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At least 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Tropical Cyclones, Hurricanes, and Climate: NASA's Global Cloud-Scale Simulations and New Observations that Characterize the Lifecycle of Hurricanes

One of the primary interests of Global Change research is the impact of climate changes and climate variability on extreme weather events, such as intense tropical storms and hurricanes. Atmospheric climate models run at resolutions of global weather models have been used to study the impact of climate variability, as seen in sea surface temperatures, on the frequency and intensity of tropical cyclones. NASA's Goddard Earth Observing System Model, version 5 (GEOS-5) in ensembles run at 50 km resolution has been able to reproduce the interannual variations of tropical cyclone frequency seen in nature. This, and other global models, have found it much more difficult to reproduce the interannual changes in intensity, a result that reflects the inability of the models to simulate the intensities of the most extreme storms. Better representation of the structures of cyclones requires much higher resolution models. Such improved representation is also fundamental to making best use of satellite observations. In collaboration with NOAA's Geophysical Fluid Dynamics Laboratory, GEOS-5 now has the capability of running at much higher resolution to better represent cloud-scale resolutions. Global simulations at cloud-permitting resolutions (10- to 3.5-km) allows for the development of realistic tropical cyclones from tropical storm 119 km/hr winds) to category 5 (>249km1hr winds) intensities. GEOS-5 has produced realistic rain-band and eye-wall structures in tropical cyclones that can be directly analyzed against satellite observations. For the first time a global climate model is capable of representing realistic intensity and track variability on a seasonal scale across basins. GEOS-5 is also used in assimilation mode to test the impact of NASA's observations on tropical cyclone forecasts. One such test, for tropical cyclone Nargis in the Indian Ocean in May 2008, showed that observations from Atmospheric Infrared Sounder (AIRS) and the Advanced Microwave Sounding Unit (AMSU-A) on Aqua substantially reduced forecast track errors. Tropical cyclones in the northern Indian Ocean pose serious challenges to operational weather forecasting systems, partly due to their shorter lifespan and more erratic track, compared to those in the Atlantic and the Pacific. SA is also bringing several state of the art instruments in recent field campaigns to peer under the clouds and study the inner workings of the tropical storms. With the Genesis and Rapid Intensification Processes (GRIP) experiment, a NASA Earth science field experiment in 2010 that includes the Global Hawk Unmanned Airborne System (UAS) configured with a suite of in situ and remote sensing instruments that are observing and characterizing the lifecycle of hurricanes, we expect significant improvement in our understanding of the track and intensification processes with the assimilation of the satellite and field campaign observations of meteorological parameters in the numerical prediction models.

Putman, William M.↗
NASA NTRS2016

Crop Model Improvement Reduces the Uncertainty of the Response to Temperature of Multi-Model Ensembles

To improve climate change impact estimates and to quantify their uncertainty, multi-model ensembles (MMEs) have been suggested. Model improvements can improve the accuracy of simulations and reduce the uncertainty of climate change impact assessments. Furthermore, they can reduce the number of models needed in a MME. Herein, 15 wheat growth models of a larger MME were improved through re-parameterization and/or incorporating or modifying heat stress effects on phenology, leaf growth and senescence, biomass growth, and grain number and size using detailed field experimental data from the USDA Hot Serial Cereal experiment (calibration data set). Simulation results from before and after model improvement were then evaluated with independent field experiments from a CIMMYT worldwide field trial network (evaluation data set). Model improvements decreased the variation (10th to 90th model ensemble percentile range) of grain yields simulated by the MME on average by 39% in the calibration data set and by 26% in the independent evaluation data set for crops grown in mean seasonal temperatures greater than 24 C. MME mean squared error in simulating grain yield decreased by 37%. A reduction in MME uncertainty range by 27% increased MME prediction skills by 47%. Results suggest that the mean level of variation observed in field experiments and used as a benchmark can be reached with half the number of models in the MME. Improving crop models is therefore important to increase the certainty of model-based impact assessments and allow more practical, i.e. smaller MMEs to be used effectively.

