore, required to reduce the agricultural impacts of climate change. Climate change projections of precipitation, surface temperature, and surface solar radiation distributions are necessary input for adaption planning studies. These projections are conventionally constructed from an ensemble of climate model simulations (e.g., the Coupled Model Intercomparison Project 5 (CMIP5)) as an equal weighted average, one model one vote. Each climate model, however, represents the array of climate-relevant physical processes with varying degrees of fidelity influencing the projection of individual climate variables differently. Presented here is a new approach, termed the "Intelligent Ensemble, that constructs climate variable projections by weighting each model according to its ability to represent key physical processes, e.g., precipitation probability distribution. This approach provides added value over the equal weighted average method. Physical process metrics applied in the "Intelligent Ensemble" method are created using a combination of NASA and NOAA satellite and surface-based cloud, radiation, temperature, and precipitation data sets. The "Intelligent Ensemble" method is applied to the RCP4.5 and RCP8.5 anthropogenic climate forcing simulations within the CMIP5 archive to develop a set of climate change scenarios for precipitation, temperature, and surface solar radiation in each USDA Farm Resource Region for use in climate change adaptation studies.

Incorporating agricultural management into an earth system model for the Pacific Northwest region: Interactions between climate, hydrology, agriculture, and economics

NASA Astrophysics Data System (ADS)

Chinnayakanahalli, K.; Adam, J. C.; Stockle, C.; Nelson, R.; Brady, M.; Rajagopalan, K.; Barber, M. E.; Dinesh, S.; Malek, K.; Yorgey, G.; Kruger, C.; Marsh, T.; Yoder, J.

2011-12-01

For better management and decision making in the face of climate change, earth system models must explicitly account for natural resource and agricultural management activities. Including crop system, water management, and economic models into an earth system modeling framework can help in answering questions related to the impacts of climate change on irrigation water and crop productivity, how agricultural producers can adapt to anticipated climate change, and how agricultural practices can mitigate climate change. Herein we describe the coupling of the Variability Infiltration Capacity (VIC) land surface model, which solves the water and energy balances of the hydrologic cycle at regional scales, with a crop-growth model, CropSyst. This new model, VIC-CropSyst, is the land surface model that will be used in a new regional-scale model development project focused on the Pacific Northwest, termed BioEarth. Here we describe the VIC-CropSyst coupling process and its application over the Columbia River basin (CRB) using agricultural-specific land cover information. The Washington State Department of Agriculture (WSDA) and U. S. Department of Agriculture (USDA) cropland data layers were used to identify agricultural land use patterns, in which both irrigated and dry land crops were simulated. The VIC-CropSyst model was applied over the CRB for the historical period of 1976 - 2006 to establish a baseline for surface water availability, irrigation demand, and crop production. The model was then applied under future (2030s) climate change scenarios derived from statistically-downscaled Global Circulation Models output under two emission scenarios (A1B and B1). Differences between simulated future and historical irrigation demand, irrigation water availability, and crop production were used in an economics model to identify the most economically-viable future cropping pattern. The economics model was run under varying scenarios of regional growth, trade, water pricing, and

Intercomparison of Radiation Codes in Climate Models (ICRCCM) Infrared (Clear-Sky) Line-by Line Radiative Fluxes (DB1002)

DOE Data Explorer

Arking, A.; Ridgeway, B.; Clough, T.; Iacono, M.; Fomin, B.; Trotsenko, A.; Freidenreich, S.; Schwarzkopf, D.

1994-01-01

The intercomparison of Radiation Codes in Climate Models (ICRCCM) study was launched under the auspices of the World Meteorological Organization and with the support of the U.S. Department of Energy to document differences in results obtained with various radiation codes and radiation parameterizations in general circulation models (GCMs). ICRCCM produced benchmark, longwave, line-by-line (LBL) fluxes that may be compared against each other and against models of lower spectral resolution. During ICRCCM, infrared fluxes and cooling rates for several standard model atmospheres with varying concentrations of water vapor, carbon dioxide, and ozone were calculated with LBL methods at resolutions of 0.01 cm-1 or higher. For comparison with other models, values were summed for the IR spectrum and given at intervals of 5 or 10 cm-1. This archive contains fluxes for ICRCCM-prescribed clear-sky cases. Radiative flux and cooling-rate profiles are given for specified atmospheric profiles for temperature, water vapor, and ozone-mixing ratios. The archive contains 328 files, including spectral summaries, formatted data files, and a variety of programs (i.e., C-shell scripts, FORTRAN codes, and IDL programs) to read, reformat, and display data. Collectively, these files require approximately 59 MB of disk space.

BIPM project: Intercomparison of water triple-point cells

NASA Astrophysics Data System (ADS)

Chattle, M. V.; Butler, J.

1994-12-01

The paper presents the results of an intercomparison between 3 triple point of water cells circulated by the Bureau International des Poids et Measures (BIPM), and a cell which is one of those used as a reference cell at the National Physical Laboratory (NPL). All 4 cells were prepared, stored and measured in the manner normally adopted at NPL. The results of the intercomparison show that over the course of about 6 weeks the temperatures of the 3 circulated cells generally agreed within 0.20 mK, with a maximum difference of 0.27(7) mK. Over the same period, the total variations of temperature measured in the 3 individual cells were 0.04 mK, 0.08 mK and 0.18 mK, respectively; the NPL cell varied by 0.10 mK. Gallium point measurements made over a similar period confirmed that these differences were partly due to small drifts in the thermometer resistance or in the measuring system.

The Cloud Feedback Model Intercomparison Project (CFMIP) contribution to CMIP6

DOE PAGES

Webb, Mark J.; Andrews, Timothy; Bodas-Salcedo, Alejandro; ...

2017-01-01

Our primary objective of CFMIP is to inform future assessments of cloud feedbacks through improved understanding of cloud–climate feedback mechanisms and better evaluation of cloud processes and cloud feedbacks in climate models. But, the CFMIP approach is also increasingly being used to understand other aspects of climate change, and so a second objective has now been introduced, to improve understanding of circulation, regional-scale precipitation, and non-linear changes. CFMIP is supporting ongoing model inter-comparison activities by coordinating a hierarchy of targeted experiments for CMIP6, along with a set of cloud-related output diagnostics. CFMIP contributes primarily to addressing the CMIP6 questions Howmore » does the Earth system respond to forcing? and What are the origins and consequences of systematic model biases? and supports the activities of the WCRP Grand Challenge on Clouds, Circulation and Climate Sensitivity.A compact set of Tier 1 experiments is proposed for CMIP6 to address this question: (1) what are the physical mechanisms underlying the range of cloud feedbacks and cloud adjustments predicted by climate models, and which models have the most credible cloud feedbacks? Additional Tier 2 experiments are proposed to address the following questions. (2) Are cloud feedbacks consistent for climate cooling and warming, and if not, why? (3) How do cloud-radiative effects impact the structure, the strength and the variability of the general atmospheric circulation in present and future climates? (4) How do responses in the climate system due to changes in solar forcing differ from changes due to CO 2, and is the response sensitive to the sign of the forcing? (5) To what extent is regional climate change per CO 2 doubling state-dependent (non-linear), and why? (6) Are climate feedbacks during the 20th century different to those acting on long-term climate change and climate sensitivity? (7) How do regional climate responses (e.g. in

The Cloud Feedback Model Intercomparison Project (CFMIP) contribution to CMIP6

DOE Office of Scientific and Technical Information (OSTI.GOV)

Webb, Mark J.; Andrews, Timothy; Bodas-Salcedo, Alejandro

Our primary objective of CFMIP is to inform future assessments of cloud feedbacks through improved understanding of cloud–climate feedback mechanisms and better evaluation of cloud processes and cloud feedbacks in climate models. But, the CFMIP approach is also increasingly being used to understand other aspects of climate change, and so a second objective has now been introduced, to improve understanding of circulation, regional-scale precipitation, and non-linear changes. CFMIP is supporting ongoing model inter-comparison activities by coordinating a hierarchy of targeted experiments for CMIP6, along with a set of cloud-related output diagnostics. CFMIP contributes primarily to addressing the CMIP6 questions Howmore » does the Earth system respond to forcing? and What are the origins and consequences of systematic model biases? and supports the activities of the WCRP Grand Challenge on Clouds, Circulation and Climate Sensitivity.A compact set of Tier 1 experiments is proposed for CMIP6 to address this question: (1) what are the physical mechanisms underlying the range of cloud feedbacks and cloud adjustments predicted by climate models, and which models have the most credible cloud feedbacks? Additional Tier 2 experiments are proposed to address the following questions. (2) Are cloud feedbacks consistent for climate cooling and warming, and if not, why? (3) How do cloud-radiative effects impact the structure, the strength and the variability of the general atmospheric circulation in present and future climates? (4) How do responses in the climate system due to changes in solar forcing differ from changes due to CO 2, and is the response sensitive to the sign of the forcing? (5) To what extent is regional climate change per CO 2 doubling state-dependent (non-linear), and why? (6) Are climate feedbacks during the 20th century different to those acting on long-term climate change and climate sensitivity? (7) How do regional climate responses (e.g. in

An energetic perspective on hydrological cycle changes in the Geoengineering Model Intercomparison Project

NASA Astrophysics Data System (ADS)

Kravitz, Ben; Rasch, Philip J.; Forster, Piers M.; Andrews, Timothy; Cole, Jason N. S.; Irvine, Peter J.; Ji, Duoying; Kristjánsson, Jón Egill; Moore, John C.; Muri, Helene; Niemeier, Ulrike; Robock, Alan; Singh, Balwinder; Tilmes, Simone; Watanabe, Shingo; Yoon, Jin-Ho

2013-12-01

of surface and atmospheric energy budget responses to CO2 and solar forcings can be used to reveal mechanisms of change in the hydrological cycle. We apply this energetic perspective to output from 11 fully coupled atmosphere-ocean general circulation models simulating experiment G1 of the Geoengineering Model Intercomparison Project (GeoMIP), which achieves top-of-atmosphere energy balance between an abrupt quadrupling of CO2 from preindustrial levels (abrupt4xCO2) and uniform solar irradiance reduction. We divide the climate system response into a rapid adjustment, in which climate response is due to adjustment of the atmosphere and land surface on short time scales, and a feedback response, in which the climate response is predominantly due to feedback related to global mean temperature changes. Global mean temperature change is small in G1, so the feedback response is also small. G1 shows a smaller magnitude of land sensible heat flux rapid adjustment than in abrupt4xCO2 and a larger magnitude of latent heat flux adjustment, indicating a greater reduction of evaporation and less land temperature increase than abrupt4xCO2. The sum of surface flux changes in G1 is small, indicating little ocean heat uptake. Using an energetic perspective to assess precipitation changes, abrupt4xCO2 shows decreased mean evaporative moisture flux and increased moisture convergence, particularly over land. However, most changes in precipitation in G1 are in mean evaporative flux, suggesting that changes in mean circulation are small.

WCRP Task Team for the Intercomparison of Reanalyses (TIRA): Motivation and Progress

NASA Technical Reports Server (NTRS)

Bosilovich, Michael

2017-01-01

Reanalyses have proven to be an important resource for weather and climate related research, as well as societal applications at large. Several centers have emerged to produce new atmospheric reanalyses in various forms every few years. In addition, land and ocean communities are producing disciplinary uncoupled reanalyses. Current research and development in reanalysis is directed at (1) extending the length of reanalyzed period and (2) use of coupled Earth system models for climate reanalysis. While WCRPs involvement in the reanalyses communities through its Data Advisory Council (WDAC) has been substantial, for example in organizing international conferences on reanalyses, a central team of reanalyses expertise is not in place in the WCRP structure. The differences among reanalyses and their inherent uncertainties are some of the most important questions for both users and developers of reanalyses. Therefore, a collaborative effort to systematically assess and intercompare reanalyses would be a logical progression that fills the needs of the community and contributes to the WCRP mission. The primary charge to the TIRA is to develop a reanalysis intercomparison project plan that will attain the following objectives.1)To foster understanding and estimation of uncertainties in reanalysis data by intercomparison and other means 2)To communicate new developments and best practices among the reanalyses producing centers 3)To enhance the understanding of data and assimilation issues and their impact on uncertainties, leading to improved reanalyses for climate assessment 4)To communicate the strengths and weaknesses of reanalyses, their fitness for purpose, and best practices in the use of reanalysis datasets by the scientific community. This presentation outlines the need for a task team on reanalyses, their intercomparison, the objectives of the team and progress thus far.

Airborne hygrometer calibration inter-comparison against a metrological water vapour standard

NASA Astrophysics Data System (ADS)

Smorgon, Denis; Boese, Norbert; Ebert, Volker

2014-05-01

Water vapour is the most important atmospheric greenhouse gas, which causes a major feedback to warming and other changes in the climate system. Knowledge of the distribution of water vapour and its climate induced changes is especially important in the upper troposphere and lower stratosphere (UT/LS) where vapour plays a critical role in atmospheric radiative balance, cirrus cloud formation, and photochemistry. But, our understanding of water in the UT/LS is limited by significant uncertainties in current UT/LS water measurements. One of the most comprehensive inter-comparison campaigns for airborne hygrometers, termed AQUAVIT (AV1) [1], took place in 2007 at the AIDA chamber at the Karlsruhe Institute of Technology (KIT) in Germany. AV1 was a well-defined, referred, blind inter-comparison of 22 airborne field instruments from 17 international research groups. One major metrological deficit of AV1, however, was, that no traceable reference instrument participated in the inter-comparison experiments and that the calibration procedures of the participating instruments were not monitored or interrogated. Consequently a follow-up inter-comparison was organized in April 2013, which for the first time also provides a traceable link to the international humidity scale. This AQUAVIT2 (AV2) campaign (details see: http://www.imk-aaf.kit.edu/aquavit/index.php/Main_Page) was again located at KIT/AIDA and organised by an international organizing committee including KIT, PTB, FZJ and others. Generally AV2 is divided in two parallel comparisons: 1) AV2-A uses the AIDA chamber for a simultaneous comparison of all instruments (incl. sampling and in-situ instruments) over a broad range of conditions characteristic for the UT/LS; 2) AV2-B, about which this paper is reporting, is a sequential comparison of selected hygrometers and (when possible) their reference calibration infrastructures by means of a chilled mirror hygrometer traced back to the primary National humidity standard

The agroecological matrix as alternative to the land-sparing/agriculture intensification model.

PubMed

Perfecto, Ivette; Vandermeer, John

2010-03-30

Among the myriad complications involved in the current food crisis, the relationship between agriculture and the rest of nature is one of the most important yet remains only incompletely analyzed. Particularly in tropical areas, agriculture is frequently seen as the antithesis of the natural world, where the problem is framed as one of minimizing land devoted to agriculture so as to devote more to conservation of biodiversity and other ecosystem services. In particular, the "forest transition model" projects an overly optimistic vision of a future where increased agricultural intensification (to produce more per hectare) and/or increased rural-to-urban migration (to reduce the rural population that cuts forest for agriculture) suggests a near future of much tropical aforestation and higher agricultural production. Reviewing recent developments in ecological theory (showing the importance of migration between fragments and local extinction rates) coupled with empirical evidence, we argue that there is little to suggest that the forest transition model is useful for tropical areas, at least under current sociopolitical structures. A model that incorporates the agricultural matrix as an integral component of conservation programs is proposed. Furthermore, we suggest that this model will be most successful within a framework of small-scale agroecological production.

FACE-IT. A Science Gateway for Food Security Research

DOE Office of Scientific and Technical Information (OSTI.GOV)

Montella, Raffaele; Kelly, David; Xiong, Wei

Progress in sustainability science is hindered by challenges in creating and managing complex data acquisition, processing, simulation, post-processing, and intercomparison pipelines. To address these challenges, we developed the Framework to Advance Climate, Economic, and Impact Investigations with Information Technology (FACE-IT) for crop and climate impact assessments. This integrated data processing and simulation framework enables data ingest from geospatial archives; data regridding, aggregation, and other processing prior to simulation; large-scale climate impact simulations with agricultural and other models, leveraging high-performance and cloud computing; and post-processing to produce aggregated yields and ensemble variables needed for statistics, for model intercomparison, and to connectmore » biophysical models to global and regional economic models. FACE-IT leverages the capabilities of the Globus Galaxies platform to enable the capture of workflows and outputs in well-defined, reusable, and comparable forms. We describe FACE-IT and applications within the Agricultural Model Intercomparison and Improvement Project and the Center for Robust Decision-making on Climate and Energy Policy.« less

Impacts of historic and projected land-cover, land-use, and land-management change on carbon and water fluxes: The Land Use Model Intercomparison Project (LUMIP)

NASA Astrophysics Data System (ADS)

Lawrence, D. M.; Lombardozzi, D. L.; Lawrence, P.; Hurtt, G. C.

2017-12-01

Human land-use activities have resulted in large changes to the Earth surface, with resulting implications for climate. In the future, land-use activities are likely to intensify to meet growing demands for food, fiber, and energy. The Land Use Model Intercomparison Project (LUMIP) aims to further advance understanding of the broad question of impacts of land-use and land-cover change (LULCC) as well as more detailed science questions to get at process-level attribution, uncertainty, and data requirements in more depth and sophistication than possible in a multi-model context to date. LUMIP is multi-faceted and aims to advance our understanding of land-use change from several perspectives. In particular, LUMIP includes a factorial set of land-only simulations that differ from each other with respect to the specific treatment of land use or land management (e.g., irrigation active or not, crop fertilization active or not, wood harvest on or not), or in terms of prescribed climate. This factorial series of experiments serves several purposes and is designed to provide a detailed assessment of how the specification of land-cover change and land management affects the carbon, water, and energy cycle response to land-use change. The potential analyses that are possible through this set of experiments are vast. For example, comparing a control experiment with all land management active to an experiment with no irrigation allows a multi-model assessment of whether or not the increasing use of irrigation during the 20th century is likely to have significantly altered trends of regional water and energy fluxes (and therefore climate) and/or crop yield and carbon fluxes in agricultural regions. Here, we will present preliminary results from the factorial set of experiments utilizing the Community Land Model (CLM5). The analyses presented here will help guide multi-model analyses once the full set of LUMIP simulations are available.

