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At least 1,315 records · Page 73

The Description and Validation of a Computationally-Efficient CH4-CO-OH (ECCOHv1.01) Chemistry Module for 3D Model Applications

We present the Efficient CH4-CO-OH (ECCOH) chemistry module that allows for the simulation of the methane, carbon monoxide, and hydroxyl radical (CH4-CO- OH) system, within a chemistry climate model, carbon cycle model, or Earth system model. The computational efficiency of the module allows many multi-decadal sensitivity simulations of the CH4-CO-OH system, which primarily determines the global atmospheric oxidizing capacity. This capability is important for capturing the nonlinear feedbacks of the CH4-CO-OH system and understanding the perturbations to methane, CO, and OH, and the concomitant impacts on climate. We implemented the ECCOH chemistry module in the NASA GEOS-5 atmospheric global circulation model (AGCM), performed multiple sensitivity simulations of the CH4-CO-OH system over 2 decades, and evaluated the model output with surface and satellite data sets of methane and CO. The favorable comparison of output from the ECCOH chemistry module (as configured in the GEOS- 5 AGCM) with observations demonstrates the fidelity of the module for use in scientific research.

carbon cycle model↗

Impact of Growth Phase, Pigment Adaptation, and Climate Change Conditions on the Cellular Pigment and Carbon Content of Fifty‐One Phytoplankton Isolates

Owing to their importance in aquatic ecosystems, the demand for models that estimate phytoplankton biomass and community composition in the global ocean has increased over the last decade. Moreover, the impacts of climate change, including elevated carbon dioxide (CO2), increased stratification, and warmer sea surface temperatures, will likely shape phytoplankton community composition in the global ocean. Chemotaxonomic methods are useful for modeling phytoplankton community composition from marker pigments normalized to chlorophyll a (Chl a). However, photosynthetic pigments, particularly Chl a, are sensitive to nutrient and light conditions. Cellular carbon is less sensitive, so using carbon biomass instead may provide an alternative approach. To this end, cellular pigment and carbon concentrations were measured in 51 strains of globally relevant, cultured phytoplankton. Pigment-to-Chl a and pigment-to-carbon ratios were computed for each strain. For 25 strains, measurements were taken during two growth phases. While some differences between growth phases were observed, they did not exceed within class differences. Multiple strains of Amphidinium carterae, Ditylum brightwellii and Heterosigma akashiwo were measured to determine whether time in culture influenced pigment and carbon composition. No appreciable trends in cellular pigment or carbon content were observed. Lastly, the potential impact of climate change conditions on the pigment ratios was assessed using a multistressor experiment that included increased mean light, temperature, and elevated pCO2 on three species: Thalassiosira oceanica, Ostreococcus lucimarinus, and Synechococcus. The largest differences were observed in the pigment-to-carbon ratios, while the marker pigments largely covaried with Chl a. The implications of these observations to chemotaxonomic applications are discussed.

Pigments↗

Better calibration of cloud parameterizations and subgrid effects increases the fidelity of the E3SM Atmosphere Model version 1

Abstract. Realistic simulation of the Earth's mean-state climate remains a major challenge, and yet it is crucial for predicting the climate system in transition. Deficiencies in models' process representations, propagation of errors from one process to another, and associated compensating errors can often confound the interpretation and improvement of model simulations. These errors and biases can also lead to unrealistic climate projections and incorrect attribution of the physical mechanisms governing past and future climate change. Here we show that a significantly improved global atmospheric simulation can be achieved by focusing on the realism of process assumptions in cloud calibration and subgrid effects using the Energy Exascale Earth System Model (E3SM) Atmosphere Model version 1 (EAMv1). The calibration of clouds and subgrid effects informed by our understanding of physical mechanisms leads to significant improvements in clouds and precipitation climatology, reducing common and long-standing biases across cloud regimes in the model. The improved cloud fidelity in turn reduces biases in other aspects of the system. Furthermore, even though the recalibration does not change the global mean aerosol and total anthropogenic effective radiative forcings (ERFs), the sensitivity of clouds, precipitation, and surface temperature to aerosol perturbations is significantly reduced. This suggests that it is possible to achieve improvements to the historical evolution of surface temperature over EAMv1 and that precise knowledge of global mean ERFs is not enough to constrain historical or future climate change. Cloud feedbacks are also significantly reduced in the recalibrated model, suggesting that there would be a lower climate sensitivity when it is run as part of the fully coupled E3SM. This study also compares results from incremental changes to cloud microphysics, turbulent mixing, deep convection, and subgrid effects to understand how assumptions in the representation of these processes affect different aspects of the simulated atmosphere as well as its response to forcings. We conclude that the spectral composition and geographical distribution of the ERFs and cloud feedback, as well as the fidelity of the simulated base climate state, are important for constraining the climate in the past and future.