damage assessment↗
NASA NTRS2024

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↗
NASA NTRS1990

The influence of continental sources of aerosols on the marine stratocumulus during FIRE IFO-1

The effects of aerosols on the microphysical characteristics of marine stratocumulus clouds can have a significant impact on climate processes through modification of cloud radiative properties. The effect of aerosols on clouds and the impact on climate processes have recently been discussed by several authors (Twomey et al., 1984; Coakley et al., 1987; Charlson et al., 1987). Of particular concern is the potential for observing variations of cloud characteristics that might be related to variations of available aerosols. The results of comparisons between aircraft-measured microphysical characteristics and satellite-detected radiative properties of marine stratocumulus clouds are presented. These results are extracted from Mineart (1988) and Durkee and Mineart (1989) where the analysis procedures and a full discussion of the observations are presented. Due to the space available, only a brief description of the results is presented. The satellite data used here are from the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) collected at the Scripps Satellite Oceanography Facility. The AVHRR channel 1 (0.63 microns), channel 2 (0.86 microns), channel 3 (3.7 microns), and channel 4 (11 microns) data were used in the analysis. Cloud microphysical data were obtained by instruments on the NCAR Electra during cloud-penetrating missions in support of the field operations from 29 June to 19 July 1988.

Durkee, Philip A.↗
NASA NTRS2004

Application of Remote Sensing to Assess the Impact of Short Term Climate Variability on Coastal Sedimentation

The purpose of this joint University of Wisconsin (UW) and Louisiana State University (LSU) project has been to relate short term climate variation to response in the coastal zone of Louisiana in an attempt to better understand how the coastal zone is shaped by climate variation. Climate variation in this case largely refers to variation in surface wind conditions that affect wave action and water currents in the coastal zone. The primary region of focus was the Atchafalaya Bay and surrounding bays in the central coastal region of Louisiana. Suspended solids in the water column show response to wind systems both in quantity (through resuspension) and in the pattern of dispersement or transport. Wind systems associated with cold fronts are influenced by short term climate variation. Wind energy was used as the primary signature of climate variation in this study because winds are a significant influence on sediment transport in the micro-tidal Gilf of Mexico coastal zone. Using case studies, the project has been able to investigate the influence of short term climate variation on sediment transport. Wind energy data, collected daily for National Weather Service (NWS) stations at Lake Charles and New Orleans, LA, were used as an indicator of short term climate variation influence on seasonal time scales. A goal was to relate wind energy to coastal impact through sediment transport. This goal was partially accomplished by combining remote sensing and wind energy data. Daily high resolution remote sensing observations are needed to monitor the complex coastal zone environment, where winds, tides, and water level all interact to influence sediment transport. The NASA Earth Observing System (EOS) era brings hope for documenting and revealing response of the complex coastal transport mosaic through regular high spatial resolution observations from the Moderate resolution Imaging Spectrometer (MODIS) instrument. MODIS observations were sampled in this project for information content and should continue to be viewed as a resource for coastal zone monitoring. The project initialized the effort to transfer a suspended sediment concentration (SSC) algorithm to the MODIS platform for case 2 waters. MODIS enables monitoring of turbid coastal zones around the globe. The MODIS SSC algorithm requires refinements in the atmospheric aerosol contribution, sun glint influence, and designation of the sediment inherent optical properties (IOPs); the framework for continued development is in place with a plan to release the algorithm to the MODIS direct broadcast community.