Intercomparison of shortwave radiative transfer schemes in global aerosol modeling: results from the AeroCom Radiative Transfer Experiment

NASA Astrophysics Data System (ADS)

Randles, C. A.; Kinne, S.; Myhre, G.; Schulz, M.; Stier, P.; Fischer, J.; Doppler, L.; Highwood, E.; Ryder, C.; Harris, B.; Huttunen, J.; Ma, Y.; Pinker, R. T.; Mayer, B.; Neubauer, D.; Hitzenberger, R.; Oreopoulos, L.; Lee, D.; Pitari, G.; Di Genova, G.; Quaas, J.; Rose, Fred G.; Kato, S.; Rumbold, S. T.; Vardavas, I.; Hatzianastassiou, N.; Matsoukas, C.; Yu, H.; Zhang, F.; Zhang, H.; Lu, P.

2012-12-01

In this study we examine the performance of 31 global model radiative transfer schemes in cloud-free conditions with prescribed gaseous absorbers and no aerosols (Rayleigh atmosphere), with prescribed scattering-only aerosols, and with more absorbing aerosols. Results are compared to benchmark results from high-resolution, multi-angular line-by-line radiation models. For purely scattering aerosols, model bias relative to the line-by-line models in the top-of-the atmosphere aerosol radiative forcing ranges from roughly -10 to 20%, with over- and underestimates of radiative cooling at higher and lower sun elevation, respectively. Inter-model diversity (relative standard deviation) increases from ~10 to 15% as sun elevation increases. Inter-model diversity in atmospheric and surface forcing decreases with increased aerosol absorption, indicating that the treatment of multiple-scattering is more variable than aerosol absorption in the models considered. Aerosol radiative forcing results from multi-stream models are generally in better agreement with the line-by-line results than the simpler two-stream schemes. Considering radiative fluxes, model performance is generally the same or slightly better than results from previous radiation scheme intercomparisons. However, the inter-model diversity in aerosol radiative forcing remains large, primarily as a result of the treatment of multiple-scattering. Results indicate that global models that estimate aerosol radiative forcing with two-stream radiation schemes may be subject to persistent biases introduced by these schemes, particularly for regional aerosol forcing.

Intercomparison of shortwave radiative transfer schemes in global aerosol modeling: results from the AeroCom Radiative Transfer Experiment

NASA Astrophysics Data System (ADS)

Randles, C. A.; Kinne, S.; Myhre, G.; Schulz, M.; Stier, P.; Fischer, J.; Doppler, L.; Highwood, E.; Ryder, C.; Harris, B.; Huttunen, J.; Ma, Y.; Pinker, R. T.; Mayer, B.; Neubauer, D.; Hitzenberger, R.; Oreopoulos, L.; Lee, D.; Pitari, G.; Di Genova, G.; Quaas, J.; Rose, F. G.; Kato, S.; Rumbold, S. T.; Vardavas, I.; Hatzianastassiou, N.; Matsoukas, C.; Yu, H.; Zhang, F.; Zhang, H.; Lu, P.

2013-03-01

In this study we examine the performance of 31 global model radiative transfer schemes in cloud-free conditions with prescribed gaseous absorbers and no aerosols (Rayleigh atmosphere), with prescribed scattering-only aerosols, and with more absorbing aerosols. Results are compared to benchmark results from high-resolution, multi-angular line-by-line radiation models. For purely scattering aerosols, model bias relative to the line-by-line models in the top-of-the atmosphere aerosol radiative forcing ranges from roughly -10 to 20%, with over- and underestimates of radiative cooling at lower and higher solar zenith angle, respectively. Inter-model diversity (relative standard deviation) increases from ~10 to 15% as solar zenith angle decreases. Inter-model diversity in atmospheric and surface forcing decreases with increased aerosol absorption, indicating that the treatment of multiple-scattering is more variable than aerosol absorption in the models considered. Aerosol radiative forcing results from multi-stream models are generally in better agreement with the line-by-line results than the simpler two-stream schemes. Considering radiative fluxes, model performance is generally the same or slightly better than results from previous radiation scheme intercomparisons. However, the inter-model diversity in aerosol radiative forcing remains large, primarily as a result of the treatment of multiple-scattering. Results indicate that global models that estimate aerosol radiative forcing with two-stream radiation schemes may be subject to persistent biases introduced by these schemes, particularly for regional aerosol forcing.

Identifying Hydrologic Processes in Agricultural Watersheds Using Precipitation-Runoff Models

USGS Publications Warehouse

Linard, Joshua I.; Wolock, David M.; Webb, Richard M.T.; Wieczorek, Michael

2009-01-01

Understanding the fate and transport of agricultural chemicals applied to agricultural fields will assist in designing the most effective strategies to prevent water-quality impairments. At a watershed scale, the processes controlling the fate and transport of agricultural chemicals are generally understood only conceptually. To examine the applicability of conceptual models to the processes actually occurring, two precipitation-runoff models - the Soil and Water Assessment Tool (SWAT) and the Water, Energy, and Biogeochemical Model (WEBMOD) - were applied in different agricultural settings of the contiguous United States. Each model, through different physical processes, simulated the transport of water to a stream from the surface, the unsaturated zone, and the saturated zone. Models were calibrated for watersheds in Maryland, Indiana, and Nebraska. The calibrated sets of input parameters for each model at each watershed are discussed, and the criteria used to validate the models are explained. The SWAT and WEBMOD model results at each watershed conformed to each other and to the processes identified in each watershed's conceptual hydrology. In Maryland the conceptual understanding of the hydrology indicated groundwater flow was the largest annual source of streamflow; the simulation results for the validation period confirm this. The dominant source of water to the Indiana watershed was thought to be tile drains. Although tile drains were not explicitly simulated in the SWAT model, a large component of streamflow was received from lateral flow, which could be attributed to tile drains. Being able to explicitly account for tile drains, WEBMOD indicated water from tile drains constituted most of the annual streamflow in the Indiana watershed. The Nebraska models indicated annual streamflow was composed primarily of perennial groundwater flow and infiltration-excess runoff, which conformed to the conceptual hydrology developed for that watershed. The hydrologic

Cloud-resolving model intercomparison of an MC3E squall line case: Part I-Convective updrafts: CRM Intercomparison of a Squall Line

DOE PAGES

Fan, Jiwen; Han, Bin; Varble, Adam; ...

2017-09-06

An intercomparison study of a midlatitude mesoscale squall line is performed using the Weather Research and Forecasting (WRF) model at 1 km horizontal grid spacing with eight different cloud microphysics schemes to investigate processes that contribute to the large variability in simulated cloud and precipitation properties. All simulations tend to produce a wider area of high radar reflectivity (Z e > 45 dBZ) than observed but a much narrower stratiform area. Furthermore, the magnitude of the virtual potential temperature drop associated with the gust front passage is similar in simulations and observations, while the pressure rise and peak wind speedmore » are smaller than observed, possibly suggesting that simulated cold pools are shallower than observed. Most of the microphysics schemes overestimate vertical velocity and Z e in convective updrafts as compared with observational retrievals. Simulated precipitation rates and updraft velocities have significant variability across the eight schemes, even in this strongly dynamically driven system. Differences in simulated updraft velocity correlate well with differences in simulated buoyancy and low-level vertical perturbation pressure gradient, which appears related to cold pool intensity that is controlled by the evaporation rate. Simulations with stronger updrafts have a more optimal convective state, with stronger cold pools, ambient low-level vertical wind shear, and rear-inflow jets. We found that updraft velocity variability between schemes is mainly controlled by differences in simulated ice-related processes, which impact the overall latent heating rate, whereas surface rainfall variability increases in no-ice simulations mainly because of scheme differences in collision-coalescence parameterizations.« less

A new PUB-working group on SLope InterComparison Experiments (SLICE)

NASA Astrophysics Data System (ADS)

McGuire, K.; Retter, M.; Freer, J.; Troch, P.; McDonnell, J.

2006-05-01

The International Association of Hydrological Sciences (IAHS) decade on Prediction in Ungauged Basins (PUB) has the scientific goal to shift hydrology from calibration reliant models to new and rich understanding- based models. To support this, six PUB science themes have been developed under the PUB Science Steering group. Theme 1 covers basin inter-comparison and classification. The SLope InterComparison Experiment (SLICE) is a newly-formed working group aligned with theme 1. Its 2- year target is to promote the improved understanding of regional hydrological characteristics via hillslope inter- comparison studies and top-down analysis of data from hillslope experiments from around the world. It will further deliver the major building blocks of a catchment classification system. A first workshop of SLICE took place 26-28 September 2005 at the HJ Andrews Experimental Forest, Oregon, USA. 40 participants from seven countries were in attendance. The program consisted of keynote presentations on the state-of-the-art of hillslope hydrology, outlining a hillslope classification system, and through small group discussion, a focus on the following questions: a.) How can we capture flow path heterogeneity at the hillslope scale with residence time distributions? b.) Can networks help characterize hillslope subsurface systems? c.) What patterns are useful to characterize in a hillslope comparison context? d.) How does bedrock permeability condition hillslope response? e.) Can we actually observe pressure waves in the field and/or how likely are they to exist at the hillslope continuum scale? The poster presents an overview of the workshop outcomes and directions of future work.

1993 Intercomparison of Photometric Units Maintained at NIST (USA) and PTB (Germany)

PubMed Central

Ohno, Yoshihiro; Sauter, Georg

1995-01-01

A bilateral intercomparison of photometric units between NIST, USA and PTB, Germany has been conducted to update the knowledge of the relationship between the photometric units disseminated in each country. The luminous intensity unit (cd) and the luminous flux unit (lm) maintained at both laboratories are compared by circulating transfer standard lamps. Also, the photometric responsivity sv is compared by circulating a V(λ)-corrected detector with a built-in current-to-voltage converter. The results show that the difference of luminous intensity unit between NIST and PTB, (PTB-NIST)/NIST, is 0.2 % with a relative expanded uncertainty (coverage factor k = 2) of 0.24 %. The difference is reduced significantly from that at the 1985 CCPR intercomparison (0.9 %). The difference in luminous flux unit, (PTB – NIST)/NIST, is found to be 1.5 % with a relative expanded uncertainty (coverage factor k =2) of 0.15 %. The difference remained nearly the same as that at the 1985 intercomparison (1.6 %). These results agree with what is predicted from the history of maintaining the units at each laboratory. PMID:29151737

A statistical model for radar images of agricultural scenes

NASA Technical Reports Server (NTRS)

Frost, V. S.; Shanmugan, K. S.; Holtzman, J. C.; Stiles, J. A.

1982-01-01

The presently derived and validated statistical model for radar images containing many different homogeneous fields predicts the probability density functions of radar images of entire agricultural scenes, thereby allowing histograms of large scenes composed of a variety of crops to be described. Seasat-A SAR images of agricultural scenes are accurately predicted by the model on the basis of three assumptions: each field has the same SNR, all target classes cover approximately the same area, and the true reflectivity characterizing each individual target class is a uniformly distributed random variable. The model is expected to be useful in the design of data processing algorithms and for scene analysis using radar images.

Intercomparison of state-of-the-art models for wind energy resources with mesoscale models:

NASA Astrophysics Data System (ADS)

Olsen, Bjarke Tobias; Hahmann, Andrea N.; Sempreviva, Anna Maria; Badger, Jake; Joergensen, Hans E.

2016-04-01

vertical resolution, model parameterizations, surface roughness length) that could be used to group the various models and interpret the results of the intercomparison. 3. Main body abstract Twenty separate entries were received by the deadline of 31 March 2015. They included simulations done with various versions of the Weather Research and Forecast (WRF) model, but also of six other well-known mesoscale models. The various entries represent an excellent sample of the various models used in by the wind energy industry today. The analysis of the submitted time series included comparison to observations, summarized with well-known measures such as biases, RMSE, correlations, and of sector-wise statistics, e.g. frequency and Weibull A and k. The comparison also includes the observed and modeled temporal spectra. The various statistics were grouped as a function of the various models, their spatial resolution, forcing data, and the various integration methods. Many statistics have been computed and will be presented in addition to those shown in the Helsinki presentation. 4. Conclusions The analysis of the time series from twenty entries has shown to be an invaluable source of information about state of the art in wind modeling with mesoscale models. Biases between the simulated and observed wind speeds at hub heights (80-100 m AGL) from the various models are around ±1.0 m/s and fairly independent of the site and do not seem to be directly related to the model horizontal resolution used in the modeling. As probably expected, the wind speeds from the simulations using the various version of the WRF model cluster close to each other, especially in their description of the wind profile.

GCSS/WGNE Pacific Cross-section Intercomparison: Tropical and Subtropical Cloud Transitions

NASA Astrophysics Data System (ADS)

Teixeira, J.

2008-12-01

In this presentation I will discuss the role of the GEWEX Cloud Systems Study (GCSS) working groups in paving the way for substantial improvements in cloud parameterization in weather and climate models. The GCSS/WGNE Pacific Cross-section Intercomparison (GPCI) is an extension of GCSS and is a different type of model evaluation where climate models are analyzed along a Pacific Ocean transect from California to the equator. This approach aims at complementing the more traditional efforts in GCSS by providing a simple framework for the evaluation of models that encompasses several fundamental cloud regimes such as stratocumulus, shallow cumulus and deep cumulus, as well as the transitions between them. Currently twenty four climate and weather prediction models are participating in GPCI. We will present results of the comparison between models and recent satellite data. In particular, we will explore in detail the potential of the Atmospheric Infrared Sounder (AIRS) and CloudSat data for the evaluation of the representation of clouds and convection in climate models.

Airborne intercomparison of nitric oxide measurement techniques

NASA Technical Reports Server (NTRS)

Hoell, James M., Jr.; Gregory, Gerald L.; Mcdougal, David S.; Torres, Arnold L.; Davis, Douglas D.

1987-01-01

Results from an airborne intercomparison of techniques to measure tropospheric levels of nitric oxide (NO) are discussed. The intercomparison was part of the National Aeronautics and Space Administration's Global Tropospheric Experiment and was conducted during missions flown in the fall of 1983 and spring of 1984. Instruments intercompared included a laser-induced fluorescence (LIF) system and two chemiluminescence instruments (CL). NO mixing ratios from below 5 pptv (parts per trillion by volume) to greater than 100 pptv were reported, with the majority less than 20 pptv. Good correlation was observed between the measurements reported by the CL and LIF techniques. The general level of agreement observed for the ensemble of measurements obtained during the two missions provides the basis from which one can conclude that equally 'valid' measurements of background levels of NO can be expected from either CL or LIF instruments. At the same time the periods of disagreement that were observed between the CL and LIF instruments as well as between the two CL instruments highlight the difficulty of obtaining reliable measurements with NO mixing ratios in the 5-20 pptv range and emphasize the vigilance that should be maintained in future NO measurements.

Flood damage modeling based on expert knowledge: Insights from French damage model for agricultural sector

NASA Astrophysics Data System (ADS)

Grelot, Frédéric; Agenais, Anne-Laurence; Brémond, Pauline

2015-04-01

In France, since 2011, it is mandatory for local communities to conduct cost-benefit analysis (CBA) of their flood management projects, to make them eligible for financial support from the State. Meanwhile, as a support, the French Ministry in charge of Environment proposed a methodology to fulfill CBA. Like for many other countries, this methodology is based on the estimation of flood damage. However, existing models to estimate flood damage were judged not convenient for a national-wide use. As a consequence, the French Ministry in charge of Environment launched studies to develop damage models for different sectors, such as: residential sector, public infrastructures, agricultural sector, and commercial and industrial sector. In this presentation, we aim at presenting and discussing methodological choices of those damage models. They all share the same principle: no sufficient data from past events were available to build damage models on a statistical analysis, so modeling was based on expert knowledge. We will focus on the model built for agricultural activities and more precisely for agricultural lands. This model was based on feedback from 30 agricultural experts who experienced floods in their geographical areas. They were selected to have a representative experience of crops and flood conditions in France. The model is composed of: (i) damaging functions, which reveal physiological vulnerability of crops, (ii) action functions, which correspond to farmers' decision rules for carrying on crops after a flood, and (iii) economic agricultural data, which correspond to featured characteristics of crops in the geographical area where the flood management project studied takes place. The two first components are generic and the third one is specific to the area studied. It is, thus, possible to produce flood damage functions adapted to different agronomic and geographical contexts. In the end, the model was applied to obtain a pool of damage functions giving

Flood damage modeling based on expert knowledge: Insights from French damage model for agricultural sector

NASA Astrophysics Data System (ADS)

Grelot, Frédéric; Agenais, Anne-Laurence; Brémond, Pauline

2014-05-01

In France, since 2011, it is mandatory for local communities to conduct cost-benefit analysis (CBA) of their flood management projects, to make them eligible for financial support from the State. Meanwhile, as a support, the French Ministry in charge of Environment proposed a methodology to fulfill CBA. Like for many other countries, this methodology is based on the estimation of flood damage. Howerver, existing models to estimate flood damage were judged not convenient for a national-wide use. As a consequence, the French Ministry in charge of Environment launched studies to develop damage models for different sectors, such as: residential sector, public infrastructures, agricultural sector, and commercial and industrial sector. In this presentation, we aim at presenting and discussing methodological choices of those damage models. They all share the same principle: no sufficient data from past events were available to build damage models on a statistical analysis, so modeling was based on expert knowledge. We will focus on the model built for agricultural activities and more precisely for agricultural lands. This model was based on feedback from 30 agricultural experts who experienced floods in their geographical areas. They were selected to have a representative experience of crops and flood conditions in France. The model is composed of: (i) damaging functions, which reveal physiological vulnerability of crops, (ii) action functions, which correspond to farmers' decision rules for carrying on crops after a flood, and (iii) economic agricultural data, which correspond to featured characteristics of crops in the geographical area where the flood management project studied takes place. The two first components are generic and the third one is specific to the area studied. It is, thus, possible to produce flood damage functions adapted to different agronomic and geographical contexts. In the end, the model was applied to obtain a pool of damage functions giving

NASA Giovanni Portals for NLDAS/GLDAS Online Visualization, Analysis, and Intercomparison

NASA Technical Reports Server (NTRS)

Rui, Hualan; Teng, William L.; Vollmer, Bruce; Mocko, David M.; Beaudoing, Hiroko Kato; Rodell, Matthew

2011-01-01

The North American Land Data Assimilation System (NLDAS) and Global Land Data Assimilation System (GLDAS) are generating a series of land surface forcing (e.g., precipitation, surface meteorology, and radiation), state (e.g., soil moisture and temperature, and snow), and flux (e.g., evaporation and sensible heat flux) products, simulated by several land surface models. To date, NLDAS and GLDAS have generated more than 30 (1979 - present) and 60 (1948 - present) years of data, respectively. To further facilitate data accessibility and utilization, three new portals in the NASA Giovanni system have been made available for NLDAS and GLDAS online visualization, analysis, and intercomparison.

