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NASA NTRS2005

NCAR Johns Hopkins/CDC Climate and Health Summer Institute

The interactions between climate and health are rife with complexity and present many conceptual and methodological challenges. Possible effects of climate change on health are considered some of the most sensitive impacts of climate change and are a high priority for policy-makers and the public. As a first step toward improving tlit: quality of research, we developed a Climate and Health Workshop (Institute), geared toward teaching students various aspects of how to conduct integrated climate and health research. At the workshop scientists presented selected case studies of climate and health (e.g., heat mortality, vector-borne diseases), thus demonstrating a subset of key analytical tools and databases most useful to researchers in this field. Key research gaps in this research area were discussed. In this six-day Institute (21-28 July 2004, Boulder, Colorado), health scientists and students benefited from lectures and hands-on tools taught by top NCAR scientists. The attendees learned about health databases and epidemiologic methods from leading health scientists from CDC, Johns Hopkins, and other institutions from around the globe.

Mearns, Linda O.↗

NASA NTRS1997

Global Analysis of Empirical Relationships Between Annual Climate and Seasonality of NDVI

This paper describes the use of satellite data to calibrate a new climate-vegetation greenness relationship for global change studies. We examined statistical relationships between annual climate indexes (temperature, precipitation, and surface radiation) and seasonal attributes If the AVHRR Normalized Difference Vegetation Index (NDVI) time series for the mid-1980's in order to refine our understanding of intra-annual patterns and global abiotic controls on natural vegetation dynamics. Multiple linear regression results using global 1o gridded data sets suggest that three climate indexes: degree days (growing/chilling), annual precipitation total, and an annual moisture index together can account to 70-80 percent of the geographic variation in the NDVI seasonal extremes (maximum and minimum values) for the calibration year 1984. Inclusion of the same annual climate index values from the previous year explains no substantial additional portion of the global scale variation in NDVI seasonal extremes. The monthly timing of NDVI extremes is closely associated with seasonal patterns in maximum and minimum temperature and rainfall, with lag times of 1 to 2 months. We separated well-drained areas from lo grid cells mapped as greater than 25 percent inundated coverage for estimation of both the magnitude and timing of seasonal NDVI maximum values. Predicted monthly NDVI, derived from our climate-based regression equations and Fourier smoothing algorithms, shows good agreement with observed NDVI for several different years at a series of ecosystem test locations from around the globe. Regions in which NDVI seasonal extremes are not accurately predicted are mainly high latitude zones, mixed and disturbed vegetation types, and other remote locations where climate station data are sparse.

Potter, C. S.↗

NASA NTRS1997

Global Analysis of Empirical Relationships Between Annual Climate and Seasonality of NDVI

This study describes the use of satellite data to calibrate a new climate-vegetation greenness function for global change studies. We examined statistical relationships between annual climate indexes (temperature, precipitation, and surface radiation) and seasonal attributes of the AVHRR Normalized Difference Vegetation Index (NDVI) time series for the mid-1980s in order to refine our empirical understanding of intraannual patterns and global abiotic controls on natural vegetation dynamics. Multiple linear regression results using global l(sup o) gridded data sets suggest that three climate indexes: growing degree days, annual precipitation total, and an annual moisture index together can account to 70-80 percent of the variation in the NDVI seasonal extremes (maximum and minimum values) for the calibration year 1984. Inclusion of the same climate index values from the previous year explained no significant additional portion of the global scale variation in NDVI seasonal extremes. The monthly timing of NDVI extremes was closely associated with seasonal patterns in maximum and minimum temperature and rainfall, with lag times of 1 to 2 months. We separated well-drained areas from l(sup o) grid cells mapped as greater than 25 percent inundated coverage for estimation of both the magnitude and timing of seasonal NDVI maximum values. Predicted monthly NDVI, derived from our climate-based regression equations and Fourier smoothing algorithms, shows good agreement with observed NDVI at a series of ecosystem test locations from around the globe. Regions in which NDVI seasonal extremes were not accurately predicted are mainly high latitude ecosystems and other remote locations where climate station data are sparse.