Menzel, W. Paul↗
NASA NTRS2022

Global Gridded Crop Models Underestimate Yield Responses to Droughts and Heatwaves

Extreme events can lead to crop yield declines, resulting in financial losses and threats to food security, and the frequency and intensity of such events is projected to increase. As global gridded crop models (GGCMs) are commonly used to assess climate change impacts on agricultural yields, there is a need to understand whether these models are able to reproduce the observed yield declines. We evaluated 13 GGCMs from the Inter-Sectoral Impact Model Intercomparison Project and compared observed and simulated impact of past droughts and heatwaves on yields for four crops (maize, rice, soy, wheat). We found that most models detect but underestimate the impact of droughts and heatwaves on yield. Specifically, the drought signal was detected by 12 of 13 models for maize and all models for wheat, while the heat signal was detected by eleven models for maize and six models for wheat. To investigate whether the difference between simulated and observed yield declines is due to a misrepresentation of simulated exposure to heat or water scarcity (i.e. misrepresentation of growing season), we analysed the relationship between average discrepancies between observed and simulated yield losses, and average simulated exposure to extreme weather conditions across all crop models. We found a positive correlation between simulated exposure to heat and model performance for heatwaves, but found no correlation for droughts. This suggests that there is a systematic underestimation of yield responses to heat and drought and not only a misrepresentation of exposure. Assuming that performance for the past indicates models' capacity to project future yield impacts, models likely underestimate future yield decline from climate change. High-quality temporally and spatially resolved observational data on growing seasons will be highly valuable to further improve crop models' capacity to adequately respond to extreme weather events.

extreme events↗
NASA NTRS2015

Preface

The potential effects of climate change on the food production system are raising concern both globally and regionally. The system is already challenged to deliver sufficient and healthy sustenance to all people, and is certain to be even further challenged as world population grows and price shocks loom. The prospect of climate change intensifies these challenges, raising the risk that more frequent and intense extreme weather events threaten the stability of agricultural production in regions around the globe. This two-part set is an important contribution to the ongoing Imperial College Press (ICP) Series on Climate Change Impacts, Adaptation, and Mitigation. This series aims to provide the know ledge base necessary for understanding and responding to climate change, in both its current form and future manifestations. In these volumes, ·leading agricultural researchers have come together to contribute their expertise on actual and potential climate change impacts, adaptation strategies, and mitigation efforts. This ongoing series is jointly published by The American Society of Agronomy (ASA), Crop Science Society of America (CSSA), and Soil Science Society of America (SSSA), together with ICP. We hope that this fruitful cooperation will continue for many years to come, as it spurs the global effort to define and meet the great food security and climate change challenges of our time.

farmlands↗
NASA NTRS2014

Heat-Related Mortality in a Warming Climate: Projections for 12 U.S. Cities

Heat is among the deadliest weather-related phenomena in the United States, and the number of heat-related deaths may increase under a changing climate, particularly in urban areas. Regional adaptation planning is unfortunately often limited by the lack of quantitative information on potential future health responses. This study presents an assessment of the future impacts of climate change on heat-related mortality in 12 cities using 16 global climate models, driven by two scenarios of greenhouse gas emissions. Although the magnitude of the projected heat effects was found to differ across time, cities, climate models and greenhouse pollution emissions scenarios, climate change was projected to result in increases in heat-related fatalities over time throughout the 21st century in all of the 12 cities included in this study. The increase was more substantial under the high emission pathway, highlighting the potential benefits to public health of reducing greenhouse gas emissions. Nearly 200,000 heat-related deaths are projected to occur in the 12 cities by the end of the century due to climate warming, over 22,000 of which could be avoided if we follow a low GHG emission pathway. The presented estimates can be of value to local decision makers and stakeholders interested in developing strategies to reduce these impacts and building climate change resilience.