Estimation of Distributed Groundwater Pumping Rates in Yolo County,CA—Intercomparison of Two Modeling Frameworks

NASA Astrophysics Data System (ADS)

Maples, S.; Fogg, G. E.; Harter, T.

2015-12-01

Accurate estimation of groundwater (GW) budgets and effective management of agricultural GW pumping remains a challenge in much of California's Central Valley (CV) due to a lack of irrigation well metering. CVHM and C2VSim are two regional-scale integrated hydrologic models that provide estimates of historical and current CV distributed pumping rates. However, both models estimate GW pumping using conceptually different agricultural water models with uncertainties that have not been adequately investigated. Here, we evaluate differences in distributed agricultural GW pumping and recharge estimates related to important differences in the conceptual framework and model assumptions used to simulate surface water (SW) and GW interaction across the root zone. Differences in the magnitude and timing of GW pumping and recharge were evaluated for a subregion (~1000 mi2) coincident with Yolo County, CA, to provide similar initial and boundary conditions for both models. Synthetic, multi-year datasets of land-use, precipitation, evapotranspiration (ET), and SW deliveries were prescribed for each model to provide realistic end-member scenarios for GW-pumping demand and recharge. Results show differences in the magnitude and timing of GW-pumping demand, deep percolation, and recharge. Discrepancies are related, in large part, to model differences in the estimation of ET requirements and representation of soil-moisture conditions. CVHM partitions ET demand, while C2VSim uses a bulk ET rate, resulting in differences in both crop-water and GW-pumping demand. Additionally, CVHM assumes steady-state soil-moisture conditions, and simulates deep percolation as a function of irrigation inefficiencies, while C2VSim simulates deep percolation as a function of transient soil-moisture storage conditions. These findings show that estimates of GW-pumping demand are sensitive to these important conceptual differences, which can impact conjunctive-use water management decisions in the CV.

Stochastic and deterministic models for agricultural production networks.

PubMed

Bai, P; Banks, H T; Dediu, S; Govan, A Y; Last, M; Lloyd, A L; Nguyen, H K; Olufsen, M S; Rempala, G; Slenning, B D

2007-07-01

An approach to modeling the impact of disturbances in an agricultural production network is presented. A stochastic model and its approximate deterministic model for averages over sample paths of the stochastic system are developed. Simulations, sensitivity and generalized sensitivity analyses are given. Finally, it is shown how diseases may be introduced into the network and corresponding simulations are discussed.

The Hydrological Impact of Geoengineering in the Geoengineering Model Intercomparison Project (GeoMIP)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tilmes, S.; Fasullo, John; Lamarque, J.-F.

2013-10-14

Abstract: The hydrologic impact of enhancing Earth’s albedo due to solar radiation management (SRM) is investigated using simulations from 12 models contributing to the Geoengineering Model Intercomparison Project (GeoMIP). An artificial experiment is investigated, where global mean temperature is preserved at pre-industrial conditions, while atmospheric carbon dioxide concentrations are quadrupled. The associated reduction of downwelling surface solar radiation in a high CO2 environment leads to a reduction of global evaporation of 10% and 4% and precipitation of 6.1% and 6.3% over land and ocean, respectively. An initial reduction of latent heat flux at the surface is largely driven by reducedmore » evapotranspiration over land with instantly increasing CO2 concentrations in both experiments. A warming surface associated with the transient adjustment in the 4xCO2 experiment further generates an increase of global precipitation, with considerable regional changes, such as a significant precipitation reduction of 7% for the North American summer monsoon. Reduced global precipitation persists in the geoengineered experiment where temperatures are stabilized, with considerable regional rainfall deficits. Precipitation reductions that are consistent in sign across models are identified in the geoengineered experiment over monsoonal land regions of East Asia (6%), North America (7%), South America (6%) and South Africa (5%). In contrast to the 4xCO2 experiment, where the frequency of months with heavy precipitation intensity is increased by over 50%, it is reduced by up to 20% in the geoengineering scenario . The reduction in heavy precipitation is more pronounced over land than over the ocean, and accompanies a stronger reduction in evaporation over land. For northern mid-latitudes, maximum precipitation reduction over land ranges from 1 to 16% for individual models. For 45-65°N, the frequency of median to high intensity precipitation in summer is strongly

The Cloud Feedback Model Intercomparison Project (CFMIP) contribution to CMIP6

NASA Astrophysics Data System (ADS)

Webb, Mark J.; Andrews, Timothy; Bodas-Salcedo, Alejandro; Bony, Sandrine; Bretherton, Christopher S.; Chadwick, Robin; Chepfer, Hélène; Douville, Hervé; Good, Peter; Kay, Jennifer E.; Klein, Stephen A.; Marchand, Roger; Medeiros, Brian; Pier Siebesma, A.; Skinner, Christopher B.; Stevens, Bjorn; Tselioudis, George; Tsushima, Yoko; Watanabe, Masahiro

2017-01-01

The primary objective of CFMIP is to inform future assessments of cloud feedbacks through improved understanding of cloud-climate feedback mechanisms and better evaluation of cloud processes and cloud feedbacks in climate models. However, the CFMIP approach is also increasingly being used to understand other aspects of climate change, and so a second objective has now been introduced, to improve understanding of circulation, regional-scale precipitation, and non-linear changes. CFMIP is supporting ongoing model inter-comparison activities by coordinating a hierarchy of targeted experiments for CMIP6, along with a set of cloud-related output diagnostics. CFMIP contributes primarily to addressing the CMIP6 questions How does the Earth system respond to forcing? and What are the origins and consequences of systematic model biases? and supports the activities of the WCRP Grand Challenge on Clouds, Circulation and Climate Sensitivity.A compact set of Tier 1 experiments is proposed for CMIP6 to address this question: (1) what are the physical mechanisms underlying the range of cloud feedbacks and cloud adjustments predicted by climate models, and which models have the most credible cloud feedbacks? Additional Tier 2 experiments are proposed to address the following questions. (2) Are cloud feedbacks consistent for climate cooling and warming, and if not, why? (3) How do cloud-radiative effects impact the structure, the strength and the variability of the general atmospheric circulation in present and future climates? (4) How do responses in the climate system due to changes in solar forcing differ from changes due to CO2, and is the response sensitive to the sign of the forcing? (5) To what extent is regional climate change per CO2 doubling state-dependent (non-linear), and why? (6) Are climate feedbacks during the 20th century different to those acting on long-term climate change and climate sensitivity? (7) How do regional climate responses (e.g. in

Assessing the agricultural costs of climate change: Combining results from crop and economic models

NASA Astrophysics Data System (ADS)

Howitt, R. E.

2016-12-01

Any perturbation to a resource system used by humans elicits both technical and behavioral changes. For agricultural production, economic criteria and their associated models are usually good predictors of human behavior in agricultural production. Estimation of the agricultural costs of climate change requires careful downscaling of global climate models to the level of agricultural regions. Plant growth models for the dominant crops are required to accurately show the full range of trade-offs and adaptation mechanisms needed to minimize the cost of climate change. Faced with the shifts in the fundamental resource base of agriculture, human behavior can either exacerbate or offset the impact of climate change on agriculture. In addition, agriculture can be an important source of increased carbon sequestration. However the effectiveness and timing of this sequestration depends on agricultural practices and farmer behavior. Plant growth models and economic models have been shown to interact in two broad fashions. First there is the direct embedding of a parametric representation plant growth simulations in the economic model production function. A second and more general approach is to have plant growth and crop process models interact with economic models as they are simulated. The development of more general wrapper programs that transfer information between models rapidly and efficiently will encourage this approach. However, this method does introduce complications in terms of matching up disparate scales both in time and space between models. Another characteristic behavioral response of agricultural production is the distinction between the intensive margin which considers the quantity of resource, for example fertilizer, used for a given crop, and the extensive margin of adjustment that measures how farmers will adjust their crop proportions in response to climate change. Ideally economic models will measure the response to both these margins of adjustment

VLBI Digital-Backend Intercomparison Test Report

NASA Technical Reports Server (NTRS)

Whitney, Alan; Beaudoin, Christopher; Cappallo, Roger; Niell, Arthur; Petrachenko, Bill; Ruszczyk, Chester A.; Titus, Mike

2013-01-01

Issues related to digital-backend (DBE) systems can be difficult to evaluate in either local tests or actual VLBI experiments. The 2nd DBE intercomparison workshop at Haystack Observatory on 25-26 October 2012 provided a forum to explicitly address validation and interoperability issues among independent global developers of DBE equipment. This special report discusses the workshop. It identifies DBE systems that were tested at the workshop, describes the test objectives and procedures, and reports and discusses the results of the testing.

Forward Model Studies of Water Vapor Using Scanning Microwave Radiometers, Global Positioning System, and Radiosondes during the Cloudiness Intercomparison Experiment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mattioli, Vinia; Westwater, Ed R.; Gutman, S.

2005-05-01

Brightness temperatures computed from five absorption models and radiosonde observations were analyzed by comparing them with measurements from three microwave radiometers at 23.8 and 31.4 GHz. Data were obtained during the Cloudiness Inter-Comparison experiment at the U.S. Department of Energy's Atmospheric Radiation Measurement Program's (ARM) site in North-Central Oklahoma in 2003. The radiometers were calibrated using two procedures, the so-called instantaneous ?tipcal? method and an automatic self-calibration algorithm. Measurements from the radiometers were in agreement, with less than a 0.4-K difference during clear skies, when the instantaneous method was applied. Brightness temperatures from the radiometer and the radiosonde showed anmore » agreement of less than 0.55 K when the most recent absorption models were considered. Precipitable water vapor (PWV) computed from the radiometers were also compared to the PWV derived from a Global Positioning System station that operates at the ARM site. The instruments agree to within 0.1 cm in PWV retrieval.« less

The ASSET intercomparison of stratosphere and lower mesosphere humidity analyses

NASA Astrophysics Data System (ADS)

Thornton, H. E.; Jackson, D. R.; Bekki, S.; Bormann, N.; Errera, Q.; Geer, A. J.; Lahoz, W. A.; Rharmili, S.

2009-02-01

This paper presents results from the first detailed intercomparison of stratosphere-lower mesosphere water vapour analyses; it builds on earlier results from the EU funded framework V "Assimilation of ENVISAT Data" (ASSET) project. Stratospheric water vapour plays an important role in many key atmospheric processes and therefore an improved understanding of its daily variability is desirable. With the availability of high resolution, good quality Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) water vapour profiles, the ability of four different atmospheric models to assimilate these data is tested. MIPAS data have been assimilated over September 2003 into the models of the European Centre for Medium Range Weather Forecasts (ECMWF), the Belgian Institute for Space and Aeronomy (BIRA-IASB), the French Service d'Aéronomie (SA-IPSL) and the UK Met Office. The resultant middle atmosphere humidity analyses are compared against independent satellite data from the Halogen Occultation Experiment (HALOE), the Polar Ozone and Aerosol Measurement (POAM III) and the Stratospheric Aerosol and Gas Experiment (SAGE II). The MIPAS water vapour profiles are generally well assimilated in the ECMWF, BIRA-IASB and SA systems, producing stratosphere-mesosphere water vapour fields where the main features compare favourably with the independent observations. However, the models are less capable of assimilating the MIPAS data where water vapour values are locally extreme or in regions of strong humidity gradients, such as the southern hemisphere lower stratosphere polar vortex. Differences in the analyses can be attributed to the choice of humidity control variable, how the background error covariance matrix is generated, the model resolution and its complexity, the degree of quality control of the observations and the use of observations near the model boundaries. Due to the poor performance of the Met Office analyses the results are not included in the intercomparison

Total ozone measurement: Intercomparison of prototype New Zealand filter instrument and Dobson spectrophotometer

NASA Technical Reports Server (NTRS)

Basher, R. E.

1978-01-01

A five month intercomparison showed that the total ozone amounts of a prototype narrowband interference filter instrument were 7% less than those of a Dobson instrument for an ozone range of 0.300 to 0.500 atm cm and for airmasses less than two. The 7% bias was within the intercomparison calibration uncertainty. An airmass dependence in the Dobson instrument made the bias relationship airmass-dependent but the filter instrument's ozone values were generally constant to 2% up to an airmass of four. Long term drift in the bias was negligible.

Development of an Integrated Wastewater Treatment System/water reuse/agriculture model

NASA Astrophysics Data System (ADS)

Fox, C. H.; Schuler, A.

2017-12-01

Factors like increasing population, urbanization, and climate change have made the management of water resources a challenge for municipalities. By understanding wastewater recycling for agriculture in arid regions, we can expand the supply of water to agriculture and reduce energy use at wastewater treatment plants (WWTPs). This can improve management decisions between WWTPs and water managers. The objective of this research is to develop a prototype integrated model of the wastewater treatment system and nearby agricultural areas linked by water and nutrients, using the Albuquerque Southeast Eastern Reclamation Facility (SWRF) and downstream agricultural system as a case study. Little work has been done to understand how such treatment technology decisions affect the potential for water ruse, nutrient recovery in agriculture, overall energy consumption and agriculture production and water quality. A holistic approach to understanding synergies and tradeoffs between treatment, reuse, and agriculture is needed. For example, critical wastewater treatment process decisions include options to nitrify (oxidize ammonia), which requires large amounts of energy, to operate at low dissolved oxygen concentrations, which requires much less energy, whether to recover nitrogen and phosphorus, chemically in biosolids, or in reuse water for agriculture, whether to generate energy from anaerobic digestion, and whether to develop infrastructure for agricultural reuse. The research first includes quantifying existing and feasible agricultural sites suitable for irrigation by reuse wastewater as well as existing infrastructure such as irrigation canals and piping by using GIS databases. Second, a nutrient and water requirement for common New Mexico crop is being determined. Third, a wastewater treatment model will be utilized to quantify energy usage and nutrient removal under various scenarios. Different agricultural reuse sensors and treatment technologies will be explored. The

The April 1994 and October 1994 radon intercomparisons at EML

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fisenne, I.M.; George, A.C.; Perry, P.M.

1995-10-01

Quality assurance/quality control (QA/QC) are the backbone of many commercial and research processes and programs. QA/QC research tests the state of a functioning system, be it the production of manufactured goods or the ability to make accurate and precise measurements. The quality of the radon measurements in the US have been tested under controlled conditions in semi-annual radon gas intercomparison exercises sponsored by the Environmental Measurements Laboratory (EML) since 1981. The two Calendar Year 1994 radon gas intercomparison exercises were conducted in the EML exposure chamber. Thirty-two groups including US Federal facilities, USDOE contractors, national and state laboratories, universities andmore » foreign institutions participated in these exercises. The majority of the participant`s results were within {+-}10% of the EML value at radon concentrations of 570 and 945 Bq m{sup {minus}3}.« less

Task-focused modeling in automated agriculture

NASA Astrophysics Data System (ADS)

Vriesenga, Mark R.; Peleg, K.; Sklansky, Jack

1993-01-01

Machine vision systems analyze image data to carry out automation tasks. Our interest is in machine vision systems that rely on models to achieve their designed task. When the model is interrogated from an a priori menu of questions, the model need not be complete. Instead, the machine vision system can use a partial model that contains a large amount of information in regions of interest and less information elsewhere. We propose an adaptive modeling scheme for machine vision, called task-focused modeling, which constructs a model having just sufficient detail to carry out the specified task. The model is detailed in regions of interest to the task and is less detailed elsewhere. This focusing effect saves time and reduces the computational effort expended by the machine vision system. We illustrate task-focused modeling by an example involving real-time micropropagation of plants in automated agriculture.

An intercomparison of carbon monoxide, nitric oxide, and hydroxyl measurement techniques - Overview of results

NASA Technical Reports Server (NTRS)

Hoell, J. M.; Gregory, G. L.; Carroll, M. A.; Mcfarland, M.; Ridley, B. A.; Davis, D. D.; Bradshaw, J.; Rodgers, M. O.; Torres, A. L.; Condon, E. P.

1984-01-01

Results from an intercomparison of methods to measure carbon monoxide (CO), nitric oxide (NO), and the hydroxyl radical (OH) are discussed. The intercomparison was conducted at Wallops Island, Virginia, in July 1983 and included a laser differential absorption and three grab sample/gas chromatograph methods for CO, a laser-induced fluorescence (LIF) and two chemiluminescence methods for NO, and two LIF methods and a radiocarbon tracer method for OH. The intercomparison was conducted as a field measurement program involving ambient measurements of CO (150-300 ppbv) and NO (10-180 pptv) from a common manifold with controlled injection of CO in incremental steps from 20 to 500 ppbv and NO in steps from 10 to 220 pptv. Only ambient measurements of OH were made. The agreement between the techniques was on the order of 14 percent for CO and 17 percent for NO. Hardware difficulties during the OH tests resulted in a data base with insufficient data and uncertanties too large to permit a meaningful intercomposition.

The Detection and Attribution Model Intercomparison Project (DAMIP v1.0)contribution to CMIP6

DOE PAGES

Gillett, Nathan P.; Shiogama, Hideo; Funke, Bernd; ...

2016-10-18

Detection and attribution (D&A) simulations were important components of CMIP5 and underpinned the climate change detection and attribution assessments of the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. The primary goals of the Detection and Attribution Model Intercomparison Project (DAMIP) are to facilitate improved estimation of the contributions of anthropogenic and natural forcing changes to observed global warming as well as to observed global and regional changes in other climate variables; to contribute to the estimation of how historical emissions have altered and are altering contemporary climate risk; and to facilitate improved observationally constrained projections of futuremore » climate change. D&A studies typically require unforced control simulations and historical simulations including all major anthropogenic and natural forcings. Such simulations will be carried out as part of the DECK and the CMIP6 historical simulation. In addition D&A studies require simulations covering the historical period driven by individual forcings or subsets of forcings only: such simulations are proposed here. Key novel features of the experimental design presented here include firstly new historical simulations with aerosols-only, stratospheric-ozone-only, CO2-only, solar-only, and volcanic-only forcing, facilitating an improved estimation of the climate response to individual forcing, secondly future single forcing experiments, allowing observationally constrained projections of future climate change, and thirdly an experimental design which allows models with and without coupled atmospheric chemistry to be compared on an equal footing.« less

The Detection and Attribution Model Intercomparison Project (DAMIP v1.0) contribution to CMIP6

NASA Astrophysics Data System (ADS)

Gillett, Nathan P.; Shiogama, Hideo; Funke, Bernd; Hegerl, Gabriele; Knutti, Reto; Matthes, Katja; Santer, Benjamin D.; Stone, Daithi; Tebaldi, Claudia

2016-10-01

Detection and attribution (D&A) simulations were important components of CMIP5 and underpinned the climate change detection and attribution assessments of the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. The primary goals of the Detection and Attribution Model Intercomparison Project (DAMIP) are to facilitate improved estimation of the contributions of anthropogenic and natural forcing changes to observed global warming as well as to observed global and regional changes in other climate variables; to contribute to the estimation of how historical emissions have altered and are altering contemporary climate risk; and to facilitate improved observationally constrained projections of future climate change. D&A studies typically require unforced control simulations and historical simulations including all major anthropogenic and natural forcings. Such simulations will be carried out as part of the DECK and the CMIP6 historical simulation. In addition D&A studies require simulations covering the historical period driven by individual forcings or subsets of forcings only: such simulations are proposed here. Key novel features of the experimental design presented here include firstly new historical simulations with aerosols-only, stratospheric-ozone-only, CO2-only, solar-only, and volcanic-only forcing, facilitating an improved estimation of the climate response to individual forcing, secondly future single forcing experiments, allowing observationally constrained projections of future climate change, and thirdly an experimental design which allows models with and without coupled atmospheric chemistry to be compared on an equal footing.