Potter, C. S.↗

NASA NTRS2007

Future Climate Impacts of Direct Radiative Forcing Anthropogenic Aerosols, Tropospheric Ozone, and Long-lived Greenhouse Gases

Long-lived greenhouse gases (GHGs) are the most important driver of climate change over the next century. Aerosols and tropospheric ozone (O3) are expected to induce significant perturbations to the GHG-forced climate. To distinguish the equilibrium climate responses to changes in direct radiative forcing of anthropogenic aerosols, tropospheric ozone, and GHG between present day and year 2100, four 80-year equilibrium climates are simulated using a unified tropospheric chemistry-aerosol model within the Goddard Institute for Space Studies (GISS) general circulation model (GCM) 110. Concentrations of sulfate, nitrate, primary organic (POA) carbon, secondary organic (SOA) carbon, black carbon (BC) aerosols, and tropospheric ozone for present day and year 2100 are obtained a priori by coupled chemistry-aerosol GCM simulations, with emissions of aerosols, ozone, and precursors based on the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenario (SRES) A2. Changing anthropogenic aerosols, tropospheric ozone, and GHG from present day to year 2100 is predicted to perturb the global annual mean radiative forcing by +0.18 (considering aerosol direct effects only), +0.65, and +6.54 W m(sup -2) at the tropopause, and to induce an equilibrium global annual mean surface temperature change of +0.14, +0.32, and +5.31 K, respectively, with the largest temperature response occurring at northern high latitudes. Anthropogenic aerosols, through their direct effect, are predicted to alter the Hadley circulation owing to an increasing interhemispheric temperature gradient, leading to changes in tropical precipitation. When changes in both aerosols and tropospheric ozone are considered, the predicted patterns of change in global circulation and the hydrological cycle are similar to those induced by aerosols alone. GHG-induced climate changes, such as amplified warming over high latitudes, weakened Hadley circulation, and increasing precipitation over the Tropics and high latitudes, are consistent with predictions of a number of previous GCM studies. Finally, direct radiative forcing of anthropogenic aerosols is predicted to induce strong regional cooling over East and South Asia. Wintertime rainfall over southeastern China and the Indian subcontinent is predicted to decrease because of the increased atmospheric stability and decreased surface evaporation, while the geographic distribution of precipitation is also predicted to be altered as a result of aerosol-induced changes in wind flow.

Chen, Wei-Ting↗

NASA NTRS2007

The Spatiotemporal Structure of 20th Century Climate Variations in Observations and Reanalyses: Long-term Trend - Part 1

The dominant interannual El Nino-Southern Oscillation phenomenon (ENSO) and the short length of climate observation records make it difficult to study long-term climate variations in the spatiotemporal domain. Based on the fact that the ENS0 signal spreads to remote regions and induces delayed climate variation through atmospheric teleconnections, we develop an ENSO-removal method through which the ENS0 signal can be approximately removed at the grid box level from the spatiotemporal field of a climate parameter. After this signal is removed, long-term climate variations, namely, the global warming trend (GW) and the Pacific pan-decadal variability (PDV), are isolated at middle and low latitudes in the climate parameter fields from observed and reanalyses datasets. Except for known GW characteristics, the warming that occurs in the Pacific basin (approximately 0.4K in the 2oth century) is much weaker than in surrounding regions and the other two ocean basins (approximately 0.8K). The modest warming in the Pacific basin is likely due to its dynamic nature on the interannual and decadal time scales and/or the leakage of upper ocean water through the Indonesian Throughflow. Based on NCEP/NCAR and ERA-40 reanalyses, a comprehensive atmospheric structure associated with GW is given. Significant discrepancies exist between the two datasets, especially in the tightly coupled dynamic and water vapor fields. The dynamic field based on NCEP/NCAR reanalysis, which shows a change in the Walker Circulation, is consistent with the GW change in the surface temperature field. However, intensification in the Hadley Circulation is associated with GW trend in the ERA-40 reanalysis.