heat-related mortality↗
NASA NTRS1992

A model of the CO2 exchanges between biosphere and atmosphere in the tundra

A physical model of the soil thermal regime in a permafrost terrain has been developed and validated with soil temperature measurements at Barrow, Alaska. The model calculates daily soil temperatures as a function of depth and average moisture contents of the organic and mineral layers using a set of five climatic variables, i.e., air temperature, precipitation, cloudiness, wind speed, and relative humidity. The model is not only designed to study the impact of climate change on the soil temperature and moisture regime, but also to provide the input to a decomposition and net primary production model. In this context, it is well known that CO2 exchanges between the terrestrial biosphere and the atmosphere are driven by soil temperature through decomposition of soil organic matter and root respiration. However, in tundra ecosystems, net CO2 exchange is extremely sensitive to soil moisture content; therefore it is necessary to predict variations in soil moisture in order to assess the impact of climate change on carbon fluxes. To this end, the present model includes the representation of the soil moisture response to changes in climatic conditions. The results presented in the foregoing demonstrate that large errors in soil temperature and permafrost depth estimates arise from neglecting the dependence of the soil thermal regime on soil moisture contents. Permafrost terrain is an example of a situation where soil moisture and temperature are particularly interrelated: drainage conditions improve when the depth of the permafrost increases; a decrease in soil moisture content leads to a decrease in the latent heat required for the phase transition so that the heat penetrates faster and deeper, and the maximum depth of thaw increases; and as excepted, soil thermal coefficients increase with moisture.

Labgaa, Rachid R.↗
NASA NTRS2021

Increases in Future AR Count and Size: Overview of 2 the ARTMIP Tier 2 CMIP5/6 Experiment

The Atmospheric River (AR) Tracking Method Intercomparison Project (ARTMIP) is a community effort to systematically assess how the uncertainties from AR detectors (ARDTs) impact our scientific understanding of ARs. This study describes the ARTMIP Tier 2 experimental design and initial results using the Coupled Model Intercomparison Project (CMIP) Phases 5 and 6 multi-model ensembles. We show that AR statistics from a given ARDT in CMIP5/6 historical simulations compare remarkably well with the MERRA-2 reanalysis. In CMIP5/6 future simulations, most ARDTs project a global increase in AR frequency, counts, and sizes, especially along the western coastlines of the Pacific and Atlantic oceans. We find that the choice of ARDT is the dominant contributor to the uncertainty in projected AR frequency when compared with model choice. These results imply that new projects investigating future changes in ARs should explicitly consider ARDT uncertainty as a core part of the experimental design. Plain Language Summary: Atmospheric rivers (ARs) are a type of weather pattern known to be important for moving water vapor from the warm, moist tropics to the cool, dry polar regions; when they reach midlatitudes in the winter time, they are commonly associated with heavy precipitation. Recent studies that assess the impacts of global climate change on ARs tend to agree that there will be more ARs in a warmer climate, and that ARs will tend to be more extreme. However, it has been increasingly recognized by the AR research community that these results may depend on the method used to identify ARs and the choice of climate model. This study reports results from a controlled experiment, involving an international research community, that aims to show how different AR identification methods and climate models might impact our scientific understanding of ARs in the future. This experiment shows that there will likely be more ARs in the future, and that ARs will generally have a larger spatial footprint. This experiment also shows that uncertainty in these results are large, with the uncertainty from AR identification methods outweighing that of climate models. Future efforts to better understand the physics of ARs may help us reduce this uncertainty.

T A OBrien↗
NASA NTRS2014

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

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.

Climate Forcing Data↗
NASA NTRS2014

Sensitivity of Air Quality to Potential Future Climate Change and Emissions in the United States and Major Cities

Simulated present and future air quality is compared for the years 2006e2010 and 2048e2052 over the contiguous United States (CONUS) using the Community Multi-scale Air Quality (CMAQ) model. Regionally downscaled present and future climate results are developed using GISS and the Weather Research Forecasting (WRF) model. Present and future emissions are estimated using MARKAL 9R model. O3 and PM(sub 2.5) sensitivities to precursor emissions for the years 2010 and 2050 are calculated using CMAQDDM (Direct Decoupled Method). We find major improvements in future U.S. air quality including generally decreased MDA8 (maximum daily 8-hr average O3) mixing ratios and PM(sub 2.5) concentrations and reduced frequency of NAAQS O3 standard exceedances in most major U.S. cities. The Eastern and Pacific U.S. experience the largest reductions in summertime seasonal average MDA8 (up to 12 ppb) with localized decreases in the 4th highest MDA8 of the year, decreasing by up to 25 ppb. Results from a Climate Penalty (CP) scenario isolate the impact of climate change on air quality and show that future climate change tends to increase O3 mixing ratios in some regions of the U.S., with climate change causing increases of over 10 ppb in the annual 4th highest MDA8 in Los Angeles. Seasonal average PM(sub 2.5) decreases (2-4 microgram m(exp -3)) over the Eastern U.S. are accounted for by decreases in sulfate and nitrate concentrations resulting from reduced mobile and point source emissions of NO(sub x) and SO(sub x).