54 ENVIRONMENTAL SCIENCES↗

How Can Future Climate Change Affect the Corn Production System in Nebraska, USA?

The increasing temperatures and changing precipitation patterns have affected both crop yields and water requirements challenging agricultural systems in sustaining high crop yields and ensuring water and food security. In the present study, we evaluated the impact of climate change on the corn production under irrigated and rainfed cropping systems in Nebraska considering four climate zones until 2100 as a case study for the US Corn Belt. Additionally, suggests ways to reduce the impact of climate change on corn yield and water resources. Five global circulation model datasets from the sixth phase of the Coupled Model Intercomparison Project (CMIP6) interconnected to Shared Socioeconomic Pathways (SSPs), were selected. Three future periods: near (2020–2039), mid (2040–2069), and far future (2070–2100) under SSP226, SSP370, and SSP585 scenarios were used to predict the climate changes, crop cycle length, crop yield, and crop water requirement. Additionally, we input annual CO2 concentration scenarios for each SSP scenario to model changes from 2015 to 2100 using the CERES-Maize model. Temperatures are forecasted to rise, precipitation to decline, and crop cycle length to decrease, particularly for SSP370 (up to 49% yield decrease) and SSP585 (up to 67% yield decrease) by 2070–2100. Yields are expected to decline across all scenarios and periods for irrigated and rainfed fields due to the reduction in crop cycle length. Crop water demand is projected to increase, with rainfed systems facing heightened impact due to reduced precipitation. Addressing climate change in Nebraska requires actions like developing new corn varieties to longer the crop season, transitioning to efficient irrigation systems, improving irrigation management for water and food security, and reducing the risk of conflicts over its use. These results open possibilities for discussion about the actions that can be taken to cope with climate change and guarantee water and food security in the US Corn Belt.

CMIP6↗

The role of ocean climate data in operational Naval oceanography

Local application of global-scale models describes the U.S. Navy's basic philosophy for operational oceanography in support of fleet operations. Real-time data, climatologies, coupled air/ocean models, and large scale computers are the essential components of the Navy's system for providing the war fighters with the performance predictions and tactical decision aids they need to operate safely and efficiently. In peacetime, these oceanographic predictions are important for safety of navigation and flight. The paucity and uneven distribution of real-time data mean we have to fall back on climatology to provide the basic data to operate our models. The Navy is both a producer and user of climatologies; it provides observations to the national archives and in turn employs data from these archives to establish data bases. Suggestions for future improvements to ocean climate data are offered.

Chesbrough, Radm G.↗

Climate Change Impact and Adaptation for Wheat Protein

Wheat grain protein concentration is an important determinant of wheat quality for human nutrition that is often overlooked in efforts to improve crop production. We tested and applied a 32‐multi‐model ensemble to simulate global wheat yield and quality in a changing climate. Potential benefits of elevated atmospheric CO2 concentration by 2050 on global wheat grain and protein yield are likely to be negated by impacts from rising temperature and changes in rainfall, but with considerable disparities between regions. Grain and protein yields are expected to be lower and more variable in most low‐rainfall regions, with nitrogen availability limiting growth stimulus from elevated CO2. Introducing genotypes adapted to warmer temperatures (and also considering changes in CO2 and rainfall) could boost global wheat yield by 7% and protein yield by 2%, but grain protein concentration would be reduced by −1.1 percentage points, representing a relative change of −8.6%. Climate change adaptations that benefit grain yield are not always positive for grain quality, putting additional pressure on global wheat production.

grain protein↗

Attributing human mortality from fire PM 2.5 to climate change

Climate change intensifies fire smoke, emitting hazardous air pollutants that impact human health. However, the global influence of climate change on fire-induced health impacts remains unquantified. Here, in this study, we used three well-tested fire-vegetation models in combination with a chemical transport model and health risk assessment framework to attribute global human mortality from fire fine particulate matter (PM 2.5 ) emissions to climate change. Of the 46401 (1960s) –to 98748 (2010s) annual fire PM 2.5 mortalities, 669 (1.2%, 1960s) –to 12566 (12.8%, 2010s) were attributed to climate change. The most substantial influence of climate change on fire mortality occurred in South America, Australia, and Europe, coinciding with decreased relative humidity, and in boreal forests with increased air temperature. Increasing relative humidity lowered fire mortality in other regions, like South Asia. Our study highlights the role of climate change in fire mortality, aiding public health authorities in spatial targeting adaptation measures for sensitive fire-prone areas.