Chen, Junye↗

NASA NTRS2009

Atmospheric Aerosol Properties and Climate Impacts

This report critically reviews current knowledge about global distributions and properties of atmospheric aerosols, as they relate to aerosol impacts on climate. It assesses possible next steps aimed at substantially reducing uncertainties in aerosol radiative forcing estimates. Current measurement techniques and modeling approaches are summarized, providing context. As a part of the Synthesis and Assessment Product in the Climate Change Science Program, this assessment builds upon recent related assessments, including the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR4, 2007) and other Climate Change Science Program reports. The objectives of this report are (1) to promote a consensus about the knowledge base for climate change decision support, and (2) to provide a synthesis and integration of the current knowledge of the climate-relevant impacts of anthropogenic aerosols for policy makers, policy analysts, and general public, both within and outside the U.S government and worldwide.

Chin, Mian↗

NASA NTRS2010

The Net Climate Impact of Coal-Fired Power Plant Emissions

Coal-fired power plants influence climate via both the emission of long-lived carbon dioxide (CO2) and short-lived ozone and aerosol precursors. Using a climate model, we perform the first study of the spatial and temporal pattern of radiative forcing specifically for coal plant emissions. Without substantial pollution controls, we find that near-term net global mean climate forcing is negative due to the well-known aerosol masking of the effects of CO2. Imposition of pollution controls on sulfur dioxide and nitrogen oxides leads to a rapid realization of the full positive forcing from CO2, however. Long-term global mean forcing from stable (constant) emissions is positive regardless of pollution controls. Emissions from coal-fired power plants until 1970, including roughly 1/3 of total anthropogenic CO2 emissions, likely contributed little net global mean climate forcing during that period though they may have induce weak Northern Hemisphere mid-latitude (NHml) cooling. After that time many areas imposed pollution controls or switched to low sulfur coal. Hence forcing due to emissions from 1970 to 2000 and CO2 emitted previously was strongly positive and contributed to rapid global and especially NHml warming. Most recently, new construction in China and India has increased rapidly with minimal application of pollution controls. Continuation of this trend would add negative near-term global mean climate forcing but severely degrade air quality. Conversely, following the Western and Japanese pattern of imposing air quality pollution controls at a later time could accelerate future warming rates, especially at NHmls. More broadly, our results indicate that due to spatial and temporal inhomogeneities in forcing, climate impacts of multi-pollutant emissions can vary strongly from region to region and can include substantial effects on maximum rate-of-change, neither of which are captured by commonly used global metrics. The method we introduce here to estimate regional temperature responses may provide additional insight.

Shindell, D.↗

NASA NTRS2012

The Aerosol-Monsoon Climate System of Asia

In Asian monsoon countries such as China and India, human health and safety problems caused by air-pollution are worsening due to the increased loading of atmospheric pollutants stemming from rising energy demand associated with the rapid pace of industrialization and modernization. Meanwhile, uneven distribution of monsoon rain associated with flash flood or prolonged drought, has caused major loss of human lives, and damages in crop and properties with devastating societal impacts on Asian countries. Historically, air-pollution and monsoon research are treated as separate problems. However a growing number of recent studies have suggested that the two problems may be intrinsically intertwined and need to be studied jointly. Because of complexity of the dynamics of the monsoon systems, aerosol impacts on monsoons and vice versa must be studied and understood in the context of aerosol forcing in relationship to changes in fundamental driving forces of the monsoon climate system (e.g. sea surface temperature, land-sea contrast etc.) on time scales from intraseasonal variability (~weeks) to climate change (~ multi-decades). Indeed, because of the large contributions of aerosols to the global and regional energy balance of the atmosphere and earth surface, and possible effects of the microphysics of clouds and precipitation, a better understanding of the response to climate change in Asian monsoon regions requires that aerosols be considered as an integral component of a fully coupled aerosol-monsoon system on all time scales. In this paper, using observations and results from climate modeling, we will discuss the coherent variability of the coupled aerosol-monsoon climate system in South Asia and East Asia, including aerosol distribution and types, with respect to rainfall, moisture, winds, land-sea thermal contrast, heat sources and sink distributions in the atmosphere in seasonal, interannual to climate change time scales. We will show examples of how elevated absorbing aerosols (dust and black carbon) may interact with monsoon dynamics to produce feedback effects on the atmospheric water cycle, leading to in accelerated melting of snowpacks over the Himalayas and Tibetan Plateau, and subsequent changes in evolution of the pre-monsoon and peak monsoon rainfall, moisture and wind distributions in South Asia and East Asia.

