Search Results
You are looking at 111 - 120 of 129 items for
- Author or Editor: J. Anderson x
- Refine by Access: All Content x
Abstract
Corn is the most widely grown crop in the Americas, with annual production in the United States of approximately 332 million metric tons. Improved climate forecasts, together with climate-related decision tools for corn producers based on these improved forecasts, could substantially reduce uncertainty and increase profitability for corn producers. The purpose of this paper is to acquaint climate information developers, climate information users, and climate researchers with an overview of weather conditions throughout the year that affect corn production as well as forecast content and timing needed by producers. The authors provide a graphic depicting the climate-informed decision cycle, which they call the climate forecast–decision cycle calendar for corn.
Abstract
Corn is the most widely grown crop in the Americas, with annual production in the United States of approximately 332 million metric tons. Improved climate forecasts, together with climate-related decision tools for corn producers based on these improved forecasts, could substantially reduce uncertainty and increase profitability for corn producers. The purpose of this paper is to acquaint climate information developers, climate information users, and climate researchers with an overview of weather conditions throughout the year that affect corn production as well as forecast content and timing needed by producers. The authors provide a graphic depicting the climate-informed decision cycle, which they call the climate forecast–decision cycle calendar for corn.
This document outlines a practical strategy for achieving an observationally based quantification of direct climate forcing by anthropogenic aerosols. The strategy involves a four-step program for shifting the current assumption-laden estimates to an increasingly empirical basis using satellite observations coordinated with suborbital remote and in situ measurements and with chemical transport models. Conceptually, the problem is framed as a need for complete global mapping of four parameters: clear-sky aerosol optical depth f f, radiative efficiency per unit optical depth δ, fine-mode fraction of optical depth f f, and the anthropogenic fraction of the fine mode f af . The first three parameters can be retrieved from satellites, but correlative, suborbital measurements are required for quantifying the aerosol properties that control E, for validating the retrieval of f f, and for partitioning fine-mode δ between natural and anthropogenic components. The satellite focus is on the “A-Train,” a constellation of six spacecraft that will fly in formation from about 2005 to 2008. Key satellite instruments for this report are the Moderate Resolution Imaging Spectroradiometer (MODIS) and Clouds and the Earth's Radiant Energy System (CERES) radiometers on Aqua, the Ozone Monitoring Instrument (OMI) radiometer on Aura, the Polarization and Directionality of Earth's Reflectances (POLDER) polarimeter on the Polarization and Anistropy of Reflectances for Atmospheric Sciences Coupled with Observations from a Lidar (PARASOL), and the Cloud and Aerosol Lider with Orthogonal Polarization (CALIOP) lidar on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). This strategy is offered as an initial framework—subject to improvement over time—for scientists around the world to participate in the A-Train opportunity. It is a specific implementation of the Progressive Aerosol Retrieval and Assimilation Global Observing Network (PARAGON) program, presented earlier in this journal, which identified the integration of diverse data as the central challenge to progress in quantifying global-scale aerosol effects. By designing a strategy around this need for integration, we develop recommendations for both satellite data interpretation and correlative suborbital activities that represent, in many respects, departures from current practice.
This document outlines a practical strategy for achieving an observationally based quantification of direct climate forcing by anthropogenic aerosols. The strategy involves a four-step program for shifting the current assumption-laden estimates to an increasingly empirical basis using satellite observations coordinated with suborbital remote and in situ measurements and with chemical transport models. Conceptually, the problem is framed as a need for complete global mapping of four parameters: clear-sky aerosol optical depth f f, radiative efficiency per unit optical depth δ, fine-mode fraction of optical depth f f, and the anthropogenic fraction of the fine mode f af . The first three parameters can be retrieved from satellites, but correlative, suborbital measurements are required for quantifying the aerosol properties that control E, for validating the retrieval of f f, and for partitioning fine-mode δ between natural and anthropogenic components. The satellite focus is on the “A-Train,” a constellation of six spacecraft that will fly in formation from about 2005 to 2008. Key satellite instruments for this report are the Moderate Resolution Imaging Spectroradiometer (MODIS) and Clouds and the Earth's Radiant Energy System (CERES) radiometers on Aqua, the Ozone Monitoring Instrument (OMI) radiometer on Aura, the Polarization and Directionality of Earth's Reflectances (POLDER) polarimeter on the Polarization and Anistropy of Reflectances for Atmospheric Sciences Coupled with Observations from a Lidar (PARASOL), and the Cloud and Aerosol Lider with Orthogonal Polarization (CALIOP) lidar on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). This strategy is offered as an initial framework—subject to improvement over time—for scientists around the world to participate in the A-Train opportunity. It is a specific implementation of the Progressive Aerosol Retrieval and Assimilation Global Observing Network (PARAGON) program, presented earlier in this journal, which identified the integration of diverse data as the central challenge to progress in quantifying global-scale aerosol effects. By designing a strategy around this need for integration, we develop recommendations for both satellite data interpretation and correlative suborbital activities that represent, in many respects, departures from current practice.
The Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission will provide a calibration laboratory in orbit for the purpose of accurately measuring and attributing climate change. CLARREO measurements establish new climate change benchmarks with high absolute radiometric accuracy and high statistical confidence across a wide range of essential climate variables. CLARREO's inherently high absolute accuracy will be verified and traceable on orbit to Système Internationale (SI) units. The benchmarks established by CLARREO will be critical for assessing changes in the Earth system and climate model predictive capabilities for decades into the future as society works to meet the challenge of optimizing strategies for mitigating and adapting to climate change. The CLARREO benchmarks are derived from measurements of the Earth's thermal infrared spectrum (5–50 μm), the spectrum of solar radiation reflected by the Earth and its atmosphere (320–2300 nm), and radio occultation refractivity from which accurate temperature profiles are derived. The mission has the ability to provide new spectral fingerprints of climate change, as well as to provide the first orbiting radiometer with accuracy sufficient to serve as the reference transfer standard for other space sensors, in essence serving as a “NIST [National Institute of Standards and Technology] in orbit.” CLARREO will greatly improve the accuracy and relevance of a wide range of space-borne instruments for decadal climate change. Finally, CLARREO has developed new metrics and methods for determining the accuracy requirements of climate observations for a wide range of climate variables and uncertainty sources. These methods should be useful for improving our understanding of observing requirements for most climate change observations.
The Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission will provide a calibration laboratory in orbit for the purpose of accurately measuring and attributing climate change. CLARREO measurements establish new climate change benchmarks with high absolute radiometric accuracy and high statistical confidence across a wide range of essential climate variables. CLARREO's inherently high absolute accuracy will be verified and traceable on orbit to Système Internationale (SI) units. The benchmarks established by CLARREO will be critical for assessing changes in the Earth system and climate model predictive capabilities for decades into the future as society works to meet the challenge of optimizing strategies for mitigating and adapting to climate change. The CLARREO benchmarks are derived from measurements of the Earth's thermal infrared spectrum (5–50 μm), the spectrum of solar radiation reflected by the Earth and its atmosphere (320–2300 nm), and radio occultation refractivity from which accurate temperature profiles are derived. The mission has the ability to provide new spectral fingerprints of climate change, as well as to provide the first orbiting radiometer with accuracy sufficient to serve as the reference transfer standard for other space sensors, in essence serving as a “NIST [National Institute of Standards and Technology] in orbit.” CLARREO will greatly improve the accuracy and relevance of a wide range of space-borne instruments for decadal climate change. Finally, CLARREO has developed new metrics and methods for determining the accuracy requirements of climate observations for a wide range of climate variables and uncertainty sources. These methods should be useful for improving our understanding of observing requirements for most climate change observations.
Abstract
Thirteen regional climate model (RCM) simulations of June–July 1993 were compared with each other and observations. Water vapor conservation and precipitation characteristics in each RCM were examined for a 10° × 10° subregion of the upper Mississippi River basin, containing the region of maximum 60-day accumulated precipitation in all RCMs and station reports.
All RCMs produced positive precipitation minus evapotranspiration (P − E > 0), though most RCMs produced P − E below the observed range. RCM recycling ratios were within the range estimated from observations. No evidence of common errors of E was found. In contrast, common dry bias of P was found in the simulations.
Daily cycles of terms in the water vapor conservation equation were qualitatively similar in most RCMs. Nocturnal maximums of P and C (convergence) occurred in 9 of 13 RCMs, consistent with observations. Three of the four driest simulations failed to couple P and C overnight, producing afternoon maximum P. Further, dry simulations tended to produce a larger fraction of their 60-day accumulated precipitation from low 3-h totals.