Select strengths and biases of models in representing the Arctic winter boundary layer over sea ice: the Larcform 1 single column model intercomparison

DOE PAGES

Pithan, Felix; Ackerman, Andrew; Angevine, Wayne M.; ...

2016-08-27

We struggle to represent lower tropospheric temperature and moisture profiles and surface fluxes in Artic winter using weather and climate models, partly because they lack or misrepresent physical processes that are specific to high latitudes. Observations have revealed two preferred states of the Arctic winter boundary layer. In the cloudy state, cloud liquid water limits surface radiative cooling, and temperature inversions are weak and elevated. In the radiatively clear state, strong surface radiative cooling leads to the build-up of surface-based temperature inversions. Many large-scale models lack the cloudy state, and some substantially underestimate inversion strength in the clear state. Themore » transformation from a moist to a cold dry air mass is modeled using an idealized Lagrangian perspective. The trajectory includes both boundary layer states, and the single-column experiment is the first Lagrangian Arctic air formation experiment (Larcform 1) organized within GEWEX GASS (Global atmospheric system studies). The intercomparison reproduces the typical biases of large-scale models: some models lack the cloudy state of the boundary layer due to the representation of mixed-phase microphysics or to the interaction between micro- and macrophysics. In some models, high emissivities of ice clouds or the lack of an insulating snow layer prevent the build-up of surface-based inversions in the radiatively clear state. Models substantially disagree on the amount of cloud liquid water in the cloudy state and on turbulent heat fluxes under clear skies. Finally, observations of air mass transformations including both boundary layer states would allow for a tighter constraint of model behavior.« less

Select strengths and biases of models in representing the Arctic winter boundary layer over sea ice: the Larcform 1 single column model intercomparison

PubMed Central

Pithan, Felix; Ackerman, Andrew; Angevine, Wayne M.; Hartung, Kerstin; Ickes, Luisa; Kelley, Maxwell; Medeiros, Brian; Sandu, Irina; Steeneveld, Gert-Jan; Sterk, HAM; Svensson, Gunilla; Vaillancourt, Paul A.; Zadra, Ayrton

2017-01-01

Weather and climate models struggle to represent lower tropospheric temperature and moisture profiles and surface fluxes in Arctic winter, partly because they lack or misrepresent physical processes that are specific to high latitudes. Observations have revealed two preferred states of the Arctic winter boundary layer. In the cloudy state, cloud liquid water limits surface radiative cooling, and temperature inversions are weak and elevated. In the radiatively clear state, strong surface radiative cooling leads to the build-up of surface-based temperature inversions. Many large-scale models lack the cloudy state, and some substantially underestimate inversion strength in the clear state. Here, the transformation from a moist to a cold dry air mass is modelled using an idealized Lagrangian perspective. The trajectory includes both boundary layer states, and the single-column experiment is the first Lagrangian Arctic air formation experiment (Larcform 1) organized within GEWEX GASS (Global atmospheric system studies). The intercomparison reproduces the typical biases of large-scale models: Some models lack the cloudy state of the boundary layer due to the representation of mixed-phase micro-physics or to the interaction between micro-and macrophysics. In some models, high emissivities of ice clouds or the lack of an insulating snow layer prevent the build-up of surface-based inversions in the radiatively clear state. Models substantially disagree on the amount of cloud liquid water in the cloudy state and on turbulent heat fluxes under clear skies. Observations of air mass transformations including both boundary layer states would allow for a tighter constraint of model behaviour. PMID:28966718

Select strengths and biases of models in representing the Arctic winter boundary layer over sea ice: the Larcform 1 single column model intercomparison

NASA Astrophysics Data System (ADS)

Pithan, Felix; Ackerman, Andrew; Angevine, Wayne M.; Hartung, Kerstin; Ickes, Luisa; Kelley, Maxwell; Medeiros, Brian; Sandu, Irina; Steeneveld, Gert-Jan; Sterk, H. A. M.; Svensson, Gunilla; Vaillancourt, Paul A.; Zadra, Ayrton

2016-09-01

Weather and climate models struggle to represent lower tropospheric temperature and moisture profiles and surface fluxes in Arctic winter, partly because they lack or misrepresent physical processes that are specific to high latitudes. Observations have revealed two preferred states of the Arctic winter boundary layer. In the cloudy state, cloud liquid water limits surface radiative cooling, and temperature inversions are weak and elevated. In the radiatively clear state, strong surface radiative cooling leads to the build-up of surface-based temperature inversions. Many large-scale models lack the cloudy state, and some substantially underestimate inversion strength in the clear state. Here, the transformation from a moist to a cold dry air mass is modeled using an idealized Lagrangian perspective. The trajectory includes both boundary layer states, and the single-column experiment is the first Lagrangian Arctic air formation experiment (Larcform 1) organized within GEWEX GASS (Global atmospheric system studies). The intercomparison reproduces the typical biases of large-scale models: some models lack the cloudy state of the boundary layer due to the representation of mixed-phase microphysics or to the interaction between micro- and macrophysics. In some models, high emissivities of ice clouds or the lack of an insulating snow layer prevent the build-up of surface-based inversions in the radiatively clear state. Models substantially disagree on the amount of cloud liquid water in the cloudy state and on turbulent heat fluxes under clear skies. Observations of air mass transformations including both boundary layer states would allow for a tighter constraint of model behavior.

Select strengths and biases of models in representing the Arctic winter boundary layer over sea ice: the Larcform 1 single column model intercomparison.

PubMed

Pithan, Felix; Ackerman, Andrew; Angevine, Wayne M; Hartung, Kerstin; Ickes, Luisa; Kelley, Maxwell; Medeiros, Brian; Sandu, Irina; Steeneveld, Gert-Jan; Sterk, Ham; Svensson, Gunilla; Vaillancourt, Paul A; Zadra, Ayrton

2016-09-01

Weather and climate models struggle to represent lower tropospheric temperature and moisture profiles and surface fluxes in Arctic winter, partly because they lack or misrepresent physical processes that are specific to high latitudes. Observations have revealed two preferred states of the Arctic winter boundary layer. In the cloudy state, cloud liquid water limits surface radiative cooling, and temperature inversions are weak and elevated. In the radiatively clear state, strong surface radiative cooling leads to the build-up of surface-based temperature inversions. Many large-scale models lack the cloudy state, and some substantially underestimate inversion strength in the clear state. Here, the transformation from a moist to a cold dry air mass is modelled using an idealized Lagrangian perspective. The trajectory includes both boundary layer states, and the single-column experiment is the first L agrangian Arc tic air form ation experiment (Larcform 1) organized within GEWEX GASS (Global atmospheric system studies). The intercomparison reproduces the typical biases of large-scale models: Some models lack the cloudy state of the boundary layer due to the representation of mixed-phase micro-physics or to the interaction between micro-and macrophysics. In some models, high emissivities of ice clouds or the lack of an insulating snow layer prevent the build-up of surface-based inversions in the radiatively clear state. Models substantially disagree on the amount of cloud liquid water in the cloudy state and on turbulent heat fluxes under clear skies. Observations of air mass transformations including both boundary layer states would allow for a tighter constraint of model behaviour.

Hydrological extremes and their agricultural impacts under a changing climate in Texas

NASA Astrophysics Data System (ADS)

Lee, K.; Gao, H.; Huang, M.; Sheffield, J.

2015-12-01

With the changing climate, hydrologic extremes (such as floods, droughts, and heat waves) are becoming more frequent and intensified. Such changes in extreme events are expected to affect agricultural production and food supplies. This study focuses on the State of Texas, which has the largest farm area and the highest value of livestock production in the U.S. The objectives are two-fold: First, to investigate the climatic impact on the occurrence of future hydrologic extreme events; and second, to evaluate the effects of the future extremes on agricultural production. The Variable Infiltration Capacity (VIC) model, which is calibrated and validated over Texas river basins during the historical period, is employed for this study. The VIC model is forced by the statistically downscaled climate projections from the Coupled Model Intercomparison Project Phase 5 (CMIP5) model ensembles at a spatial resolution of 1/8°. The CMIP5 projections contain four different scenarios in terms of Representative Concentration Pathway (RCP) (i.e. 2.6, 4.5, 6.0 and 8.5 w/m2). To carry out the analysis, VIC outputs forced by the CMIP5 model scenarios over three 30-year periods (1970-1999, 2020-2049 and 2070-2099) are first evaluated to identify how the frequency and the extent of the extreme events will be altered in the ten Texas major river basins. The results suggest that a significant increase in the number of extreme events will occur starting in the first half of the 21st century in Texas. Then, the effects of the predicted hydrologic extreme events on the irrigation water demand are investigated. It is found that future changes in water demand vary by crop type and location, with an east-to-west gradient. The results are expected to contribute to future water management and planning in Texas.

Ecohydrological modeling: the consideration of agricultural trees is essential in the Mediterranean area

NASA Astrophysics Data System (ADS)

Fader, Marianela; von Bloh, Werner; Shi, Sinan; Bondeau, Alberte; Cramer, Wolfgang

2016-04-01

In the Mediterranean region, climate and land use change are expected to impact on natural and agricultural ecosystems by warming, reduced rainfall and direct degradation of ecosystems. Human population growth and socioeconomic changes, notably on the Eastern and Southern shores, will require increases in food production and put additional pressure on agro-ecosystems and water resources. Coping with these challenges requires informed decisions that, in turn, require assessments by means of a comprehensive ecohydrological model. Here we present here the inclusion of 10 Mediterranean agricultural plants, mainly perennial crops, in an agro-ecosystem model (LPJmL, "Lund-Potsdam-Jena managed Land"): nut trees, date palms, citrus trees, orchards, olive trees, grapes, cotton, potatoes, vegetables and fodder grasses. The model was then successfully tested in three model outputs: agricultural yields, irrigation requirements and soil carbon density. A first application of the model indicates that, currently, agricultural trees consume in average more irrigation water per hectare than annual crops. Also, different crops show different magnitude of changes in net irrigation requirements due to climate change, being the increases most pronounced in agricultural trees. This is very relevant since the Mediterranean area as a whole might face an increase in gross irrigation requirements between 4% and 74% from climate change and population growth if irrigation systems and conveyance are not improved. Additionally, future water scarcity might pose further challenges to the agricultural sector: Algeria, Libya, Israel, Jordan, Lebanon, Syria, Serbia, Morocco, Tunisia and Spain have a high risk of not being able to sustainably meet future irrigation water requirements in some scenarios by the end of the century (1). The importance of including agricultural trees in the ecohydrological models is also shown in the results concerning soil organic carbon (SOC). Since in former model

Agriculture and Climate Change in Global Scenarios: Why Don't the Models Agree

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nelson, Gerald; van der Mensbrugghe, Dominique; Ahammad, Helal

Agriculture is unique among economic sectors in the nature of impacts from climate change. The production activity that transforms inputs into agricultural outputs makes direct use of weather inputs. Previous studies of the impacts of climate change on agriculture have reported substantial differences in outcomes of key variables such as prices, production, and trade. These divergent outcomes arise from differences in model inputs and model specification. The goal of this paper is to review climate change results and underlying determinants from a model comparison exercise with 10 of the leading global economic models that include significant representation of agriculture. Bymore » providing common productivity drivers that include climate change effects, differences in model outcomes are reduced. All models show higher prices in 2050 because of negative productivity shocks from climate change. The magnitude of the price increases, and the adaptation responses, differ significantly across the various models. Substantial differences exist in the structural parameters affecting demand, area, and yield, and should be a topic for future research.« less

Intercomparison Project on Parameterizations of Large-Scale Dynamics for Simulations of Tropical Convection

NASA Astrophysics Data System (ADS)

Sobel, A. H.; Wang, S.; Bellon, G.; Sessions, S. L.; Woolnough, S.

2013-12-01

Parameterizations of large-scale dynamics have been developed in the past decade for studying the interaction between tropical convection and large-scale dynamics, based on our physical understanding of the tropical atmosphere. A principal advantage of these methods is that they offer a pathway to attack the key question of what controls large-scale variations of tropical deep convection. These methods have been used with both single column models (SCMs) and cloud-resolving models (CRMs) to study the interaction of deep convection with several kinds of environmental forcings. While much has been learned from these efforts, different groups' efforts are somewhat hard to compare. Different models, different versions of the large-scale parameterization methods, and experimental designs that differ in other ways are used. It is not obvious which choices are consequential to the scientific conclusions drawn and which are not. The methods have matured to the point that there is value in an intercomparison project. In this context, the Global Atmospheric Systems Study - Weak Temperature Gradient (GASS-WTG) project was proposed at the Pan-GASS meeting in September 2012. The weak temperature gradient approximation is one method to parameterize large-scale dynamics, and is used in the project name for historical reasons and simplicity, but another method, the damped gravity wave (DGW) method, will also be used in the project. The goal of the GASS-WTG project is to develop community understanding of the parameterization methods currently in use. Their strengths, weaknesses, and functionality in models with different physics and numerics will be explored in detail, and their utility to improve our understanding of tropical weather and climate phenomena will be further evaluated. This presentation will introduce the intercomparison project, including background, goals, and overview of the proposed experimental design. Interested groups will be invited to join (it will not be

Evaluation and intercomparison of five major dry deposition ...

EPA Pesticide Factsheets

Dry deposition of various pollutants needs to be quantified in air quality monitoring networks as well as in chemical transport models. The inferential method is the most commonly used approach in which the dry deposition velocity (Vd) is empirically parameterized as a function of meteorological and biological conditions and pollutant species’ chemical properties. Earlier model intercomparison studies suggested that existing dry deposition algorithms produce quite different Vd values, e.g., up to a factor of 2 for monthly to annual average values for ozone, and sulfur and nitrogen species (Flechard et al., 2011; Schwede et al., 2011; Wu et al., 2011). To further evaluate model discrepancies using available flux data, this study compared the five dry deposition algorithms commonly used in North America and evaluated the models using five-year Vd(O3) and Vd(SO2) data generated from concentration gradient measurements above a temperate mixed forest in Canada. The five algorithms include: (1) the one used in the Canadian Air and Precipitation Monitoring Network (CAPMoN) and several Canadian air quality models based on Zhang et al. (2003), (2) the one used in the US Clean Air Status and Trends Network (CASTNET) based on Meyers et al. (1998), (3) the one used in the Community Multiscale Air Quality (CMAQ) model described in Pleim and Ran (2011), (4) the Noah land surface model coupled with a photosynthesis-based Gas Exchange Model (Noah-GEM) described in Wu et a

Host model uncertainties in aerosol radiative forcing estimates: results from the AeroCom prescribed intercomparison study

NASA Astrophysics Data System (ADS)

Stier, P.; Schutgens, N. A. J.; Bian, H.; Boucher, O.; Chin, M.; Ghan, S.; Huneeus, N.; Kinne, S.; Lin, G.; Myhre, G.; Penner, J. E.; Randles, C.; Samset, B.; Schulz, M.; Yu, H.; Zhou, C.

2012-09-01

Simulated multi-model "diversity" in aerosol direct radiative forcing estimates is often perceived as measure of aerosol uncertainty. However, current models used for aerosol radiative forcing calculations vary considerably in model components relevant for forcing calculations and the associated "host-model uncertainties" are generally convoluted with the actual aerosol uncertainty. In this AeroCom Prescribed intercomparison study we systematically isolate and quantify host model uncertainties on aerosol forcing experiments through prescription of identical aerosol radiative properties in nine participating models. Even with prescribed aerosol radiative properties, simulated clear-sky and all-sky aerosol radiative forcings show significant diversity. For a purely scattering case with globally constant optical depth of 0.2, the global-mean all-sky top-of-atmosphere radiative forcing is -4.51 W m-2 and the inter-model standard deviation is 0.70 W m-2, corresponding to a relative standard deviation of 15%. For a case with partially absorbing aerosol with an aerosol optical depth of 0.2 and single scattering albedo of 0.8, the forcing changes to 1.26 W m-2, and the standard deviation increases to 1.21 W m-2, corresponding to a significant relative standard deviation of 96%. However, the top-of-atmosphere forcing variability owing to absorption is low, with relative standard deviations of 9% clear-sky and 12% all-sky. Scaling the forcing standard deviation for a purely scattering case to match the sulfate radiative forcing in the AeroCom Direct Effect experiment, demonstrates that host model uncertainties could explain about half of the overall sulfate forcing diversity of 0.13 W m-2 in the AeroCom Direct Radiative Effect experiment. Host model errors in aerosol radiative forcing are largest in regions of uncertain host model components, such as stratocumulus cloud decks or areas with poorly constrained surface albedos, such as sea ice. Our results demonstrate that host

Host model uncertainties in aerosol radiative forcing estimates: results from the AeroCom Prescribed intercomparison study

NASA Astrophysics Data System (ADS)

Stier, P.; Schutgens, N. A. J.; Bellouin, N.; Bian, H.; Boucher, O.; Chin, M.; Ghan, S.; Huneeus, N.; Kinne, S.; Lin, G.; Ma, X.; Myhre, G.; Penner, J. E.; Randles, C. A.; Samset, B.; Schulz, M.; Takemura, T.; Yu, F.; Yu, H.; Zhou, C.