54 ENVIRONMENTAL SCIENCES↗

Hurricanes and Climate: the U.S. CLIVAR Working Group on Hurricanes

While a quantitative climate theory of tropical cyclone formation remains elusive, considerable progress has been made recently in our ability to simulate tropical cyclone climatologies and understand the relationship between climate and tropical cyclone formation. Climate models are now able to simulate a realistic rate of global tropical cyclone formation, although simulation of the Atlantic tropical cyclone climatology remains challenging unless horizontal resolutions finer than 50 km are employed. The idealized experiments of the Hurricane Working Group of U.S. CLIVAR, combined with results from other model simulations, have suggested relationships between tropical cyclone formation rates and climate variables such as mid-tropospheric vertical velocity. Systematic differences are shown between experiments in which only sea surface temperature is increases versus experiments where only atmospheric carbon dioxide is increased, with the carbon dioxide experiments more likely to demonstrate a decrease in numbers. Further experiments are proposed that may improve our understanding of the relationship between climate and tropical cyclone formation, including experiments with two-way interaction between the ocean and the atmosphere and variations in atmospheric aerosols.

Climate Models↗

Time Variable Gravity modeling for Precise Orbits Across the TOPEX/Poseidon, Jason-l and Jason-2 Missions

Modeling of the Time Variable Gravity (TVG) is believed to constitute one of the the largest remaining source of orbit error for altimeter satellite POD. The GSFC operational TVG model consists of forward modeling the atmospheric gravity using ECMWF 6-hour pressure data, a GRACE derived 20x20 annual field to account for changes in the hydrology and ocean water mass, and linear rates for C20, C30, C40, based on 17 years of SLR data analysis (IERS 2003) using the EIGEN-GL04S1 (a GRACE+Lageos-based geopotential solution). Although the GSFC Operational model can be applied from 1987, there may be long-term variations not captured by these linear models, and more importantly the linear models may not be consistent with more recent surface mass trends due to global climate change, We have evaluated the impact of TVG in two different wavs: (1) by using the more recent EIGEN-6S gravity model developed by the GFZ/GRGS tearm, which consists of annual, semi-annual and secular changes in the coefficients to 50x50 determined over 8(?) years of GRACE+Lageos+GOCE data (2003-200?): (2) Application of 4x4 solutions developed from a multi satellite SLR+DORIS solution based on GGM03S that span the period from 1993 to 2011. We have evaluated the recently released EIGEN6s static and time-varying gravity field for Jason-2 (J2). Jason-I (J1), and TOPEX/Posiedon (TP) Precise Orbit Determination (POD) spanning 1993-2011. Although EIGEN6s shows significant improvement for J2POD spanning 2008 - 2011, it also shows significant degradation for TP POD from 1992. The GSFC 4x4 time SLR+DORIS-based series spans 1993 to mid 2011, and shows promise for POD. We evaluate the performance of the different TVG models based on analysis of tracking data residuals use of independent data such as altimeter crossovers, and through analysis of differences with internally-generated and externally generated orbits.

Zelensky, Nikita P.↗

Toward an Improved Understanding of the Global Fresh Water Budget

The major components of the global fresh water cycle include the evaporation from the land and ocean surfaces, precipitation onto the Ocean and land surfaces, the net atmospheric transport of water from oceanic areas over land, and the return flow of water from the land back into the ocean. The additional components of oceanic water transport are few, principally, the mixing of fresh water through the oceanic boundary layer, transport by ocean currents, and sea ice processes. On land the situation is considerably more complex, and includes the deposition of rain and snow on land; water flow in runoff; infiltration of water into the soil and groundwater; storage of water in soil, lakes and streams, and groundwater; polar and glacial ice; and use of water in vegetation and human activities. Knowledge of the key terms in the fresh water flux budget is poor. Some components of the budget, e.g. precipitation, runoff, storage, are measured with variable accuracy across the globe. We are just now obtaining precise measurements of the major components of global fresh water storage in global ice and ground water. The easily accessible fresh water sources in rivers, lakes and snow runoff are only adequately measured in the more affluent portions of the world. presents proposals are suggesting methods of making global measurements of these quantities from space. At the same time, knowledge of the global fresh water resources under the effects of climate change is of increasing importance and the human population grows. This paper provides an overview of the state of knowledge of the global fresh water budget, evaluating the accuracy of various global water budget measuring and modeling techniques. We review the measurement capabilities of satellite instruments as compared with field validation studies and modeling approaches. Based on these analyses, and on the goal of improved knowledge of the global fresh water budget under the effects of climate change, we suggest priorities for future improvements in global fresh water budget monitoring. The priorities are based on the potential of new approaches to provide improved measurement and modeling systems, and on the need to measure and understand the potential for a speed-up of the global water cycle under the effects of climate change.