Lau, William K. M.↗

NASA NTRS2012

Climate Variability and Weather Extremes: Model-Simulated and Historical Data

Extremes in weather and climate encompass a wide array of phenomena including tropical storms, mesoscale convective systems, snowstorms, floods, heat waves, and drought. Understanding how such extremes might change in the future requires an understanding of their past behavior including their connections to large-scale climate variability and trends. Previous studies suggest that the most robust findings concerning changes in short-term extremes are those that can be most directly (though not completely) tied to the increase in the global mean temperatures. These include the findings that (IPCC 2007): There has been a widespread reduction in the number of frost days in mid-latitude regions in recent decades, an increase in the number of warm extremes, particularly warm nights, and a reduction in the number of cold extremes, particularly cold nights. For North America in particular (CCSP SAP 3.3, 2008): There are fewer unusually cold days during the last few decades. The last 10 years have seen a lower number of severe cold waves than for any other 10-year period in the historical record that dates back to 1895. There has been a decrease in the number of frost days and a lengthening of the frost-free season, particularly in the western part of North America. Other aspects of extremes such as the changes in storminess have a less clear signature of long term change, with considerable interannual, and decadal variability that can obscure any climate change signal. Nevertheless, regarding extratropical storms (CCSP SAP 3.3, 2008): The balance of evidence suggests that there has been a northward shift in the tracks of strong low pressure systems (storms) in both the North Atlantic and North Pacific basins. For North America: Regional analyses suggest that there has been a decrease in snowstorms in the South and lower Midwest of the United States, and an increase in snowstorms in the upper Midwest and Northeast. Despite the progress already made, our understanding of the basic mechanisms by which extremes vary is incomplete. As noted in IPCC (2007), Incomplete global data sets and remaining model uncertainties still restrict understanding of changes in extremes and attribution of changes to causes, although understanding of changes in the intensity, frequency and risk of extremes has improved. Separating decadal and other shorter-term variability from climate change impacts on extremes requires a better understanding of the processes responsible for the changes. In particular, the physical processes linking sea surface temperature changes to regional climate changes, and a basic understanding of the inherent variability in weather extremes and how that is impacted by atmospheric circulation changes at subseasonal to decadal and longer time scales, are still inadequately understood. Given the fundamental limitations in the time span and quality of global observations, substantial progress on these issues will rely increasingly on improvements in models, with observations continuing to play a critical role, though less as a detection tool, and more as a tool for addressing physical processes, and to insure the quality of the climate models and the verisimilitude of the simulations (CCSP SAP 1.3, 2008).

Schubert, Siegfried D.↗

NASA NTRS2012

Climate Change Impacts on the Built Environment in the United States and Implications for Sustainability

As an integral part of the National Climate Assessment (NCA), technical assessment reports for 13 regions in the U.S. that describe the scientific rationale to support climate change impacts within the purview of these regions, and provide adaptation or mitigation measures in response to these impacts. These technical assessments focus on climate change impacts on sectors that are important environmental, biophysical, and social and economic aspects of sustainability within the U.S.: Climate change science, Ecosystems and biodiversity, Water resources, Human health, Energy supply and use, Water/energy/land use, Transportation, Urban/infrastructure/vulnerability, Agriculture, Impacts of climate change on tribal/indigenous and native lands and resources, Forestry, Land use/land cover change, Rural communities development, and Impacts on biogeochemical cycles, with implications for ecosystems and biodiversity. There is a critical and timely need for the development of mitigation and adaptation strategies in response to climate change by the policy and decision making communities, to insure resiliency and sustainability of the built environment in the future.