In station reports, accumulation from high (low) 3-h totals had a nocturnal (early morning) maximum. This time lag occurred, in part, because many mesoscale convective systems had reached peak intensity overnight and had declined in intensity by early morning. None of the RCMs contained such a time lag. It is recommended that short-period experiments be performed to examine the ability of RCMs to simulate mesoscale convective systems prior to generating long-period simulations for hydroclimatology.
Abstract
Thirteen regional climate model (RCM) simulations of June–July 1993 were compared with each other and observations. Water vapor conservation and precipitation characteristics in each RCM were examined for a 10° × 10° subregion of the upper Mississippi River basin, containing the region of maximum 60-day accumulated precipitation in all RCMs and station reports.
All RCMs produced positive precipitation minus evapotranspiration (P − E > 0), though most RCMs produced P − E below the observed range. RCM recycling ratios were within the range estimated from observations. No evidence of common errors of E was found. In contrast, common dry bias of P was found in the simulations.
Daily cycles of terms in the water vapor conservation equation were qualitatively similar in most RCMs. Nocturnal maximums of P and C (convergence) occurred in 9 of 13 RCMs, consistent with observations. Three of the four driest simulations failed to couple P and C overnight, producing afternoon maximum P. Further, dry simulations tended to produce a larger fraction of their 60-day accumulated precipitation from low 3-h totals.
In station reports, accumulation from high (low) 3-h totals had a nocturnal (early morning) maximum. This time lag occurred, in part, because many mesoscale convective systems had reached peak intensity overnight and had declined in intensity by early morning. None of the RCMs contained such a time lag. It is recommended that short-period experiments be performed to examine the ability of RCMs to simulate mesoscale convective systems prior to generating long-period simulations for hydroclimatology.
Aerosols exert myriad influences on the earth's environment and climate, and on human health. The complexity of aerosol-related processes requires that information gathered to improve our understanding of climate change must originate from multiple sources, and that effective strategies for data integration need to be established. While a vast array of observed and modeled data are becoming available, the aerosol research community currently lacks the necessary tools and infrastructure to reap maximum scientific benefit from these data. Spatial and temporal sampling differences among a diverse set of sensors, nonuniform data qualities, aerosol mesoscale variabilities, and difficulties in separating cloud effects are some of the challenges that need to be addressed. Maximizing the longterm benefit from these data also requires maintaining consistently well-understood accuracies as measurement approaches evolve and improve. Achieving a comprehensive understanding of how aerosol physical, chemical, and radiative processes impact the earth system can be achieved only through a multidisciplinary, interagency, and international initiative capable of dealing with these issues. A systematic approach, capitalizing on modern measurement and modeling techniques, geospatial statistics methodologies, and high-performance information technologies, can provide the necessary machinery to support this objective. We outline a framework for integrating and interpreting observations and models, and establishing an accurate, consistent, and cohesive long-term record, following a strategy whereby information and tools of progressively greater sophistication are incorporated as problems of increasing complexity are tackled. This concept is named the Progressive Aerosol Retrieval and Assimilation Global Observing Network (PARAGON). To encompass the breadth of the effort required, we present a set of recommendations dealing with data interoperability; measurement and model integration; multisensor synergy; data summarization and mining; model evaluation; calibration and validation; augmentation of surface and in situ measurements; advances in passive and active remote sensing; and design of satellite missions. Without an initiative of this nature, the scientific and policy communities will continue to struggle with understanding the quantitative impact of complex aerosol processes on regional and global climate change and air quality.
Aerosols exert myriad influences on the earth's environment and climate, and on human health. The complexity of aerosol-related processes requires that information gathered to improve our understanding of climate change must originate from multiple sources, and that effective strategies for data integration need to be established. While a vast array of observed and modeled data are becoming available, the aerosol research community currently lacks the necessary tools and infrastructure to reap maximum scientific benefit from these data. Spatial and temporal sampling differences among a diverse set of sensors, nonuniform data qualities, aerosol mesoscale variabilities, and difficulties in separating cloud effects are some of the challenges that need to be addressed. Maximizing the longterm benefit from these data also requires maintaining consistently well-understood accuracies as measurement approaches evolve and improve. Achieving a comprehensive understanding of how aerosol physical, chemical, and radiative processes impact the earth system can be achieved only through a multidisciplinary, interagency, and international initiative capable of dealing with these issues. A systematic approach, capitalizing on modern measurement and modeling techniques, geospatial statistics methodologies, and high-performance information technologies, can provide the necessary machinery to support this objective. We outline a framework for integrating and interpreting observations and models, and establishing an accurate, consistent, and cohesive long-term record, following a strategy whereby information and tools of progressively greater sophistication are incorporated as problems of increasing complexity are tackled. This concept is named the Progressive Aerosol Retrieval and Assimilation Global Observing Network (PARAGON). To encompass the breadth of the effort required, we present a set of recommendations dealing with data interoperability; measurement and model integration; multisensor synergy; data summarization and mining; model evaluation; calibration and validation; augmentation of surface and in situ measurements; advances in passive and active remote sensing; and design of satellite missions. Without an initiative of this nature, the scientific and policy communities will continue to struggle with understanding the quantitative impact of complex aerosol processes on regional and global climate change and air quality.