Projecting emissions↗
NASA NTRS2024

Downscaled and Bias-Adjusted Climate Projections for Afghanistan

Climate change is already having devastating impacts on human communities and natural landscapes, from increasing severity and frequency of natural disasters to drought and desertification that degrade both natural ecosystems and human livelihoods. However, the impacts of climate change are not evenly distributed across the world—some places are at far greater risk than others. These highly vulnerable places should be a higher priority for investments and interventions to help people and nature adapt to changing climatic conditions. Afghanistan is one of the most at-risk countries from climate change. Within the country, the river basins are particularly sensitive as climate change will dramatically alter their water regimes upon which ecosystems and a vast proportion of the Afghan population and millions of people in neighbouring countries rely. As part of an EU-funded project implemented by the Wildlife Conservation Society (WCS), WCS conducted a vulnerability assessment for the Amu Darya River Basin that drains c. 14% of Afghanistan’s land area and is critically important for supporting both people and sensitive biodiversity (Elsen et al., 2023). Central to the vulnerability assessment was the development of downscaled and bias-adjusted climate projections, produced by the Center for Climate Systems Research (CCSR)1. The climate projections were produced at a much higher resolution (1 km2) than were otherwise available and were tailored to the local environment.

climate projections↗
NASA NTRSDate not supplied

Urban Expansion and Climate Change: Investigating the Impact of Future Scenarios on Child Health

Cities in the poorest countries of the world are rapidly urbanizing. In fact, some of the fastest growing cities on the planet are found in sub-Saharan Africa. Many people benefit from economic, educational, and health opportunities that exist in cities and, as a result, city-dwellers often face less risk of poverty and disease in the context of climate change than their rural-dwelling counterparts. However, rapid urbanization, resulting from a large and constant influx of migrants from rural areas, can put pressure on existing social, economic, and health systems. For poor cities, they face a challenge to support existing residents while also expanding to support the needs of migrants, many of whom are deeply impoverished. Additionally, in a climate change, linked to heat waves, floods, droughts, and other related events, can add stress to complex urban food, health, hygiene, and housing systems. In this project we investigate urban expansion, climate change, and health in four major African cities – Ouagadougou, Addis Ababa, Nairobi, and Kigali. We consider different scenarios of urban expansion using historic and contemporary maps of urban extent, combined with climate (temperature, rainfall, and vegetation) and land cover combined with spatially referenced health information from the Demographic and Health Surveys (DHS) to investigate the relationships between urban dwelling, climate change and health. Temperature and rainfall scenarios are developed under different urban land use futures (expanding agricultural areas versus reducing agricultural areas) to examine the ways that individual health outcomes related to malnutrition vary under different potential future conditions. Preliminary results of the research highlight the importance of temperature for health, in particular, and suggest that while urban conditions related to urban infrastructure (e.g., educational attainment, electricity access, and improved hygiene) cannot reduce health risks to counter the impacts of high temperatures and reduced agricultural land. As cities in poor countries urbanize, city-dwellers face unique risks when droughts, heat waves, and other extreme weather events occur. In this project we explore urban land use conditions, climate conditions and health using future scenarios. Specifically we evaluate health outcomes in the future while considering different land use practices, urban expansion, temperature, and rainfall conditions to identify individual-level risk and protective factors. We compare results across four major cities in sub Saharan Africa.