2013-03-01

Simulated multi-model "diversity" in aerosol direct radiative forcing estimates is often perceived as a measure of aerosol uncertainty. However, current models used for aerosol radiative forcing calculations vary considerably in model components relevant for forcing calculations and the associated "host-model uncertainties" are generally convoluted with the actual aerosol uncertainty. In this AeroCom Prescribed intercomparison study we systematically isolate and quantify host model uncertainties on aerosol forcing experiments through prescription of identical aerosol radiative properties in twelve participating models. Even with prescribed aerosol radiative properties, simulated clear-sky and all-sky aerosol radiative forcings show significant diversity. For a purely scattering case with globally constant optical depth of 0.2, the global-mean all-sky top-of-atmosphere radiative forcing is -4.47 Wm-2 and the inter-model standard deviation is 0.55 Wm-2, corresponding to a relative standard deviation of 12%. For a case with partially absorbing aerosol with an aerosol optical depth of 0.2 and single scattering albedo of 0.8, the forcing changes to 1.04 Wm-2, and the standard deviation increases to 1.01 W-2, corresponding to a significant relative standard deviation of 97%. However, the top-of-atmosphere forcing variability owing to absorption (subtracting the scattering case from the case with scattering and absorption) is low, with absolute (relative) standard deviations of 0.45 Wm-2 (8%) clear-sky and 0.62 Wm-2 (11%) all-sky. Scaling the forcing standard deviation for a purely scattering case to match the sulfate radiative forcing in the AeroCom Direct Effect experiment demonstrates that host model uncertainties could explain about 36% of the overall sulfate forcing diversity of 0.11 Wm-2 in the AeroCom Direct Radiative Effect experiment. Host model errors in aerosol radiative forcing are largest in regions of uncertain host model components, such as stratocumulus

The tropical rain belts with an annual cycle and a continent model intercomparison project: TRACMIP

DOE PAGES

Voigt, Aiko; Biasutti, Michela; Scheff, Jacob; ...

2016-11-16

This paper introduces the Tropical Rain belts with an Annual cycle and a Continent Model Intercomparison Project (TRACMIP). TRACMIP studies the dynamics of tropical rain belts and their response to past and future radiative forcings through simulations with 13 comprehensive and one simplified atmosphere models coupled to a slab ocean and driven by seasonally-varying insolation. Five idealized experiments, two with an aquaplanet setup and three with a setup with an idealized tropical continent, fill the space between prescribed-SST aquaplanet simulations and realistic simulations provided by CMIP5/6. The simulations reproduce key features of the present-day climate and expected future climate change,more » including an annual-mean intertropical convergence zone (ITCZ) that is located north of the equator and Hadley cells and eddy-driven jets that are similar to the present-day climate. Quadrupling CO 2 leads to a northward ITCZ shift and preferential warming in Northern high-latitudes. The simulations show interesting CO 2-induced changes in the seasonal excursion of the ITCZ and indicate a possible state-dependence of climate sensitivity. The inclusion of an idealized continent modulates both the control climate and the response to increased CO 2; for example it reduces the northward ITCZ shift associated with warming and, in some models, climate sensitivity. In response to eccentricity-driven seasonal insolation changes, seasonal changes in oceanic rainfall are best characterized as a meridional dipole, while seasonal continental rainfall changes tend to be symmetric about the equator. Finally, this survey illustrates TRACMIP’s potential to engender a deeper understanding of global and regional climate phenomena and to address pressing questions on past and future climate change.« less

The Tropical Rain Belts with an Annual Cycle and a Continent Model Intercomparison Project: TRACMIP

NASA Technical Reports Server (NTRS)

Voigt, Aiko; Biasutti, Michela; Scheff, Jacob; Bader, Juergen; Bordoni, Simona; Codron, Francis; Dixon, Ross D.; Jonas, Jeffrey; Kang, Sarah M.; Klingaman, Nicholas P.;

A socio-hydrologic model of coupled water-agriculture dynamics with emphasis on farm size.

NASA Astrophysics Data System (ADS)

Brugger, D. R.; Maneta, M. P.

2015-12-01

Agricultural land cover dynamics in the U.S. are dominated by two trends: 1) total agricultural land is decreasing and 2) average farm size is increasing. These trends have important implications for the future of water resources because 1) growing more food on less land is due in large part to increased groundwater withdrawal and 2) larger farms can better afford both more efficient irrigation and more groundwater access. However, these large-scale trends are due to individual farm operators responding to many factors including climate, economics, and policy. It is therefore difficult to incorporate the trends into watershed-scale hydrologic models. Traditional scenario-based approaches are valuable for many applications, but there is typically no feedback between the hydrologic model and the agricultural dynamics and so limited insight is gained into the how agriculture co-evolves with water resources. We present a socio-hydrologic model that couples simplified hydrologic and agricultural economic dynamics, accounting for many factors that depend on farm size such as irrigation efficiency and returns to scale. We introduce an "economic memory" (EM) state variable that is driven by agricultural revenue and affects whether farms are sold when land market values exceed expected returns from agriculture. The model uses a Generalized Mixture Model of Gaussians to approximate the distribution of farm sizes in a study area, effectively lumping farms into "small," "medium," and "large" groups that have independent parameterizations. We apply the model in a semi-arid watershed in the upper Columbia River Basin, calibrating to data on streamflow, total agricultural land cover, and farm size distribution. The model is used to investigate the sensitivity of the coupled system to various hydrologic and economic scenarios such as increasing market value of land, reduced surface water availability, and increased irrigation efficiency in small farms.

Dosimetry audits and intercomparisons in radiotherapy: A Malaysian profile

NASA Astrophysics Data System (ADS)

M. Noor, Noramaliza; Nisbet, A.; Hussein, M.; Chu S, Sarene; Kadni, T.; Abdullah, N.; Bradley, D. A.

2017-11-01

Quality audits and intercomparisons are important in ensuring control of processes in any system of endeavour. Present interest is in control of dosimetry in teletherapy, there being a need to assess the extent to which there is consistent radiation dose delivery to the patient. In this study we review significant factors that impact upon radiotherapy dosimetry, focusing upon the example situation of radiotherapy delivery in Malaysia, examining existing literature in support of such efforts. A number of recommendations are made to provide for increased quality assurance and control. In addition to this study, the first level of intercomparison audit i.e. measuring beam output under reference conditions at eight selected Malaysian radiotherapy centres is checked; use being made of 9 μm core diameter Ge-doped silica fibres (Ge-9 μm). The results of Malaysian Secondary Standard Dosimetry Laboratory (SSDL) participation in the IAEA/WHO TLD postal dose audit services during the period between 2011 and 2015 will also been discussed. In conclusion, following review of the development of dosimetry audits and the conduct of one such exercise in Malaysia, it is apparent that regular periodic radiotherapy audits and intercomparison programmes should be strongly supported and implemented worldwide. The programmes to-date demonstrate these to be a good indicator of errors and of consistency between centres. A total of ei+ght beams have been checked in eight Malaysian radiotherapy centres. One out of the eight beams checked produced an unacceptable deviation; this was found to be due to unfamiliarity with the irradiation procedures. Prior to a repeat measurement, the mean ratio of measured to quoted dose was found to be 0.99 with standard deviation of 3%. Subsequent to the repeat measurement, the mean distribution was 1.00, and the standard deviation was 1.3%.

Optical modeling of agricultural fields and rough-textured rock and mineral surfaces

NASA Technical Reports Server (NTRS)

Suits, G. H.; Vincent, R. K.; Horwitz, H. M.; Erickson, J. D.

1973-01-01

Review was made of past models for describing the reflectance and/or emittance properties of agricultural/forestry and geological targets in an effort to select the best theoretical models. An extension of the six parameter Allen-Gayle-Richardson model was chosen as the agricultural plant canopy model. The model is used to predict the bidirectional reflectance of a field crop from known laboratory spectra of crop components and approximate plant geometry. The selected geological model is based on Mie theory and radiative transfer equations, and will assess the effect of textural variations of the spectral emittance of natural rock surfaces.

Intercomparison of aerosol-cloud-precipitation interactions in stratiform orographic mixed-phase clouds

NASA Astrophysics Data System (ADS)

Muhlbauer, A.; Hashino, T.; Xue, L.; Teller, A.; Lohmann, U.; Rasmussen, R. M.; Geresdi, I.; Pan, Z.

2010-04-01

Anthropogenic aerosols serve as a source of both cloud condensation nuclei (CCN) and ice nuclei (IN) and affect microphysical properties of clouds. Increasing aerosol number concentrations is hypothesized to retard the cloud droplet collision/coalescence and the riming in mixed-phase clouds, thereby decreasing orographic precipitation. This study presents results from a model intercomparison of 2-D simulations of aerosol-cloud-precipitation interactions in stratiform orographic mixed-phase clouds. The sensitivity of orographic precipitation to changes in the aerosol number concentrations is analyzed and compared for various dynamical and thermodynamical situations. Furthermore, the sensitivities of microphysical processes such as collision/coalescence, aggregation and riming to changes in the aerosol number concentrations are evaluated and compared. The participating models are the Consortium for Small-Scale Modeling's (COSMO) model with bulk-microphysics, the Weather Research and Forecasting (WRF) model with bin-microphysics and the University of Wisconsin modeling system (UWNMS) with a spectral ice-habit prediction microphysics scheme. All models are operated on a cloud-resolving scale with 2 km horizontal grid spacing. The results of the model intercomparison suggest that the sensitivity of orographic precipitation to aerosol modifications varies greatly from case to case and from model to model. Neither a precipitation decrease nor a precipitation increase is found robustly in all simulations. Qualitative robust results can only be found for a subset of the simulations but even then quantitative agreement is scarce. Estimates of the second indirect aerosol effect on orographic precipitation are found to range from -19% to 0% depending on the simulated case and the model. Similarly, riming is shown to decrease in some cases and models whereas it increases in others which implies that a decrease in riming with increasing aerosol load is not a robust result

Intercomparison of aerosol-cloud-precipitation interactions in stratiform orographic mixed-phase clouds

NASA Astrophysics Data System (ADS)

Muhlbauer, A.; Hashino, T.; Xue, L.; Teller, A.; Lohmann, U.; Rasmussen, R. M.; Geresdi, I.; Pan, Z.

2010-09-01

Anthropogenic aerosols serve as a source of both cloud condensation nuclei (CCN) and ice nuclei (IN) and affect microphysical properties of clouds. Increasing aerosol number concentrations is hypothesized to retard the cloud droplet coalescence and the riming in mixed-phase clouds, thereby decreasing orographic precipitation. This study presents results from a model intercomparison of 2-D simulations of aerosol-cloud-precipitation interactions in stratiform orographic mixed-phase clouds. The sensitivity of orographic precipitation to changes in the aerosol number concentrations is analysed and compared for various dynamical and thermodynamical situations. Furthermore, the sensitivities of microphysical processes such as coalescence, aggregation, riming and diffusional growth to changes in the aerosol number concentrations are evaluated and compared. The participating numerical models are the model from the Consortium for Small-Scale Modeling (COSMO) with bulk microphysics, the Weather Research and Forecasting (WRF) model with bin microphysics and the University of Wisconsin modeling system (UWNMS) with a spectral ice habit prediction microphysics scheme. All models are operated on a cloud-resolving scale with 2 km horizontal grid spacing. The results of the model intercomparison suggest that the sensitivity of orographic precipitation to aerosol modifications varies greatly from case to case and from model to model. Neither a precipitation decrease nor a precipitation increase is found robustly in all simulations. Qualitative robust results can only be found for a subset of the simulations but even then quantitative agreement is scarce. Estimates of the aerosol effect on orographic precipitation are found to range from -19% to 0% depending on the simulated case and the model. Similarly, riming is shown to decrease in some cases and models whereas it increases in others, which implies that a decrease in riming with increasing aerosol load is not a robust result

ATHLI16: the ATHens Lidar Intercomparison campaign

NASA Astrophysics Data System (ADS)

Amodeo, Aldo; D'Amico, Giuseppe; Giunta, Aldo; Papagiannopoulos, Nikolaos; Papayannis, Alex; Argyrouli, Athina; Mylonaki, Maria; Tsaknakis, Georgios; Kokkalis, Panos; Soupiona, Ourania; Tzanis, Chris

2018-04-01

The results of the ATHLI16 (ATHens Lidar Intercomparison) campaign, held in Athens from 26/09 to 07/10 2016 are presented. The campaign was performed within the Lidar Calibration Centre activities (EU H2020 ACTRIS-2 project) to assess the performance of the EOLE lidar system (NTUA, Athens, Greece), operating within EARLINET, by comparing against the EARLINET reference lidar system MUSA (CNR-IMAA, Potenza, Italy). For both lidars only products retrieved by the EARLINET Single Calculus Chain have been compared.

The Second Cabauw Intercomparison of Nitrogen Dioxide Measuring Instruments (CINDI-2)

NASA Astrophysics Data System (ADS)

Van Roozendael, M.; Hendrick, F.; Apituley, A.; Kreher, K.; Friess, U.; Richter, A.; Wagner, T.; Fehr, T.

2017-12-01

For the validation of space borne UV-Vis observations of air quality gases, ground based remote-sensing instruments using the MAXDOAS technique are an excellent choice, since they rely on similar retrieval techniques as the observations from orbit. Over the last decade, MAXDOAS instruments of various designs (including PANDORA systems) have been deployed worldwide forming the basis for a global ground based reference network suitable for the validation of future satellite sensors, such as TROPOMI/Sentinel-5 precursor, GEMS, TEMPO, and Sentinel 4 and 5. To ensure proper traceability of these observations, assess their accuracy and progress towards harmonized data acquisition and delivery, a thorough intercomparison campaign known as the Second Cabauw Intercomparison of Nitrogen Dioxide Measuring Instruments (CINDI-2) was held in Cabauw, The Netherlands during the month of September 2016. About 35 MAXDOAS instruments operated by 25 different groups were deployed, together with systems providing key ancillary in-situ measurements of NO2 and aerosol optical properties, as well as vertical profiles of NO2 by lidar and sonde and vertical profiles of aerosol optical properties by Raman lidar. We provide an overview of the main outcome of the campaign, which included a formal semi-blind slant column intercomparison and a number of additional exercises aiming at assessing the potential of the MAXDOAS technique for retrieving vertically-resolved information on NO2, aerosol, HCHO, O3 and a few other more challenging species such as HONO and glyoxal.

Modeling the Heterogeneous Effects of GHG Mitigation Policies on Global Agriculture and Forestry

NASA Astrophysics Data System (ADS)

Golub, A.; Henderson, B.; Hertel, T. W.; Rose, S. K.; Sohngen, B.

2010-12-01

Agriculture and forestry are envisioned as potentially key sectors for climate change mitigation policy, yet the depth of analysis of mitigation options and their economic consequences remains remarkably shallow in comparison to that for industrial mitigation. Farming and land use change - much of it induced by agriculture -account for one-third of global greenhouse gas (GHG) emissions. Any serious attempt to curtail these emissions will involve changes in the way farming is conducted, as well as placing limits on agricultural expansion into areas currently under more carbon-intensive land cover. However, agriculture and forestry are extremely heterogeneous, both in the technology and intensity of production, as well as in the GHG emissions intensity of these activities. And these differences, in turn, give rise to significant changes in the distribution of agricultural production, trade and consumption in the wake of mitigation policies. This paper assesses such distributional impacts via a global economic analysis undertaken with a modified version of the GTAP model. The paper builds on a global general equilibrium GTAP-AEZ-GHG model (Golub et al., 2009). This is a unified modeling framework that links the agricultural, forestry, food processing and other sectors through land, and other factor markets and international trade, and incorporates different land-types, land uses and related CO2 and non-CO2 GHG emissions and sequestration. The economic data underlying this work is the global GTAP data base aggregated up to 19 regions and 29 sectors. The model incorporates mitigation cost curves for different regions and sectors based on information from the US-EPA. The forestry component of the model is calibrated to the results of the state of the art partial equilibrium global forestry model of Sohngen and Mendelson (2007). Forest carbon sequestration at both the extensive and intensive margins are modeled separately to better isolate land competition between

Coordinating AgMIP data and models across global and regional scales for 1.5°C and 2.0°C assessments

NASA Astrophysics Data System (ADS)

Rosenzweig, Cynthia; Ruane, Alex C.; Antle, John; Elliott, Joshua; Ashfaq, Muhammad; Chatta, Ashfaq Ahmad; Ewert, Frank; Folberth, Christian; Hathie, Ibrahima; Havlik, Petr; Hoogenboom, Gerrit; Lotze-Campen, Hermann; MacCarthy, Dilys S.; Mason-D'Croz, Daniel; Contreras, Erik Mencos; Müller, Christoph; Perez-Dominguez, Ignacio; Phillips, Meridel; Porter, Cheryl; Raymundo, Rubi M.; Sands, Ronald D.; Schleussner, Carl-Friedrich; Valdivia, Roberto O.; Valin, Hugo; Wiebe, Keith

2018-05-01

The Agricultural Model Intercomparison and Improvement Project (AgMIP) has developed novel methods for Coordinated Global and Regional Assessments (CGRA) of agriculture and food security in a changing world. The present study aims to perform a proof of concept of the CGRA to demonstrate advantages and challenges of the proposed framework. This effort responds to the request by the UN Framework Convention on Climate Change (UNFCCC) for the implications of limiting global temperature increases to 1.5°C and 2.0°C above pre-industrial conditions. The protocols for the 1.5°C/2.0°C assessment establish explicit and testable linkages across disciplines and scales, connecting outputs and inputs from the Shared Socio-economic Pathways (SSPs), Representative Agricultural Pathways (RAPs), Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI) and Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble scenarios, global gridded crop models, global agricultural economics models, site-based crop models and within-country regional economics models. The CGRA consistently links disciplines, models and scales in order to track the complex chain of climate impacts and identify key vulnerabilities, feedbacks and uncertainties in managing future risk. CGRA proof-of-concept results show that, at the global scale, there are mixed areas of positive and negative simulated wheat and maize yield changes, with declines in some breadbasket regions, at both 1.5°C and 2.0°C. Declines are especially evident in simulations that do not take into account direct CO2 effects on crops. These projected global yield changes mostly resulted in increases in prices and areas of wheat and maize in two global economics models. Regional simulations for 1.5°C and 2.0°C using site-based crop models had mixed results depending on the region and the crop. In conjunction with price changes from the global economics models, productivity declines in the Punjab, Pakistan, resulted in

Coordinating AgMIP data and models across global and regional scales for 1.5°C and 2.0°C assessments.