Abstract
During Northern Hemisphere winters, the West Coast of North America is battered by extratropical storms. The impact of these storms is of paramount concern to California, where aging water supply and flood protection infrastructures are challenged by increased standards for urban flood protection, an unusually variable weather regime, and projections of climate change. Additionally, there are inherent conflicts between releasing water to provide flood protection and storing water to meet requirements for the water supply, water quality, hydropower generation, water temperature and flow for at-risk species, and recreation. To improve reservoir management and meet the increasing demands on water, improved forecasts of precipitation, especially during extreme events, are required. Here, the authors describe how California is addressing their most important and costliest environmental issue—water management—in part, by installing a state-of-the-art observing system to better track the area’s most severe wintertime storms.
Abstract
During Northern Hemisphere winters, the West Coast of North America is battered by extratropical storms. The impact of these storms is of paramount concern to California, where aging water supply and flood protection infrastructures are challenged by increased standards for urban flood protection, an unusually variable weather regime, and projections of climate change. Additionally, there are inherent conflicts between releasing water to provide flood protection and storing water to meet requirements for the water supply, water quality, hydropower generation, water temperature and flow for at-risk species, and recreation. To improve reservoir management and meet the increasing demands on water, improved forecasts of precipitation, especially during extreme events, are required. Here, the authors describe how California is addressing their most important and costliest environmental issue—water management—in part, by installing a state-of-the-art observing system to better track the area’s most severe wintertime storms.
In 2006, NASA led a field campaign to investigate the factors that control the fate of African easterly waves (AEWs) moving westward into the tropical Atlantic Ocean. Aircraft and surface-based equipment were based on Cape Verde's islands, helping to fill some of the data void between Africa and the Caribbean. Taking advantage of the international African Monsoon Multidisciplinary Analysis (AMMA) program over the continent, the NASA-AMMA (NAMMA) program used enhanced upstream data, whereas NOAA aircraft farther west in the Atlantic studied several of the storms downstream. Seven AEWs were studied during AMMA, with at least two becoming tropical cyclones. Some of the waves that did not develop while being sampled near Cape Verde likely intensified in the central Atlantic instead. NAMMA observations were able to distinguish between the large-scale wave structure and the smaller-scale vorticity maxima that often form within the waves. A special complication of the east Atlantic environment is the Saharan air layer (SAL), which frequently accompanies the AEWs and may introduce dry air and heavy aerosol loading into the convective storm systems in the AEWs. One of the main achievements of NAMMA was the acquisition of a database of remote sensing and in situ observations of the properties of the SAL, enabling dynamic models and satellite retrieval algorithms to be evaluated against high-quality real data. Ongoing research with this database will help determine how the SAL influences cloud microphysics and perhaps also tropical cyclogenesis, as well as the more general question of recognizing the properties of small-scale vorticity maxima within tropical waves that are more likely to become tropical cyclones.
In 2006, NASA led a field campaign to investigate the factors that control the fate of African easterly waves (AEWs) moving westward into the tropical Atlantic Ocean. Aircraft and surface-based equipment were based on Cape Verde's islands, helping to fill some of the data void between Africa and the Caribbean. Taking advantage of the international African Monsoon Multidisciplinary Analysis (AMMA) program over the continent, the NASA-AMMA (NAMMA) program used enhanced upstream data, whereas NOAA aircraft farther west in the Atlantic studied several of the storms downstream. Seven AEWs were studied during AMMA, with at least two becoming tropical cyclones. Some of the waves that did not develop while being sampled near Cape Verde likely intensified in the central Atlantic instead. NAMMA observations were able to distinguish between the large-scale wave structure and the smaller-scale vorticity maxima that often form within the waves. A special complication of the east Atlantic environment is the Saharan air layer (SAL), which frequently accompanies the AEWs and may introduce dry air and heavy aerosol loading into the convective storm systems in the AEWs. One of the main achievements of NAMMA was the acquisition of a database of remote sensing and in situ observations of the properties of the SAL, enabling dynamic models and satellite retrieval algorithms to be evaluated against high-quality real data. Ongoing research with this database will help determine how the SAL influences cloud microphysics and perhaps also tropical cyclogenesis, as well as the more general question of recognizing the properties of small-scale vorticity maxima within tropical waves that are more likely to become tropical cyclones.