Quattrochi, Dale A.↗

NASA NTRS2013

It's the Heat AND the Humidity -- Assessment of Extreme Heat Scenarios to Enable the Assessment of Climate Impacts on Public Health

In the United States, extreme heat is the most deadly weather-related hazard. In the face of a warming climate and urbanization, which contributes to local-scale urban heat islands, it is very likely that extreme heat events (EHEs) will become more common and more severe in the U.S. In a NASA-funded project supporting the National Climate Assessment, we are providing historical and future measures of extreme heat to enable assessments of the impacts of heat on public health over the coterminous U.S. We use atmospheric temperature and humidity information from meteorological reanalysis and from Global Climate Models (GCMs) to provide data on past and future heat events. The project s emphasis is on providing assessments of the magnitude, frequency and geographic distribution of extreme heat in the U.S. to facilitate public health studies. In our approach, long-term climate change is captured with GCM output, and the temporal and spatial characteristics of short-term extremes are represented by the reanalysis data. Two future time horizons, 2040 and 2090, are the focus of future assessments; these are compared to the recent past period of 1981-2000. We are characterizing regional-scale temperature and humidity conditions using GCM output for two climate change scenarios (A2 and A1B) defined in the Special Report on Emissions Scenarios (SRES). For each future period, 20 years of multi-model GCM output have been analyzed to develop a heat stress climatology based on statistics of extreme heat indicators. Differences between the two future and past periods have been used to define temperature and humidity changes on a monthly time scale and regional spatial scale. These changes, combined with hourly historical meteorological data at a spatial scale (12 km) much finer than that of GCMs, enable us to create future climate realizations, from which we compute the daily heat stress measures and related spatially-specific climatological fields. These include the mean annual number of days above certain thresholds of maximum and minimum air temperatures, heat indices and a new heat stress variable that gives an integrated measure of heat stress (and relief) over the course of a day. Comparisons are made between projected (2040 and 2090) and past (1990) heat stress statistics. All output is being provided at the 12 km spatial scale and will also be aggregated to the county level, which is a popular scale of analysis for public health researchers. County-level statistics will be made available by our collaborators at the Centers for Disease Control and Prevention (CDC) via the Wide-ranging Online Data for Epidemiologic Research (WONDER) system. CDC WONDER makes the information resources of the CDC available to public health professionals and the general public. This addition of heat stress measures to CDC WONDER will allow decision and policy makers to assess the impact of alternative approaches to optimize the public health response to EHEs. It will also allow public health researchers and policy makers to better include such heat stress measures in the context of national health data available in the CDC WONDER system. The users will be able to spatially and temporally query public health and heat-related data sets and create county-level maps and statistical charts of such data across the coterminous U.S.

Crosson, William L↗

NASA NTRS2012

Does Dynamical Downscaling Introduce Novel Information in Climate Model Simulations of Recipitation Change over a Complex Topography Region?

Current climate and future climate-warming runs with the RegCM Regional Climate Model (RCM) at 50 and 11 km-resolutions forced by the ECHAM GCM are used to examine whether the increased resolution of the RCM introduces novel information in the precipitation field when the models are run for the mountainous region of the Hellenic peninsula. The model results are inter-compared with the resolution of the RCM output degraded to match that of the GCM, and it is found that in both the present and future climate runs the regional models produce more precipitation than the forcing GCM. At the same time, the RCM runs produce increases in precipitation with climate warming even though they are forced with a GCM that shows no precipitation change in the region. The additional precipitation is mostly concentrated over the mountain ranges, where orographic precipitation formation is expected to be a dominant mechanism. It is found that, when examined at the same resolution, the elevation heights of the GCM are lower than those of the averaged RCM in the areas of the main mountain ranges. It is also found that the majority of the difference in precipitation between the RCM and the GCM can be explained by their difference in topographic height. The study results indicate that, in complex topography regions, GCM predictions of precipitation change with climate warming may be dry biased due to the GCM smoothing of the regional topography.

Tselioudis, George↗

NASA NTRS2013

Future Extreme Heat Scenarios to Enable the Assessment of Climate Impacts on Public Health over the Coterminous U.S.