Hildebrand, Peter H.↗

Climate changes associated with nuclear war

Nuclear war, featuring explosion of half the world arsenal of nuclear weapons, would cause urban and forest fires that would inject 20-650 megatons of smoke into the atmosphere. The Northern Hemisphere optical depth would increase to between 0.5-14. All models indicate an increase in optical depths, a large net radiation gain in the smoke layer, and an antigreenhouse effect at the surface. Significant global cooling would proceed, transforming the global climate to a large degree toward that of an airless world. Persisting deficiencies in the models are identified, noting research areas which would improve the accuracies of the predictions.

Toon, O. B.↗

Representing Global Soil Erosion and Sediment Flux in Earth System Models

Abstract Soil erosion produces enormous amounts of sediment, carbon, and nutrient fluxes from land to rivers, thus playing crucial roles in global biogeochemical cycles and food security. To predict soil erosion in the context of climate and land use changes, we explicitly parameterize cropland management actions (i.e., irrigation, conserved agriculture, and crop residue management) and geological factors (i.e., lithology and glacier) in the Energy Exascale Earth System Model (E3SM) soil erosion module. The erosion model is calibrated using a global‐scale regionalized parameter calibration method. The spatial variabilities of the modeled and the Revised Universal Soil Loss Equation (RUSLE) based benchmark soil erosion are consistent across vegetation, climate and soil properties. Compared with independent data, our model shows a bias reduction in 59% of the observations relative to the RUSLE‐based soil erosion, with 53% of the bias reduction exceeding 50%. This improvement is mainly due to a better representation of the topographic effect on soil erosion. Our results indicate that conserved agriculture practices have effectively reduced soil erosion in cropland by over 25% in the United States and Argentina. In contrast, irrigation has increased soil erosion in many Asian countries. For upland sediment flux, our model is consistent with the WBMsed benchmark data in inter‐basin variability but could be more skillful in simulating intra‐basin variability because it couples soil erosion and sediment flux explicitly. The developed model provides useful skills for more realistic predictions of soil erosion and river sediment dynamics under environmental changes.

58 GEOSCIENCES↗

Can we achieve atmospheric chemical environments in the laboratory? An integrated model-measurement approach to chamber SOA studies

Secondary organic aerosol (SOA), atmospheric particulate matter formed from low-volatility products of volatile organic compound (VOC) oxidation, affects both air quality and climate. Current 3D models, however, cannot reproduce the observed variability in atmospheric organic aerosol. Because many SOA model descriptions are derived from environmental chamber experiments, our ability to represent atmospheric conditions in chambers directly affects our ability to assess the air quality and climate impacts of SOA. Here, we develop an approach that leverages global modeling and detailed mechanisms to design chamber experiments that mimic the atmospheric chemistry of organic peroxy radicals (RO 2 ), a key intermediate in VOC oxidation. Drawing on decades of laboratory experiments, we develop a framework for quantitatively describing RO 2 chemistry and show that no previous experimental approaches to studying SOA formation have accessed the relevant atmospheric RO 2 fate distribution. We show proof-of-concept experiments that demonstrate how SOA experiments can access a range of atmospheric chemical environments and propose several directions for future studies.

Science & Technology - Other Topics↗

Leveraging Improvements in Precipitation Measuring from GPM Mission to Achieve Prediction Improvements in Climate, Weather and Hydrometeorology