A significant fraction of Earth consists of mountainous terrain. However, the question of how to monitor the surface–atmosphere carbon exchange over complex terrain has not been fully explored. This article reports on studies by a team of investigators from U.S. universities and research institutes who carried out a multiscale and multidisciplinary field and modeling investigation of the CO2 exchange between ecosystems and the atmosphere and of CO2 transport over complex mountainous terrain in the Rocky Mountain region of Colorado. The goals of the field campaign, which included ground and airborne in situ and remote-sensing measurements, were to characterize unique features of the local CO2 exchange and to find effective methods to measure regional ecosystem–atmosphere CO2 exchange over complex terrain. The modeling effort included atmospheric and ecological numerical modeling and data assimilation to investigate regional CO2 transport and biological processes involved in ecosystem–atmosphere carbon exchange. In this report, we document our approaches, demonstrate some preliminary results, and discuss principal patterns and conclusions concerning ecosystem–atmosphere carbon exchange over complex terrain and its relation to past studies that have considered these processes over much simpler terrain.
A significant fraction of Earth consists of mountainous terrain. However, the question of how to monitor the surface–atmosphere carbon exchange over complex terrain has not been fully explored. This article reports on studies by a team of investigators from U.S. universities and research institutes who carried out a multiscale and multidisciplinary field and modeling investigation of the CO2 exchange between ecosystems and the atmosphere and of CO2 transport over complex mountainous terrain in the Rocky Mountain region of Colorado. The goals of the field campaign, which included ground and airborne in situ and remote-sensing measurements, were to characterize unique features of the local CO2 exchange and to find effective methods to measure regional ecosystem–atmosphere CO2 exchange over complex terrain. The modeling effort included atmospheric and ecological numerical modeling and data assimilation to investigate regional CO2 transport and biological processes involved in ecosystem–atmosphere carbon exchange. In this report, we document our approaches, demonstrate some preliminary results, and discuss principal patterns and conclusions concerning ecosystem–atmosphere carbon exchange over complex terrain and its relation to past studies that have considered these processes over much simpler terrain.
Shallow, maritime cumuli are ubiquitous over much of the tropical oceans, and characterizing their properties is important to understanding weather and climate. The Rain in Cumulus over the Ocean (RICO) field campaign, which took place during November 2004–January 2005 in the trades over the western Atlantic, emphasized measurements of processes related to the formation of rain in shallow cumuli, and how rain subsequently modifies the structure and ensemble statistics of trade wind clouds. Eight weeks of nearly continuous S-band polarimetric radar sampling, 57 flights from three heavily instrumented research aircraft, and a suite of ground- and ship-based instrumentation provided data on trade wind clouds with unprecedented resolution. Observational strategies employed during RICO capitalized on the advances in remote sensing and other instrumentation to provide insight into processes that span a range of scales and that lie at the heart of questions relating to the cause and effects of rain from shallow maritime cumuli.
Shallow, maritime cumuli are ubiquitous over much of the tropical oceans, and characterizing their properties is important to understanding weather and climate. The Rain in Cumulus over the Ocean (RICO) field campaign, which took place during November 2004–January 2005 in the trades over the western Atlantic, emphasized measurements of processes related to the formation of rain in shallow cumuli, and how rain subsequently modifies the structure and ensemble statistics of trade wind clouds. Eight weeks of nearly continuous S-band polarimetric radar sampling, 57 flights from three heavily instrumented research aircraft, and a suite of ground- and ship-based instrumentation provided data on trade wind clouds with unprecedented resolution. Observational strategies employed during RICO capitalized on the advances in remote sensing and other instrumentation to provide insight into processes that span a range of scales and that lie at the heart of questions relating to the cause and effects of rain from shallow maritime cumuli.