PubMed

Rosenzweig, Cynthia; Ruane, Alex C; Antle, John; Elliott, Joshua; Ashfaq, Muhammad; Chatta, Ashfaq Ahmad; Ewert, Frank; Folberth, Christian; Hathie, Ibrahima; Havlik, Petr; Hoogenboom, Gerrit; Lotze-Campen, Hermann; MacCarthy, Dilys S; Mason-D'Croz, Daniel; Contreras, Erik Mencos; Müller, Christoph; Perez-Dominguez, Ignacio; Phillips, Meridel; Porter, Cheryl; Raymundo, Rubi M; Sands, Ronald D; Schleussner, Carl-Friedrich; Valdivia, Roberto O; Valin, Hugo; Wiebe, Keith

2018-05-13

The Agricultural Model Intercomparison and Improvement Project (AgMIP) has developed novel methods for Coordinated Global and Regional Assessments (CGRA) of agriculture and food security in a changing world. The present study aims to perform a proof of concept of the CGRA to demonstrate advantages and challenges of the proposed framework. This effort responds to the request by the UN Framework Convention on Climate Change (UNFCCC) for the implications of limiting global temperature increases to 1.5°C and 2.0°C above pre-industrial conditions. The protocols for the 1.5°C/2.0°C assessment establish explicit and testable linkages across disciplines and scales, connecting outputs and inputs from the Shared Socio-economic Pathways (SSPs), Representative Agricultural Pathways (RAPs), Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI) and Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble scenarios, global gridded crop models, global agricultural economics models, site-based crop models and within-country regional economics models. The CGRA consistently links disciplines, models and scales in order to track the complex chain of climate impacts and identify key vulnerabilities, feedbacks and uncertainties in managing future risk. CGRA proof-of-concept results show that, at the global scale, there are mixed areas of positive and negative simulated wheat and maize yield changes, with declines in some breadbasket regions, at both 1.5°C and 2.0°C. Declines are especially evident in simulations that do not take into account direct CO 2 effects on crops. These projected global yield changes mostly resulted in increases in prices and areas of wheat and maize in two global economics models. Regional simulations for 1.5°C and 2.0°C using site-based crop models had mixed results depending on the region and the crop. In conjunction with price changes from the global economics models, productivity declines in the Punjab, Pakistan, resulted in

Ecosystem Services Provided by Agricultural Land as Modeled by Broad Scale Geospatial Analysis

NASA Astrophysics Data System (ADS)

Kokkinidis, Ioannis

Agricultural ecosystems provide multiple services including food and fiber provision, nutrient cycling, soil retention and water regulation. Objectives of the study were to identify and quantify a selection of ecosystem services provided by agricultural land, using existing geospatial tools and preferably free and open source data, such as the Virginia Land Use Evaluation System (VALUES), the North Carolina Realistic Yield Expectations (RYE) database, and the land cover datasets NLCD and CDL. Furthermore I sought to model tradeoffs between provisioning and other services. First I assessed the accuracy of agricultural land in NLCD and CDL over a four county area in eastern Virginia using cadastral parcels. I uncovered issues concerning the definition of agricultural land. The area and location of agriculture saw little change in the 19 years studied. Furthermore all datasets have significant errors of omission (11.3 to 95.1%) and commission (0 to 71.3%). Location of agriculture was used with spatial crop yield databases I created and combined with models I adapted to calculate baseline values for plant biomass, nutrient composition and requirements, land suitability for and potential production of biofuels and the economic impact of agriculture for the four counties. The study area was then broadened to cover 97 counties in eastern Virginia and North Carolina, investigating the potential for increased regional grain production through intensification and extensification of agriculture. Predicted yield from geospatial crop models was compared with produced yield from the NASS Survey of Agriculture. Area of most crops in CDL was similar to that in the Survey of Agriculture, but a yield gap is present for most years, partially due to weather, thus indicating potential for yield increase through intensification. Using simple criteria I quantified the potential to extend agriculture in high yield land in other uses and modeled the changes in erosion and runoff should

International Intercomparison of Regular Transmittance Scales

NASA Astrophysics Data System (ADS)

Eckerle, K. L.; Sutter, E.; Freeman, G. H. C.; Andor, G.; Fillinger, L.

1990-01-01

An intercomparison of the regular spectral transmittance scales of NIST, Gaithersburg, MD (USA); PTB, Braunschweig (FRG); NPL, Teddington, Middlesex (UK); and OMH, Budapest (H) was accomplished using three sets of neutral glass filters with transmittances ranging from approximately 0.92 to 0.001. The difference between the results from the reference spectrophotometers of the laboratories was generally smaller than the total uncertainty of the interchange. The relative total uncertainty ranges from 0.05% to 0.75% for transmittances from 0.92 to 0.001. The sample-induced error was large - contributing 40% or more of the total except in a few cases.

Numerical modeling of the agricultural-hydrologic system in Punjab, India

NASA Astrophysics Data System (ADS)

Nyblade, M.; Russo, T. A.; Zikatanov, L.; Zipp, K.

2017-12-01

The goal of food security for India's growing population is threatened by the decline in freshwater resources due to unsustainable water use for irrigation. The issue is acute in parts of Punjab, India, where small landholders produce a major quantity of India's food with declining groundwater resources. To further complicate this problem, other regions of the state are experiencing groundwater logging and salinization, and are reliant on canal systems for fresh water delivery. Due to the lack of water use records, groundwater consumption for this study is estimated with available data on crop yields, climate, and total canal water delivery. The hydrologic and agricultural systems are modeled using appropriate numerical methods and software. This is a state-wide hydrologic numerical model of Punjab that accounts for multiple aquifer layers, agricultural water demands, and interactions between the surface canal system and groundwater. To more accurately represent the drivers of agricultural production and therefore water use, we couple an economic crop optimization model with the hydrologic model. These tools will be used to assess and optimize crop choice scenarios based on farmer income, food production, and hydrologic system constraints. The results of these combined models can be used to further understand the hydrologic system response to government crop procurement policies and climate change, and to assess the effectiveness of possible water conservation solutions.

Research on prediction of agricultural machinery total power based on grey model optimized by genetic algorithm

NASA Astrophysics Data System (ADS)

Xie, Yan; Li, Mu; Zhou, Jin; Zheng, Chang-zheng

2009-07-01

Agricultural machinery total power is an important index to reflex and evaluate the level of agricultural mechanization. It is the power source of agricultural production, and is the main factors to enhance the comprehensive agricultural production capacity expand production scale and increase the income of the farmers. Its demand is affected by natural, economic, technological and social and other "grey" factors. Therefore, grey system theory can be used to analyze the development of agricultural machinery total power. A method based on genetic algorithm optimizing grey modeling process is introduced in this paper. This method makes full use of the advantages of the grey prediction model and characteristics of genetic algorithm to find global optimization. So the prediction model is more accurate. According to data from a province, the GM (1, 1) model for predicting agricultural machinery total power was given based on the grey system theories and genetic algorithm. The result indicates that the model can be used as agricultural machinery total power an effective tool for prediction.

A dynamic econometric model of agricultural wage determination in Bangladesh.

PubMed

Boyce, J K; Ravallion, M

1991-11-01

Economists applied data from 1949-1950 and 1980-1981 to a new dynamic model to examine the dynamics of determinants of agricultural wages in Bangladesh, particularly the effect of changes in relative prices of rice (the staple food) and productivity. Just a 20% rise in the price or rice was passed on in the agricultural wage rate within the current year. About 50% was passed on in the long run, however. Therefore an increase in the price of rice reduced the rice purchasing power of agricultural wages in the short and long term. In fact, the importance given to rice in the long run real wage rate was almost the same as the mean proportion of expenditure that an agricultural laborer in Bangladesh committed to rice and closely related food staples. Thus arise in the price of rice in comparison to other goods had limited effects on the long run real wage in terms of the bundle of goods typically consumed, but very adverse effects in the short run placing a high burden on the rural poor. On the other hand, the long run real wage rate fell considerably between the mid 1960s-early 1980s when overall agricultural productivity increased. The economists pointed out that this increased productivity may not have lowered long run real wage rates, but instead mitigating factors may have contributed to this fall. For example, population growth, rising landlessness, and insufficient economic growth in nonagricultural sectors resulted in a consistent growth in the labor supply. In conclusion, this new dynamic model showed that Bangladesh cannot depend only on agricultural growth to reduce the poverty of farmers.

Modeling applications for precision agriculture in the California Central Valley

NASA Astrophysics Data System (ADS)

Marklein, A. R.; Riley, W. J.; Grant, R. F.; Mezbahuddin, S.; Mekonnen, Z. A.; Liu, Y.; Ying, S.

2017-12-01

Drought in California has increased the motivation to develop precision agriculture, which uses observations to make site-specific management decisions throughout the growing season. In agricultural systems that are prone to drought, these efforts often focus on irrigation efficiency. Recent improvements in soil sensor technology allow the monitoring of plant and soil status in real-time, which can then inform models aimed at improving irrigation management. But even on farms with resources to deploy soil sensors across the landscape, leveraging that sensor data to design an efficient irrigation scheme remains a challenge. We conduct a modeling experiment aimed at simulating precision agriculture to address several questions: (1) how, when, and where does irrigation lead to optimal yield? and (2) What are the impacts of different precision irrigation schemes on yields, soil organic carbon (SOC), and total water use? We use the ecosys model to simulate precision agriculture in a conventional tomato-corn rotation in the California Central Valley with varying soil water content thresholds for irrigation and soil water sensor depths. This model is ideal for our question because it includes explicit process-based functions for the plant growth, plant water use, soil hydrology, and SOC, and has been tested extensively in agricultural ecosystems. Low irrigation thresholds allows the soil to become drier before irrigating compared to high irrigation thresholds; as such, we found that the high irrigation thresholds use more irrigation over the course of the season, have higher yields, and have lower water use efficiency. The irrigation threshold did not affect SOC. Yields and water use are highest at sensor depths of 0.5 to 0.15 m, but water use efficiency was also lowest at these depths. We found SOC to be significantly affected by sensor depth, with the highest SOC at the shallowest sensor depths. These results will help regulate irrigation water while maintaining yield

Simulated vs. empirical weather responsiveness of crop yields: US evidence and implications for the agricultural impacts of climate change

DOE PAGES

Mistry, Malcolm N.; Wing, Ian Sue; De Cian, Enrica

2017-07-10

Global gridded crop models (GGCMs) are the workhorse of assessments of the agricultural impacts of climate change. Yet the changes in crop yields projected by different models in response to the same meteorological forcing can differ substantially. Through an inter-method comparison, we provide a first glimpse into the origins and implications of this divergence—both among GGCMs and between GGCMs and historical observations. We examine yields of rainfed maize, wheat, and soybeans simulated by six GGCMs as part of the Inter-Sectoral Impact Model Intercomparison Project-Fast Track (ISIMIP-FT) exercise, comparing 1981–2004 hindcast yields over the coterminous United States (US) against US Departmentmore » of Agriculture (USDA) time series for about 1000 counties. Leveraging the empirical climate change impacts literature, we estimate reduced-form econometric models of crop yield responses to temperature and precipitation exposures for both GGCMs and observations. We find that up to 60% of the variance in both simulated and observed yields is attributable to weather variation. A majority of the GGCMs have difficulty reproducing the observed distribution of percentage yield anomalies, and exhibit aggregate responses that show yields to be more weather-sensitive than in the observational record over the predominant range of temperature and precipitation conditions. In conclusion, this disparity is largely attributable to heterogeneity in GGCMs' responses, as opposed to uncertainty in historical weather forcings, and is responsible for widely divergent impacts of climate on future crop yields.« less

Simulated vs. empirical weather responsiveness of crop yields: US evidence and implications for the agricultural impacts of climate change

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mistry, Malcolm N.; Wing, Ian Sue; De Cian, Enrica

Global gridded crop models (GGCMs) are the workhorse of assessments of the agricultural impacts of climate change. Yet the changes in crop yields projected by different models in response to the same meteorological forcing can differ substantially. Through an inter-method comparison, we provide a first glimpse into the origins and implications of this divergence—both among GGCMs and between GGCMs and historical observations. We examine yields of rainfed maize, wheat, and soybeans simulated by six GGCMs as part of the Inter-Sectoral Impact Model Intercomparison Project-Fast Track (ISIMIP-FT) exercise, comparing 1981–2004 hindcast yields over the coterminous United States (US) against US Departmentmore » of Agriculture (USDA) time series for about 1000 counties. Leveraging the empirical climate change impacts literature, we estimate reduced-form econometric models of crop yield responses to temperature and precipitation exposures for both GGCMs and observations. We find that up to 60% of the variance in both simulated and observed yields is attributable to weather variation. A majority of the GGCMs have difficulty reproducing the observed distribution of percentage yield anomalies, and exhibit aggregate responses that show yields to be more weather-sensitive than in the observational record over the predominant range of temperature and precipitation conditions. In conclusion, this disparity is largely attributable to heterogeneity in GGCMs' responses, as opposed to uncertainty in historical weather forcings, and is responsible for widely divergent impacts of climate on future crop yields.« less

Simulated vs. empirical weather responsiveness of crop yields: US evidence and implications for the agricultural impacts of climate change

NASA Astrophysics Data System (ADS)

Mistry, Malcolm N.; Wing, Ian Sue; De Cian, Enrica

2017-07-01

Global gridded crop models (GGCMs) are the workhorse of assessments of the agricultural impacts of climate change. Yet the changes in crop yields projected by different models in response to the same meteorological forcing can differ substantially. Through an inter-method comparison, we provide a first glimpse into the origins and implications of this divergence—both among GGCMs and between GGCMs and historical observations. We examine yields of rainfed maize, wheat, and soybeans simulated by six GGCMs as part of the Inter-Sectoral Impact Model Intercomparison Project-Fast Track (ISIMIP-FT) exercise, comparing 1981-2004 hindcast yields over the coterminous United States (US) against US Department of Agriculture (USDA) time series for about 1000 counties. Leveraging the empirical climate change impacts literature, we estimate reduced-form econometric models of crop yield responses to temperature and precipitation exposures for both GGCMs and observations. We find that up to 60% of the variance in both simulated and observed yields is attributable to weather variation. A majority of the GGCMs have difficulty reproducing the observed distribution of percentage yield anomalies, and exhibit aggregate responses that show yields to be more weather-sensitive than in the observational record over the predominant range of temperature and precipitation conditions. This disparity is largely attributable to heterogeneity in GGCMs’ responses, as opposed to uncertainty in historical weather forcings, and is responsible for widely divergent impacts of climate on future crop yields.

The Carbon-Land Model Intercomparison Project (C-LAMP): A Model-Data Comparison System for Evaluation of Coupled Biosphere-Atmosphere Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hoffman, Forrest M; Randerson, Jim; Thornton, Peter E

2009-01-01

The need to capture important climate feebacks in general circulation models (GCMs) has resulted in new efforts to include atmospheric chemistry and land and ocean biogeochemistry into the next generation of production climate models, now often referred to as Earth System Models (ESMs). While many terrestrial and ocean carbon models have been coupled to GCMs, recent work has shown that such models can yield a wide range of results, suggesting that a more rigorous set of offline and partially coupled experiments, along with detailed analyses of processes and comparisons with measurements, are warranted. The Carbon-Land Model Intercomparison Project (C-LAMP) providesmore » a simulation protocol and model performance metrics based upon comparisons against best-available satellite- and ground-based measurements (Hoffman et al., 2007). C-LAMP provides feedback to the modeling community regarding model improvements and to the measurement community by suggesting new observational campaigns. C-LAMP Experiment 1 consists of a set of uncoupled simulations of terrestrial carbon models specifically designed to examine the ability of the models to reproduce surface carbon and energy fluxes at multiple sites and to exhibit the influence of climate variability, prescribed atmospheric carbon dioxide (CO{sub 2}), nitrogen (N) deposition, and land cover change on projections of terrestrial carbon fluxes during the 20th century. Experiment 2 consists of partially coupled simulations of the terrestrial carbon model with an active atmosphere model exchanging energy and moisture fluxes. In all experiments, atmospheric CO{sub 2} follows the prescribed historical trajectory from C{sup 4}MIP. In Experiment 2, the atmosphere model is forced with prescribed sea surface temperatures (SSTs) and corresponding sea ice concentrations from the Hadley Centre; prescribed CO{sub 2} is radiatively active; and land, fossil fuel, and ocean CO{sub 2} fluxes are advected by the model. Both sets of

Model Course of Study for Agricultural Programs in Iowa. Preparing for the Future.

ERIC Educational Resources Information Center

Martin, Robert A.; And Others

Each section contained in this packet is necessary for designing an effective program of agriculture education. The curriculum guide that is developed from this model should include the same sections. The model includes: (1) community description; (2) school description; (3) goals and objectives of education in agriculture; (4) evaluation policy;…

A systematic intercomparison of regional flood frequency analysis models in a simulation framework

NASA Astrophysics Data System (ADS)

Ganora, Daniele; Laio, Francesco; Claps, Pierluigi

2015-04-01

Regional frequency analysis (RFA) is a well-established methodology to provide an estimate of the flood frequency curve (or other discharge-related variables), based on the fundamental concept of substituting temporal information at a site (no data or short time series) by exploiting observations at other sites (spatial information). Different RFA paradigms exist, depending on the way the information is transferred to the site of interest. Despite the wide use of such methodology, a systematic comparison between these paradigms has not been performed. The aim of this study is to provide a framework wherein carrying out the intercomparison: we thus synthetically generate data through Monte Carlo simulations for a number of (virtual) stations, following a GEV parent distribution; different scenarios can be created to represent different spatial heterogeneity patterns by manipulating the parameters of the parent distribution at each station (e.g. with a linear variation in space of the shape parameter of the GEV). A special case is the homogeneous scenario where each station record is sampled from the same parent distribution. For each scenario and each simulation, different regional models are applied to evaluate the 200-year growth factor at each station. Results are than compared to the exact growth factor of each station, which is known in our virtual world. Considered regional approaches include: (i) a single growth curve for the whole region; (ii) a multiple-region model based on cluster analysis which search for an adequate number of homogeneous subregions; (iii) a Region-of-Influence model which defines a homogeneous subregion for each site; (iv) a spatially-smooth estimation procedure based on linear regressions.. A further benchmark model is the at-site estimate based on the analysis of the local record. A comprehensive analysis of the results of the simulations shows that, if the scenario is homogeneous (no spatial variability), all the regional approaches

Potential Climate-driven Silvicultural and Agricultural Transformations in Siberia in the 21 Century

NASA Astrophysics Data System (ADS)

Tchebakova, N. M.; Parfenova, E. I.; Shvetsov, E.; Soja, A. J.