The main scientific goal of the GPM mission, currently planned for start in the 2007 time frame, is to investigate important scientific problems arising within the context of global and regional water cycles. These problems cut across a hierarchy of scales and include climate-water cycle interactions, techniques for improving weather and climate predictions, and better methods for combining observed precipitation with hydrometeorological prediction models for applications to hazardous flood-producing storms, seasonal flood/draught conditions, and fresh water resource assessments. The GPM mission will expand the scope of precipitation measurement through the use of a constellation of some 9 satellites, one of which will be an advanced TRMM-like "core" satellite carrying a dual-frequency Ku-Ka band precipitation radar and an advanced, multifrequency passive microwave radiometer with vertical-horizontal polarization discrimination. The other constellation members will include new dedicated satellites and co-existing Operational/research satellites carrying similar (but not identical) passive microwave radiometers. The goal of the constellation is to achieve approximately 3-hour sampling at any spot on the globe. The constellation's orbit architecture will consist of a mix of sun-synchronous and non-sun-synchronous satellites with the core satellite providing measurements of cloud-precipitation microphysical processes plus calibration-quality rainrate retrievals to be used with the other retrieval information to ensure bias-free constellation coverage. GPM is organized internationally, currently involving a partnership between NASA in the US and the National Space Development Agency in Japan. Additionally, the program is actively pursuing agreements with other international partners and domestic scientific agencies and institutions, as well as participation by individual scientists from academia, government, and the private sector to fulfill mission goals and to pave the way for what ultimately is expected to become an internationally-organized operational global precipitation observing system. Notably, the broad societal applications of GPM are reflected in the United Nation s identification of this mission as a foremost candidate for its Peaceful Uses of Space Program. In this presentation, an overview of the GPM mission design will be presented, followed by an explanation of its scientific agenda as an outgrowth of making improvements in rain retrieval accuracy, microphysics dexterity, sampling frequency, and global coverage. All of these improvements offer new means to observe variability in precipitation and water cycle fluxes and to achieve improved predictability of weather, climate, and hydrometeorology. Specifically, the scientific agenda of GPM has been designed to leverage the measurement improvements to improve prognostic model performance, particularly quantitative precipitation forecasting and its linked phenomena at short, intermediate, and extended time scales. The talk will address how GPM measurements will enable better detection of accelerations and decelerations in regional and global water cycle processes and their relationship to climate variability, better impacts of precipitation data assimilation on numerical weather prediction and global climate reanalysis, and better performance from basin scale hydrometeorological models for short and long term flood-drought forecasting and seasonal fresh water resource assessment. Improved hydrometeorological forecasting will be possible by using continuous global precipitation observations to obtain better closure in water budgets and to generate more realistic forcing of the models themselves to achieve more accurate estimates of interception, infiltration, evaporation/transpiration fluxes, storage, and runoff.

Smith, Eric A.↗

Simulated Impacts of Climate Change on Water Use and Yield of Irrigated Sugarcane in South Africa

Reliable predictions of climate change impacts on water use, irrigation requirements and yields of irrigated sugarcane in South Africa (a water-scarce country) are necessary to plan adaptation strategies. Although previous work has been done in this regard, methodologies and results vary considerably. The objectives were (1) to estimate likely impacts of climate change on sugarcane yields, water use and irrigation demand at three irrigated sugarcane production sites in South Africa (Malelane, Pongola and La Mercy) for current (1980-2010) and future (2070-2100) climate scenarios, using an approach based on the Agricultural Model Inter-comparison and Improvement Project (AgMIP) protocols; and (2) to assess the suitability of this methodology for investigating climate change impacts on sugarcane production. Future climate datasets were generated using the Delta downscaling method and three Global Circulation Models (GCMs) assuming atmospheric CO2 concentration [CO2] of 734 ppm(A2 emissions scenario). Yield and water use were simulated using the DSSAT-Canegro v4.5 model. Irrigated cane yields are expected to increase at all three sites (between 11 and 14%), primarily due to increased interception of radiation as a result of accelerated canopy development. Evapotranspiration and irrigation requirements increased by 11% due to increased canopy cover and evaporative demand. Sucrose yields are expected to decline because of increased consumption of photo-assimilate for structural growth and maintenance respiration. Crop responses in canopy development and yield formation differed markedly between the crop cycles investigated. Possible agronomic implications of these results include reduced weed control costs due to shortened periods of partial canopy, a need for improved efficiency of irrigation to counter increased demands, and adjustments to ripening and harvest practices to counter decreased cane quality and optimize productivity. Although the Delta climate data downscaling method is considered robust, accurate and easily-understood, it does not change the future number of rain-days per month. The impacts of this and other climate data simplifications ought to be explored in future work. Shortcomings of the DSSAT-Canegro model include the simulated responses of phenological development, photosynthesis and respiration processes to high temperatures, and the disconnect between simulated biomass accumulation and expansive growth. Proposed methodology refinements should improve the reliability of predicted climate change impacts on sugarcane yield.

Climate change↗