In the United States, extreme heat is the most deadly weather-related hazard. In the face of a warming climate and urbanization, which contributes to local-scale urban heat islands, it is very likely that extreme heat events (EHEs) will become more common and more severe in the U.S. This research seeks to provide historical and future measures of climate-driven extreme heat events to enable assessments of the impacts of heat on public health over the coterminous U.S. We use atmospheric temperature and humidity information from meteorological reanalysis and from Global Climate Models (GCMs) to provide data on past and future heat events. The focus of research is on providing assessments of the magnitude, frequency and geographic distribution of extreme heat in the U.S. to facilitate public health studies. In our approach, long-term climate change is captured with GCM outputs, and the temporal and spatial characteristics of short-term extremes are represented by the reanalysis data. Two future time horizons for 2040 and 2090 are compared to the recent past period of 1981- 2000. We characterize regional-scale temperature and humidity conditions using GCM outputs for two climate change scenarios (A2 and A1B) defined in the Special Report on Emissions Scenarios (SRES). For each future period, 20 years of multi-model GCM outputs are analyzed to develop a 'heat stress climatology' based on statistics of extreme heat indicators. Differences between the two future and the past period are used to define temperature and humidity changes on a monthly time scale and regional spatial scale. These changes are combined with the historical meteorological data, which is hourly and at a spatial scale (12 km), to create future climate realizations. From these realizations, we compute the daily heat stress measures and related spatially-specific climatological fields, such as the mean annual number of days above certain thresholds of maximum and minimum air temperatures, heat indices and a new heat stress variable developed as part of this research that gives an integrated measure of heat stress (and relief) over the course of a day. Comparisons are made between projected (2040 and 2090) and past (1990) heat stress statistics. Outputs are aggregated to the county level, which is a popular scale of analysis for public health interests. County-level statistics are made available to public health researchers by the Centers for Disease Control and Prevention (CDC) via the Wideranging Online Data for Epidemiologic Research (WONDER) system. This addition of heat stress measures to CDC WONDER allows decision and policy makers to assess the impact of alternative approaches to optimize the public health response to EHEs. Through CDC WONDER, users are able to spatially and temporally query public health and heat-related data sets and create county-level maps and statistical charts of such data across the coterminous U.S

Quattrochi, Dale A.↗

NASA NTRS2014

Climate Scenarios for the NASA / USAID SERVIR Project: Challenges for Multiple Planning Horizons

SERVIR, an acronym meaning "to serve" in Spanish, is a joint venture between NASA and the U.S. Agency for International Development (USAID) which provides satellite-based Earth observation data, modeling, and science applications to help developing nations in Central America, East Africa and the Himalayas improve environmental decision making. Anticipating climate variability / climate change impacts has now become an important component of the SERVIR efforts to build capacity in these regions. Uncertainty in hydrometeorological components of climate variations and exposure to extreme events across scales from weather to climate are of particular concern. We report here on work to construct scenarios or outlooks that are being developed as input drivers for decision support systems (DSSs) in a variety of settings. These DSSs are being developed jointly by a broad array NASA Applied Science Team (AST) Investigations and user communities in the three SERVIR Hub Regions, Central America, East Africa and the Himalayas. Issues span hydrologic / water resources modeling, agricultural productivity, and forest carbon reserves. The scenarios needed for these efforts encompass seasonal forecasts, interannual outlooks, and likely decadal / multi-decadal trends. Providing these scenarios across the different AST efforts enables some level of integration in considering regional responses to climate events. We will discuss a number of challenges in developing this continuum of scenarios including the identification and "mining" of predictability, addressing multiple continental regions, issues of downscaling global model integrations to regional / local applications (i.e. hydrologic and crop modeling). We compare / contrast the role of the U.S. National Multi- Model Experiment initiative in seasonal forecasts and the CMIP-5 climate model experiments in supporting these efforts. Examples of these scenarios, their use, and an assessment of their utility as well as limitations will be presented.

Robertson, Franklin R.↗

NASA NTRS2016

Demonstrating the Error Budget for the Climate Absolute Radiance and Refractivity Observatory Through Solar Irradiance Measurements