2017-12-01

Simulations of Siberian forests in a changing climate showed them to be changed in composition, decreased, and shifted northwards. Our goals were to evaluate the ecological consequences for the forests and agriculture in Siberia and to offer adaptive measures that may be undertaken to minimize negative consequences and maximize benefits from a rapidly changing environment in the socially important region of southern Siberia. We considered two strategies to estimate climate-change effects on potentially failing forests within an expanding forest-steppe ecotone. To support forestry, seed transfers from locations that are best suited to the genotypes in future climates may be applied to assist trees and forests in a changing climate. To support agriculture, in view of the growing world concerns on food safety, new farming lands may be established in a new forest-steppe ecotone with its favorable climatic and soil resources. We used our bioclimatic vegetation models of various levels: a forest type model to predict forest shifts and forest-failing lands, tree species range and their climatypes models to predict what tree species/climatype would be suitable and crop models to predict crops to introduce in potentially climate-disturbed areas in Siberia. Climate change data for the 2080s were calculated from the ensemble of 20 general circulation models of the Coupled Model Intercomparison Project phase 5 (CMIP5) and two scenarios to characterize the range of climate change: mild climate (RCP2.6 scenario) and sharp climate (RCP 8.5 scenario). By the 2080s, forest-steppe and steppe rather than forests would dominate up to half of Siberia in the warmer and dryer RCP 8.5 climate. Water stress tolerant and fire-resistant light-needled species Pinus sylvestris and Larix spp. would dominate the forest-steppe ecotone. Failing forests in a dryer climate may be maintained by moving and substituting proper climatypes from locations often hundreds of km away. Agriculture in Siberia

Agrochemical fate models applied in agricultural areas from Colombia

NASA Astrophysics Data System (ADS)

Garcia-Santos, Glenda; Yang, Jing; Andreoli, Romano; Binder, Claudia

2010-05-01

The misuse application of pesticides in mainly agricultural catchments can lead to severe problems for humans and environment. Especially in developing countries where there is often found overuse of agrochemicals and incipient or lack of water quality monitoring at local and regional levels, models are needed for decision making and hot spots identification. However, the complexity of the water cycle contrasts strongly with the scarce data availability, limiting the number of analysis, techniques, and models available to researchers. Therefore there is a strong need for model simplification able to appropriate model complexity and still represent the processes. We have developed a new model so-called Westpa-Pest to improve water quality management of an agricultural catchment located in the highlands of Colombia. Westpa-Pest is based on the fully distributed hydrologic model Wetspa and a fate pesticide module. We have applied a multi-criteria analysis for model selection under the conditions and data availability found in the region and compared with the new developed Westpa-Pest model. Furthermore, both models were empirically calibrated and validated. The following questions were addressed i) what are the strengths and weaknesses of the models?, ii) which are the most sensitive parameters of each model?, iii) what happens with uncertainties in soil parameters?, and iv) how sensitive are the transfer coefficients?

Agricultural climate impacts assessment for economic modeling and decision support

NASA Astrophysics Data System (ADS)

Thomson, A. M.; Izaurralde, R. C.; Beach, R.; Zhang, X.; Zhao, K.; Monier, E.

2013-12-01

A range of approaches can be used in the application of climate change projections to agricultural impacts assessment. Climate projections can be used directly to drive crop models, which in turn can be used to provide inputs for agricultural economic or integrated assessment models. These model applications, and the transfer of information between models, must be guided by the state of the science. But the methodology must also account for the specific needs of stakeholders and the intended use of model results beyond pure scientific inquiry, including meeting the requirements of agencies responsible for designing and assessing policies, programs, and regulations. Here we present methodology and results of two climate impacts studies that applied climate model projections from CMIP3 and from the EPA Climate Impacts and Risk Analysis (CIRA) project in a crop model (EPIC - Environmental Policy Indicator Climate) in order to generate estimates of changes in crop productivity for use in an agricultural economic model for the United States (FASOM - Forest and Agricultural Sector Optimization Model). The FASOM model is a forward-looking dynamic model of the US forest and agricultural sector used to assess market responses to changing productivity of alternative land uses. The first study, focused on climate change impacts on the UDSA crop insurance program, was designed to use available daily climate projections from the CMIP3 archive. The decision to focus on daily data for this application limited the climate model and time period selection significantly; however for the intended purpose of assessing impacts on crop insurance payments, consideration of extreme event frequency was critical for assessing periodic crop failures. In a second, coordinated impacts study designed to assess the relative difference in climate impacts under a no-mitigation policy and different future climate mitigation scenarios, the stakeholder specifically requested an assessment of a

First results of the CINDI-2 semi-blind MAX-DOAS intercomparison

NASA Astrophysics Data System (ADS)

Kreher, Karin; van Roozendael, Michel; Hendrick, Francois; Apituley, Arnoud; Friess, Udo; Lampel, Johannes; Piters, Ankie; Richter, Andreas; Wagner, Thomas; Cindi-2 Participants, All

2017-04-01

The second Cabauw Intercomparison campaign for Nitrogen Dioxide measuring Instruments (CINDI-2) took place at the Cabauw Experimental Site for Atmospheric Research (CESAR; Utrecht area, The Netherlands) from 25 August until 7 October 2016. The goals of this inter-comparison campaign are to support the creation of high-quality ground-based data sets (e.g. to provide reliable long-term time series for trend analysis and satellite data validation), to characterise and better understand the differences between a large number of MAX-DOAS and DOAS instruments and analysis methods, and to contribute to a harmonisation of the measurement settings and retrieval methods. During a time period of 17 days, from 12 to 28 September 2016, a formal semi-blind intercomparison was held following a detailed measurement protocol. The development of this protocol was based on the experience gained during the first CINDI campaign held in 2009 as well as more recent projects and campaigns such as the MADCAT campaign in Mainz, Germany, in 2013. Strong emphasis was put on the careful synchronisation of the measurement sequence and on exact alignment of the elevation angles using horizon scans and lamp measurements. In this presentation, we provide an overview and some highlights of the MAX-DOAS semi-blind intercomparison campaign. We will introduce the participating groups, their instruments and the measurement protocol details, and then summarize the campaign outcomes to date. The CINDI-2 data sets have been investigated using a range of diagnostics including comparisons of daily time series and relative differences between the data sets, regression analysis and correlation plots. The data products so far investigated are NO2 (nitrogen dioxide) in the UV and visible wavelength region, O4 (oxygen dimer) in the same two wavelength intervals, O3 (ozone) in the UV and visible wavelength region, HCHO (formaldehyde) and NO2 in an additional (smaller) wavelength range in the visible. The results

AgMIP Training in Multiple Crop Models and Tools

NASA Technical Reports Server (NTRS)

Boote, Kenneth J.; Porter, Cheryl H.; Hargreaves, John; Hoogenboom, Gerrit; Thornburn, Peter; Mutter, Carolyn

2015-01-01

The Agricultural Model Intercomparison and Improvement Project (AgMIP) has the goal of using multiple crop models to evaluate climate impacts on agricultural production and food security in developed and developing countries. There are several major limitations that must be overcome to achieve this goal, including the need to train AgMIP regional research team (RRT) crop modelers to use models other than the ones they are currently familiar with, plus the need to harmonize and interconvert the disparate input file formats used for the various models. Two activities were followed to address these shortcomings among AgMIP RRTs to enable them to use multiple models to evaluate climate impacts on crop production and food security. We designed and conducted courses in which participants trained on two different sets of crop models, with emphasis on the model of least experience. In a second activity, the AgMIP IT group created templates for inputting data on soils, management, weather, and crops into AgMIP harmonized databases, and developed translation tools for converting the harmonized data into files that are ready for multiple crop model simulations. The strategies for creating and conducting the multi-model course and developing entry and translation tools are reviewed in this chapter.

The Role of Cash Flow in Financial Early Warning of Agricultural Enterprises Based on Logistic Model

NASA Astrophysics Data System (ADS)

Sun, Fengru

2018-01-01

This paper chooses the agricultural listed companies as the research object, compares the financial situation of the enterprise and the theory of financial early warning, combines the financial status of the agricultural listed companies, selects the relevant cash flow indicators, discusses the application of the Logistic financial early warning model in the agricultural listed companies, Agricultural enterprises get better development. Research on financial early warning of agricultural listed companies will help the agricultural listed companies to predict the financial crisis. Financial early warning model is simple to establish, operational and strong, the use of financial early warning model, to help enterprises in the financial crisis before taking rapid and effective measures, which can avoid losses. Help enterprises to discover signs of deterioration of the financial situation in time to maintain the sustainable development of agricultural enterprises. In addition, through the financial early warning model, investors can correctly identify the financial situation of agricultural enterprises, and can evaluate the financial situation of agricultural enterprises and to help investors to invest in scientific and rational, beneficial to investors to analyze the safety of investment. But also help the relevant regulatory agencies to effectively monitor the market and promote the healthy and stable development of the market.

Towards a new generation of agricultural system data, models and knowledge products: Information and communication technology.

PubMed

Janssen, Sander J C; Porter, Cheryl H; Moore, Andrew D; Athanasiadis, Ioannis N; Foster, Ian; Jones, James W; Antle, John M

2017-07-01

Agricultural modeling has long suffered from fragmentation in model implementation. Many models are developed, there is much redundancy, models are often poorly coupled, model component re-use is rare, and it is frequently difficult to apply models to generate real solutions for the agricultural sector. To improve this situation, we argue that an open, self-sustained, and committed community is required to co-develop agricultural models and associated data and tools as a common resource. Such a community can benefit from recent developments in information and communications technology (ICT). We examine how such developments can be leveraged to design and implement the next generation of data, models, and decision support tools for agricultural production systems. Our objective is to assess relevant technologies for their maturity, expected development, and potential to benefit the agricultural modeling community. The technologies considered encompass methods for collaborative development and for involving stakeholders and users in development in a transdisciplinary manner. Our qualitative evaluation suggests that as an overall research challenge, the interoperability of data sources, modular granular open models, reference data sets for applications and specific user requirements analysis methodologies need to be addressed to allow agricultural modeling to enter in the big data era. This will enable much higher analytical capacities and the integrated use of new data sources. Overall agricultural systems modeling needs to rapidly adopt and absorb state-of-the-art data and ICT technologies with a focus on the needs of beneficiaries and on facilitating those who develop applications of their models. This adoption requires the widespread uptake of a set of best practices as standard operating procedures.

An intercomparison of aircraft instrumentation for tropospheric measurements of sulfur dioxide

NASA Technical Reports Server (NTRS)

Gregory, Gerald L.; Davis, Douglas D.; Beltz, Nobert; Bandy, Alan R.; Ferek, Ronald J.; Thornton, Donald C.

1993-01-01

As part of the NASA Tropospheric Chemistry Program, a series of field intercomparisons have been conducted to evaluate the state-of-the art for measuring key tropospheric species. One of the objectives of the third intercomparison campaign in this series, Chemical Instrumentation Test and Evaluation 3 (CITE 3), was to evaluate instrumentation for making reliable tropospheric aircraft measurements of sulfur dioxide, dimethyl sulfide, hydrogen sulfide, carbon disulfide, and carbonyl sulfide. This paper reports the results of the intercomparisons of five sulfur dioxide measurement methods ranging from filter techniques, in which samples collected in flight are returned to the laboratory for analyses (chemiluminescent or ion chromatographic), to near real-time, in-flight measurements via gas chromatographic, mass spectrometric, and chemiluminescent techniques. All techniques showed some tendency to track sizeable changes in ambient SO2 such as those associated with altitude changes. For SO2 mixing ratios in the range of 200 pptv to a few ppbv, agreement among the techniques varies from about 30% to several orders of magnitude, depending upon the pair of measurements intercompared. For SO2 mixing ratios less than 200 pptv, measurements from the techniques are uncorrelated. In general, observed differences in the measurement of standards do not account for the flight results. The CITE 3 results do not unambiguously identify one or more of the measurement techniques as providing valid or invalid SO2 measurements, but identify the range of 'potential' uncertainty in SO2 measurements reported by currently available instrumentation and as measured under realistic aircraft environments.

ISMIP6 - initMIP: Greenland ice sheet model initialisation experiments

NASA Astrophysics Data System (ADS)

Goelzer, Heiko; Nowicki, Sophie; Payne, Tony; Larour, Eric; Abe Ouchi, Ayako; Gregory, Jonathan; Lipscomb, William; Seroussi, Helene; Shepherd, Andrew; Edwards, Tamsin

2016-04-01

Earlier large-scale Greenland ice sheet sea-level projections e.g. those run during ice2sea and SeaRISE initiatives have shown that ice sheet initialisation can have a large effect on the projections and gives rise to important uncertainties. This intercomparison exercise (initMIP) aims at comparing, evaluating and improving the initialization techniques used in the ice sheet modeling community and to estimate the associated uncertainties. It is the first in a series of ice sheet model intercomparison activities within ISMIP6 (Ice Sheet Model Intercomparison Project for CMIP6). The experiments are conceived for the large-scale Greenland ice sheet and are designed to allow intercomparison between participating models of 1) the initial present-day state of the ice sheet and 2) the response in two schematic forward experiments. The latter experiments serve to evaluate the initialisation in terms of model drift (forward run without any forcing) and response to a large perturbation (prescribed surface mass balance anomaly). We present and discuss first results of the intercomparison and highlight important uncertainties with respect to projections of the Greenland ice sheet sea-level contribution.

An inexact risk management model for agricultural land-use planning under water shortage

NASA Astrophysics Data System (ADS)

Li, Wei; Feng, Changchun; Dai, Chao; Li, Yongping; Li, Chunhui; Liu, Ming

2016-09-01

Water resources availability has a significant impact on agricultural land-use planning, especially in a water shortage area such as North China. The random nature of available water resources and other uncertainties in an agricultural system present risk for land-use planning and may lead to undesirable decisions or potential economic loss. In this study, an inexact risk management model (IRM) was developed for supporting agricultural land-use planning and risk analysis under water shortage. The IRM model was formulated through incorporating a conditional value-at-risk (CVaR) constraint into an inexact two-stage stochastic programming (ITSP) framework, and could be used to control uncertainties expressed as not only probability distributions but also as discrete intervals. The measure of risk about the second-stage penalty cost was incorporated into the model so that the trade-off between system benefit and extreme expected loss could be analyzed. The developed model was applied to a case study in the Zhangweinan River Basin, a typical agricultural region facing serious water shortage in North China. Solutions of the IRM model showed that the obtained first-stage land-use target values could be used to reflect decision-makers' opinions on the long-term development plan. The confidence level α and maximum acceptable risk loss β could be used to reflect decisionmakers' preference towards system benefit and risk control. The results indicated that the IRM model was useful for reflecting the decision-makers' attitudes toward risk aversion and could help seek cost-effective agricultural land-use planning strategies under complex uncertainties.

Agricultural livelihoods in coastal Bangladesh under climate and environmental change--a model framework.

PubMed

Lázár, Attila N; Clarke, Derek; Adams, Helen; Akanda, Abdur Razzaque; Szabo, Sylvia; Nicholls, Robert J; Matthews, Zoe; Begum, Dilruba; Saleh, Abul Fazal M; Abedin, Md Anwarul; Payo, Andres; Streatfield, Peter Kim; Hutton, Craig; Mondal, M Shahjahan; Moslehuddin, Abu Zofar Md

2015-06-01

Coastal Bangladesh experiences significant poverty and hazards today and is highly vulnerable to climate and environmental change over the coming decades. Coastal stakeholders are demanding information to assist in the decision making processes, including simulation models to explore how different interventions, under different plausible future socio-economic and environmental scenarios, could alleviate environmental risks and promote development. Many existing simulation models neglect the complex interdependencies between the socio-economic and environmental system of coastal Bangladesh. Here an integrated approach has been proposed to develop a simulation model to support agriculture and poverty-based analysis and decision-making in coastal Bangladesh. In particular, we show how a simulation model of farmer's livelihoods at the household level can be achieved. An extended version of the FAO's CROPWAT agriculture model has been integrated with a downscaled regional demography model to simulate net agriculture profit. This is used together with a household income-expenses balance and a loans logical tree to simulate the evolution of food security indicators and poverty levels. Modelling identifies salinity and temperature stress as limiting factors to crop productivity and fertilisation due to atmospheric carbon dioxide concentrations as a reinforcing factor. The crop simulation results compare well with expected outcomes but also reveal some unexpected behaviours. For example, under current model assumptions, temperature is more important than salinity for crop production. The agriculture-based livelihood and poverty simulations highlight the critical significance of debt through informal and formal loans set at such levels as to persistently undermine the well-being of agriculture-dependent households. Simulations also indicate that progressive approaches to agriculture (i.e. diversification) might not provide the clear economic benefit from the perspective of

Calibration of an agricultural-hydrological model (RZWQM2) using surrogate global optimization

DOE PAGES

Xi, Maolong; Lu, Dan; Gui, Dongwei; ...

2016-11-27

Robust calibration of an agricultural-hydrological model is critical for simulating crop yield and water quality and making reasonable agricultural management. However, calibration of the agricultural-hydrological system models is challenging because of model complexity, the existence of strong parameter correlation, and significant computational requirements. Therefore, only a limited number of simulations can be allowed in any attempt to find a near-optimal solution within an affordable time, which greatly restricts the successful application of the model. The goal of this study is to locate the optimal solution of the Root Zone Water Quality Model (RZWQM2) given a limited simulation time, so asmore » to improve the model simulation and help make rational and effective agricultural-hydrological decisions. To this end, we propose a computationally efficient global optimization procedure using sparse-grid based surrogates. We first used advanced sparse grid (SG) interpolation to construct a surrogate system of the actual RZWQM2, and then we calibrate the surrogate model using the global optimization algorithm, Quantum-behaved Particle Swarm Optimization (QPSO). As the surrogate model is a polynomial with fast evaluation, it can be efficiently evaluated with a sufficiently large number of times during the optimization, which facilitates the global search. We calibrate seven model parameters against five years of yield, drain flow, and NO 3-N loss data from a subsurface-drained corn-soybean field in Iowa. Results indicate that an accurate surrogate model can be created for the RZWQM2 with a relatively small number of SG points (i.e., RZWQM2 runs). Compared to the conventional QPSO algorithm, our surrogate-based optimization method can achieve a smaller objective function value and better calibration performance using a fewer number of expensive RZWQM2 executions, which greatly improves computational efficiency.« less

Calibration of an agricultural-hydrological model (RZWQM2) using surrogate global optimization

NASA Astrophysics Data System (ADS)

Xi, Maolong; Lu, Dan; Gui, Dongwei; Qi, Zhiming; Zhang, Guannan

2017-01-01

Robust calibration of an agricultural-hydrological model is critical for simulating crop yield and water quality and making reasonable agricultural management. However, calibration of the agricultural-hydrological system models is challenging because of model complexity, the existence of strong parameter correlation, and significant computational requirements. Therefore, only a limited number of simulations can be allowed in any attempt to find a near-optimal solution within an affordable time, which greatly restricts the successful application of the model. The goal of this study is to locate the optimal solution of the Root Zone Water Quality Model (RZWQM2) given a limited simulation time, so as to improve the model simulation and help make rational and effective agricultural-hydrological decisions. To this end, we propose a computationally efficient global optimization procedure using sparse-grid based surrogates. We first used advanced sparse grid (SG) interpolation to construct a surrogate system of the actual RZWQM2, and then we calibrate the surrogate model using the global optimization algorithm, Quantum-behaved Particle Swarm Optimization (QPSO). As the surrogate model is a polynomial with fast evaluation, it can be efficiently evaluated with a sufficiently large number of times during the optimization, which facilitates the global search. We calibrate seven model parameters against five years of yield, drain flow, and NO3-N loss data from a subsurface-drained corn-soybean field in Iowa. Results indicate that an accurate surrogate model can be created for the RZWQM2 with a relatively small number of SG points (i.e., RZWQM2 runs). Compared to the conventional QPSO algorithm, our surrogate-based optimization method can achieve a smaller objective function value and better calibration performance using a fewer number of expensive RZWQM2 executions, which greatly improves computational efficiency.