Public Health↗
NASA NTRS2022

Systemic Risk

Systemic risk is the name given to impacts that spread within and across systems and sectors (e.g. ecosystems, health, infrastructure and the food sector) via the movements of people, goods, capital and information within and across boundaries (e.g. regions, countries and continents). The spread of these impacts can lead to potentially existential consequences and system collapse across a range of time horizons. Globalization contributes to systemic risk affecting people worldwide. The impacts of climate change or COVID-19 show how the challenges of addressing systemic risk go beyond conventional risk management and governance. Critical system interdependencies, amplified by underlying vulnerabilities, highlight that there is a growing need to better understand cascading impacts, systemic risks and the possible political (governance) and societal responses. This includes improving our understanding of the root causes of systemic risk, both biophysical and socio-economic, and related information needs. Addressing contemporary challenges in terms of systemic risk requires integrating different systems perspectives and fostering system thinking, while implementing key intergovernmental agendas, such as the Paris Agreement, the Sendai Framework for Disaster Risk Reduction and the Sustainable Development Goals.

systemic risk↗
NASA NTRS2004

Investigating Downscaling Methods and Evaluating Climate Models for Use in Estimating Regional Water Resources in Mountainous Regions under Changing Climatic Conditions

The purpose of this three-year study is to develop and evaluate techniques to estimate the range of potential hydrological impacts of climate change in mountainous areas. Three main objectives are set out in the proposal. (1) To develop and evaluate transfer functions to link tropospheric circulation to regional snowfall. (2) To evaluate a suite of General Circulation Models (GCMs) for use in estimating synoptic scale circulation and the resultant regional snowfall. And (3) to estimate the range of potential hydrological impacts of changing climate in the two case study areas: the Upper Colorado River basin, and the Catskill Mountains of southeastern New York State. Both regions provide water to large populations.

Frei, Allan↗
NASA NTRS2022

Powering the Future of Electric Aviation

Aviation is one of the largest contributors to climate change on this planet, responsible for nearly 5% of the global warming impact on Earth. As the aviation sector is projected to grow and as new aircraft are introduced, aviation’s impact on climate change will only increase. Without sustainable alternatives implemented in the near future, aviation could strongly contribute to making this planet uninhabitable. This paper examines the possibilities of electric aviation and other power sources in reducing the impact of aviation on climate change. Although there are many power sources for aircraft, electricity is the most effective and sustainable power source. Electric aviation, however, is still relatively new, and there are limitations with electric power, such as battery size, energy density, and charging. This paper dives deeper into the applications and factors to consider for the implementation of electric aircraft into the current society, as well as a potential solution to accelerate the process. Specifically, our research finds that hydrogen fuel cells, despite a few limitations, provide the amount of energy necessary to develop capable and sustainable electric aircraft in a manner that may be the most feasible.

electric aviation↗
NASA NTRS1998

The Impact of Very Fine Vertical Resolution on the Climate of the GEOS-2 GCM

Typical General Circulation Models (GCM's) that are used for tropospheric climate studies extend vertically with significant resolution only into the lower stratosphere, while GCM's specifically designed for the study of the stratospheric climate do not finely resolve the tropospheric jet or boundary layer regions. The NASA/Goddard Data Assimilation Office (DAO) Goddard Earth Observing System GCM, (GEOS-2 GCM) which is a component of the GEOS-2 Data Assimilation System (DAS), is configured with a sufficient number of vertical levels to provide very fine resolution in the tropospheric and stratospheric regimes. The present study is aimed at understanding the benefits for accurate simulation of the climate seen in the GEOS-2 GCM due to its choice of vertical resolution. Raising the model lid to the lower mesosphere so as to explicitly resolve the stratospheric circulation, in particular the descent over the winter pole, is included in GEOS-2 to address the common GCM deficiency of a stratospheric cold pole bias. Increasing the number of levels is directed at improving the representation of the planetary boundary layer, the troposphere at the altitude of the sub-tropical jet stream, and the stratosphere. Comparisons of the climate of simulations with three different vertical resolution formulations of the GEOS-2 GCM are presented. In addition to the reduction in the climate bias, the impact of the resolution on model variability will be briefly discussed.

Molod, Andrea↗