Calibration of an agricultural-hydrological model (RZWQM2) using surrogate global optimization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xi, Maolong; Lu, Dan; Gui, Dongwei

Robust calibration of an agricultural-hydrological model is critical for simulating crop yield and water quality and making reasonable agricultural management. However, calibration of the agricultural-hydrological system models is challenging because of model complexity, the existence of strong parameter correlation, and significant computational requirements. Therefore, only a limited number of simulations can be allowed in any attempt to find a near-optimal solution within an affordable time, which greatly restricts the successful application of the model. The goal of this study is to locate the optimal solution of the Root Zone Water Quality Model (RZWQM2) given a limited simulation time, so asmore » to improve the model simulation and help make rational and effective agricultural-hydrological decisions. To this end, we propose a computationally efficient global optimization procedure using sparse-grid based surrogates. We first used advanced sparse grid (SG) interpolation to construct a surrogate system of the actual RZWQM2, and then we calibrate the surrogate model using the global optimization algorithm, Quantum-behaved Particle Swarm Optimization (QPSO). As the surrogate model is a polynomial with fast evaluation, it can be efficiently evaluated with a sufficiently large number of times during the optimization, which facilitates the global search. We calibrate seven model parameters against five years of yield, drain flow, and NO 3-N loss data from a subsurface-drained corn-soybean field in Iowa. Results indicate that an accurate surrogate model can be created for the RZWQM2 with a relatively small number of SG points (i.e., RZWQM2 runs). Compared to the conventional QPSO algorithm, our surrogate-based optimization method can achieve a smaller objective function value and better calibration performance using a fewer number of expensive RZWQM2 executions, which greatly improves computational efficiency.« less

Nitrate-Nitrogen Leaching and Modeling in Intensive Agriculture Farmland in China

PubMed Central

Xu, Ligang; Xu, Jin

2013-01-01

Protecting water resources from nitrate-nitrogen (NO3-N) contamination is an important public health concern and a major national environmental issue in China. Loss of NO3-N in soils due to leaching is not only one of the most important problems in agriculture farming, but is also the main factor causing nitrogen pollution in aquatic environments. Three typical intensive agriculture farmlands in Jiangyin City in China are selected as a case study for NO3-N leaching and modeling in the soil profile. In this study, the transport and fate of NO3-N within the soil profile and nitrate leaching to drains were analyzed by comparing field data with the simulation results of the LEACHM model. Comparisons between measured and simulated data indicated that the NO3-N concentrations in the soil and nitrate leaching to drains are controlled by the fertilizer practice, the initial conditions and the rainfall depth and distribution. Moreover, the study reveals that the LEACHM model gives a fair description of the NO3-N dynamics in the soil and subsurface drainage at the field scale. It can also be concluded that the model after calibration is a useful tool to optimize as a function of the combination “climate-crop-soil-bottom boundary condition” the nitrogen application strategy resulting for the environment in an acceptable level of nitrate leaching. The findings in this paper help to demonstrate the distribution and migration of nitrogen in intensive agriculture farmlands, as well as to explore the mechanism of groundwater contamination resulting from agricultural activities. PMID:23983629

1989 Intercomparison of radon progeny measurement methods and equipment in North America

DOE Office of Scientific and Technical Information (OSTI.GOV)

Scofield, P.; George, A.; Tu, Keng.

1990-03-01

At the 1989 {sup 222}Rn progeny intercomparison held at the Environmental Measurements Laboratory (EML), July 10--14, 1989, grab sampling and integrating/continuous {sup 222}Rn progeny methods were evaluated. Sixteen facilities participated in this intercomparison. Twelve facilities used {sup 222}Rn progeny grab sampling methods, and nine facilities used integrating/continuous instruments. Eighty-eight percent of the participants reported grab sample {sup 222}Rn progeny concentrations that were within 20% of the EML reference values. Good agreement between participant and EML grab-sample potential alpha energy concentrations (PAECs) was observed; 92% of the participants had PAECs within 20% of the EML values. For the integrating/continuous PAEC valuesmore » determined with integrating/continuous monitors, 89% of the participants were within 20% of the EML reference values. 9 refs., 3 figs., 4 tabs.« less

Climate-Agriculture-Modeling and Decision Tool for Disease (CAMDT-Disease) for seasonal climate forecast-based crop disease risk management in agriculture

NASA Astrophysics Data System (ADS)

Kim, K. H.; Lee, S.; Han, E.; Ines, A. V. M.

2017-12-01

Climate-Agriculture-Modeling and Decision Tool (CAMDT) is a decision support system (DSS) tool that aims to facilitate translations of probabilistic seasonal climate forecasts (SCF) to crop responses such as yield and water stress. Since CAMDT is a software framework connecting different models and algorithms with SCF information, it can be easily customized for different types of agriculture models. In this study, we replaced the DSSAT-CSM-Rice model originally incorporated in CAMDT with a generic epidemiological model, EPIRICE, to generate a seasonal pest outlook. The resulting CAMDT-Disease generates potential risks for selected fungal, viral, and bacterial diseases of rice over the next months by translating SCFs into agriculturally-relevant risk information. The integrated modeling procedure of CAMDT-Disease first disaggregates a given SCF using temporal downscaling methods (predictWTD or FResampler1), runs EPIRICE with the downscaled weather inputs, and finally visualizes the EPIRICE outputs as disease risk compared to that of the previous year and the 30-year-climatological average. In addition, the easy-to-use graphical user interface adopted from CAMDT allows users to simulate "what-if" scenarios of disease risks over different planting dates with given SCFs. Our future work includes the simulation of the effect of crop disease on yields through the disease simulation models with the DSSAT-CSM-Rice model, as disease remains one of the most critical yield-reducing factors in the field.

Evaluating the sensitivity of agricultural model performance to different climate inputs

PubMed Central

Glotter, Michael J.; Moyer, Elisabeth J.; Ruane, Alex C.; Elliott, Joshua W.

2017-01-01

Projections of future food production necessarily rely on models, which must themselves be validated through historical assessments comparing modeled to observed yields. Reliable historical validation requires both accurate agricultural models and accurate climate inputs. Problems with either may compromise the validation exercise. Previous studies have compared the effects of different climate inputs on agricultural projections, but either incompletely or without a ground truth of observed yields that would allow distinguishing errors due to climate inputs from those intrinsic to the crop model. This study is a systematic evaluation of the reliability of a widely-used crop model for simulating U.S. maize yields when driven by multiple observational data products. The parallelized Decision Support System for Agrotechnology Transfer (pDSSAT) is driven with climate inputs from multiple sources – reanalysis, reanalysis bias-corrected with observed climate, and a control dataset – and compared to observed historical yields. The simulations show that model output is more accurate when driven by any observation-based precipitation product than when driven by un-bias-corrected reanalysis. The simulations also suggest, in contrast to previous studies, that biased precipitation distribution is significant for yields only in arid regions. However, some issues persist for all choices of climate inputs: crop yields appear oversensitive to precipitation fluctuations but undersensitive to floods and heat waves. These results suggest that the most important issue for agricultural projections may be not climate inputs but structural limitations in the crop models themselves. PMID:29097985

Operational overview of NASA GTE/CITE 1 airborne instrument intercomparisons - Carbon monoxide, nitric oxide, and hydroxyl instrumentation. [Global Tropospheric Experiment/Chemical Instrumentation Test and Evaluation

NASA Technical Reports Server (NTRS)

Beck, Sherwin M.; Bendura, Richard J.; Mcdougal, David S.; Hoell, James M., Jr.; Gregory, Gerald L.; Sachse, Glen W.; Hill, Gerald F.; Curfman, Howard J., Jr.; Torres, Arnold L.; Condon, Estelle P.

1987-01-01

An overview of the airborne intercomparisons of CO, NO, and OH instrumentation is presented in this first paper of the series on the NASA Global Tropospheric Experiment/Chemical Instrumentation Test and Evaluation (GTE/CITE 1). This paper provides the reader with background information about several important characteristics of the project. These include the overall objectives and approach, the measurements taken, the intercomparison protocol, aircraft platform, profiles of each aircraft flight, and the participants. A synopsis of the overall results of the CO, NO, and OH instrument intercomparisons is also included. Companion papers discuss the detailed results of the CO and NO intercomparison tests as well as pertinent scientific findings.

A commentary on domestic animals as dual-purpose models that benefit agricultural and biomedical research.

PubMed

Ireland, J J; Roberts, R M; Palmer, G H; Bauman, D E; Bazer, F W

2008-10-01

Research on domestic animals (cattle, swine, sheep, goats, poultry, horses, and aquatic species) at land grant institutions is integral to improving the global competitiveness of US animal agriculture and to resolving complex animal and human diseases. However, dwindling federal and state budgets, years of stagnant funding from USDA for the Competitive State Research, Education, and Extension Service National Research Initiative (CSREES-NRI) Competitive Grants Program, significant reductions in farm animal species and in numbers at land grant institutions, and declining enrollment for graduate studies in animal science are diminishing the resources necessary to conduct research on domestic species. Consequently, recruitment of scientists who use such models to conduct research relevant to animal agriculture and biomedicine at land grant institutions is in jeopardy. Concerned stakeholders have addressed this critical problem by conducting workshops, holding a series of meetings with USDA and National Institutes of Health (NIH) officials, and developing a white paper to propose solutions to obstacles impeding the use of domestic species as dual-purpose animal models for high-priority problems common to agriculture and biomedicine. In addition to shortfalls in research support and human resources, overwhelming use of mouse models in biomedicine, lack of advocacy from university administrators, long-standing cultural barriers between agriculture and human medicine, inadequate grantsmanship by animal scientists, and a scarcity of key reagents and resources are major roadblocks to progress. Solutions will require a large financial enhancement of USDA's Competitive Grants Program, educational programs geared toward explaining how research using agricultural animals benefits both animal agriculture and human health, and the development of a new mind-set in land grant institutions that fosters greater cooperation among basic and applied researchers. Recruitment of

Assessment of malaria transmission changes in Africa, due to the climate impact of land use change using Coupled Model Intercomparison Project Phase 5 earth system models.

PubMed

Tompkins, Adrian M; Caporaso, Luca

2016-03-31

Using mathematical modelling tools, we assessed the potential for land use change (LUC) associated with the Intergovernmental Panel on Climate Change low- and high-end emission scenarios (RCP2.6 and RCP8.5) to impact malaria transmission in Africa. To drive a spatially explicit, dynamical malaria model, data from the four available earth system models (ESMs) that contributed to the LUC experiment of the Fifth Climate Model Intercomparison Project are used. Despite the limited size of the ESM ensemble, stark differences in the assessment of how LUC can impact climate are revealed. In three out of four ESMs, the impact of LUC on precipitation and temperature over the next century is limited, resulting in no significant change in malaria transmission. However, in one ESM, LUC leads to increases in precipitation under scenario RCP2.6, and increases in temperature in areas of land use conversion to farmland under both scenarios. The result is a more intense transmission and longer transmission seasons in the southeast of the continent, most notably in Mozambique and southern Tanzania. In contrast, warming associated with LUC in the Sahel region reduces risk in this model, as temperatures are already above the 25-30°C threshold at which transmission peaks. The differences between the ESMs emphasise the uncertainty in such assessments. It is also recalled that the modelling framework is unable to adequately represent local-scale changes in climate due to LUC, which some field studies indicate could be significant.

1983 international intercomparison of nuclear accident dosimetry systems at Oak Ridge National Laboratory

DOE Office of Scientific and Technical Information (OSTI.GOV)

Swaja, R.E.; Greene, R.T.; Sims, C.S.

1985-04-01

An international intercomparison of nuclear accident dosimetry systems was conducted during September 12-16, 1983, at Oak Ridge National Laboratory (ORNL) using the Health Physics Research Reactor operated in the pulse mode to simulate criticality accidents. This study marked the twentieth in a series of annual accident dosimetry intercomparisons conducted at ORNL. Participants from ten organizations attended this intercomparison and measured neutron and gamma doses at area monitoring stations and on phantoms for three different shield conditions. Results of this study indicate that foil activation techniques are the most popular and accurate method of determining accident-level neutron doses at area monitoringmore » stations. For personnel monitoring, foil activation, blood sodium activation, and thermoluminescent (TL) methods are all capable of providing accurate dose estimates in a variety of radiation fields. All participants in this study used TLD's to determine gamma doses with very good results on the average. Chemical dosemeters were also shown to be capable of yielding accurate estimates of total neutron plus gamma doses in a variety of radiation fields. While 83% of all neutron measurements satisfied regulatory standards relative to reference values, only 39% of all gamma results satisfied corresponding guidelines for gamma measurements. These results indicate that continued improvement in accident dosimetry evaluation and measurement techniques is needed.« less

The relationship between carbon dioxide and agriculture in Ghana: a comparison of VECM and ARDL model.

PubMed

Asumadu-Sarkodie, Samuel; Owusu, Phebe Asantewaa

2016-06-01

In this paper, the relationship between carbon dioxide and agriculture in Ghana was investigated by comparing a Vector Error Correction Model (VECM) and Autoregressive Distributed Lag (ARDL) Model. Ten study variables spanning from 1961 to 2012 were employed from the Food Agricultural Organization. Results from the study show that carbon dioxide emissions affect the percentage annual change of agricultural area, coarse grain production, cocoa bean production, fruit production, vegetable production, and the total livestock per hectare of the agricultural area. The vector error correction model and the autoregressive distributed lag model show evidence of a causal relationship between carbon dioxide emissions and agriculture; however, the relationship decreases periodically which may die over-time. All the endogenous variables except total primary vegetable production lead to carbon dioxide emissions, which may be due to poor agricultural practices to meet the growing food demand in Ghana. The autoregressive distributed lag bounds test shows evidence of a long-run equilibrium relationship between the percentage annual change of agricultural area, cocoa bean production, total livestock per hectare of agricultural area, total pulses production, total primary vegetable production, and carbon dioxide emissions. It is important to end hunger and ensure people have access to safe and nutritious food, especially the poor, orphans, pregnant women, and children under-5 years in order to reduce maternal and infant mortalities. Nevertheless, it is also important that the Government of Ghana institutes agricultural policies that focus on promoting a sustainable agriculture using environmental friendly agricultural practices. The study recommends an integration of climate change measures into Ghana's national strategies, policies and planning in order to strengthen the country's effort to achieving a sustainable environment.

The Urban Food-Water Nexus: Modeling Water Footprints of Urban Agriculture using CityCrop

NASA Astrophysics Data System (ADS)

Tooke, T. R.; Lathuilliere, M. J.; Coops, N. C.; Johnson, M. S.

2014-12-01

Urban agriculture provides a potential contribution towards more sustainable food production and mitigating some of the human impacts that accompany volatility in regional and global food supply. When considering the capacity of urban landscapes to produce food products, the impact of urban water demand required for food production in cities is often neglected. Urban agricultural studies also tend to be undertaken at broad spatial scales, overlooking the heterogeneity of urban form that exerts an extreme influence on the urban energy balance. As a result, urban planning and management practitioners require, but often do not have, spatially explicit and detailed information to support informed urban agricultural policy, especially as it relates to potential conflicts with sustainability goals targeting water-use. In this research we introduce a new model, CityCrop, a hybrid evapotranspiration-plant growth model that incorporates detailed digital representations of the urban surface and biophysical impacts of the built environment and urban trees to account for the daily variations in net surface radiation. The model enables very fine-scale (sub-meter) estimates of water footprints of potential urban agricultural production. Results of the model are demonstrated for an area in the City of Vancouver, Canada and compared to aspatial model estimates, demonstrating the unique considerations and sensitivities for current and future water footprints of urban agriculture and the implications for urban water planning and policy.

Preliminary Results of the first European Source Apportionment intercomparison for Receptor and Chemical Transport Models

NASA Astrophysics Data System (ADS)

Belis, Claudio A.; Pernigotti, Denise; Pirovano, Guido

2017-04-01

Source Apportionment (SA) is the identification of ambient air pollution sources and the quantification of their contribution to pollution levels. This task can be accomplished using different approaches: chemical transport models and receptor models. Receptor models are derived from measurements and therefore are considered as a reference for primary sources urban background levels. Chemical transport model have better estimation of the secondary pollutants (inorganic) and are capable to provide gridded results with high time resolution. Assessing the performance of SA model results is essential to guarantee reliable information on source contributions to be used for the reporting to the Commission and in the development of pollution abatement strategies. This is the first intercomparison ever designed to test both receptor oriented models (or receptor models) and chemical transport models (or source oriented models) using a comprehensive method based on model quality indicators and pre-established criteria. The target pollutant of this exercise, organised in the frame of FAIRMODE WG 3, is PM10. Both receptor models and chemical transport models present good performances when evaluated against their respective references. Both types of models demonstrate quite satisfactory capabilities to estimate the yearly source contributions while the estimation of the source contributions at the daily level (time series) is more critical. Chemical transport models showed a tendency to underestimate the contribution of some single sources when compared to receptor models. For receptor models the most critical source category is industry. This is probably due to the variety of single sources with different characteristics that belong to this category. Dust is the most problematic source for Chemical Transport Models, likely due to the poor information about this kind of source in the emission inventories, particularly concerning road dust re-suspension, and consequently the