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission addresses the need to observe highaccuracy, long-term climate change trends and to use decadal change observations as a method to determine the accuracy of climate change. A CLARREO objective is to improve the accuracy of SI-traceable, absolute calibration at infrared and reflected solar wavelengths to reach on-orbit accuracies required to allow climate change observations to survive data gaps and observe climate change at the limit of natural variability. Such an effort will also demonstrate National Institute of Standards and Technology (NIST) approaches for use in future spaceborne instruments. The current work describes the results of laboratory and field measurements with the Solar, Lunar for Absolute Reflectance Imaging Spectroradiometer (SOLARIS) which is the calibration demonstration system (CDS) for the reflected solar portion of CLARREO. SOLARIS allows testing and evaluation of calibration approaches, alternate design and/or implementation approaches and components for the CLARREO mission. SOLARIS also provides a test-bed for detector technologies, non-linearity determination and uncertainties, and application of future technology developments and suggested spacecraft instrument design modifications. Results of laboratory calibration measurements are provided to demonstrate key assumptions about instrument behavior that are needed to achieve CLARREO's climate measurement requirements. Absolute radiometric response is determined using laser-based calibration sources and applied to direct solar views for comparison with accepted solar irradiance models to demonstrate accuracy values giving confidence in the error budget for the CLARREO reflectance retrieval.

CLARREO↗

NASA NTRS2015

How Difficult is it to Reduce Low-Level Cloud Biases With the Higher-Order Turbulence Closure Approach in Climate Models?

Low-level clouds cover nearly half of the Earth and play a critical role in regulating the energy and hydrological cycle. Despite the fact that a great effort has been put to advance the modeling and observational capability in recent years, low-level clouds remains one of the largest uncertainties in the projection of future climate change. Low-level cloud feedbacks dominate the uncertainty in the total cloud feedback in climate sensitivity and projection studies. These clouds are notoriously difficult to simulate in climate models due to its complicated interactions with aerosols, cloud microphysics, boundary-layer turbulence and cloud dynamics. The biases in both low cloud coverage/water content and cloud radiative effects (CREs) remain large. A simultaneous reduction in both cloud and CRE biases remains elusive. This presentation first reviews the effort of implementing the higher-order turbulence closure (HOC) approach to representing subgrid-scale turbulence and low-level cloud processes in climate models. There are two HOCs that have been implemented in climate models. They differ in how many three-order moments are used. The CLUBB are implemented in both CAM5 and GDFL models, which are compared with IPHOC that is implemented in CAM5 by our group. IPHOC uses three third-order moments while CLUBB only uses one third-order moment while both use a joint double-Gaussian distribution to represent the subgrid-scale variability. Despite that HOC is more physically consistent and produces more realistic low-cloud geographic distributions and transitions between cumulus and stratocumulus regimes, GCMs with traditional cloud parameterizations outperform in CREs because tuning of this type of models is more extensively performed than those with HOCs. We perform several tuning experiments with CAM5 implemented with IPHOC in an attempt to produce the nearly balanced global radiative budgets without deteriorating the low-cloud simulation. One of the issues in CAM5-IPHOC is that cloud water content is much higher than in CAM5, which is combined with higher low-cloud coverage to produce larger shortwave CREs in some low-cloud prevailing regions. Thus, the cloud-radiative feedbacks are exaggerated there. The turning exercise is focused on microphysical parameters, which are also commonly used for tuning in climate models. The results will be discussed in this presentation.

Xu, Kuan-Man↗

NASA NTRS2016

Role of Atmospheric Chemistry in the Climate Impacts of Stratospheric Volcanic Injections

The climate impact of a volcanic eruption is known to be dependent on the size, location and timing of the eruption. However, the chemistry and composition of the volcanic plume also control its impact on climate. It is not just sulfur dioxide gas, but also the coincident emissions of water, halogens and ash that influence the radiative and climate forcing of an eruption. Improvements in the capability of models to capture aerosol microphysics, and the inclusion of chemistry and aerosol microphysics modules in Earth system models, allow us to evaluate the interaction of composition and chemistry within volcanic plumes in a new way. These modeling efforts also illustrate the role of water vapor in controlling the chemical evolution, and hence climate impacts, of the plume. A growing realization of the importance of the chemical composition of volcanic plumes is leading to a more sophisticated and realistic representation of volcanic forcing in climate simulations, which in turn aids in reconciling simulations and proxy reconstructions of the climate impacts of past volcanic eruptions. More sophisticated simulations are expected to help, eventually, with predictions of the impact on the Earth system of any future large volcanic eruptions.

Disrupting↗

NASA NTRS2016

GC23G-1310: Investigation Into the Effects of Climate Variability and Land Cover Change on the Hydrologic System of the Lower Mekong Basin

The Lower Mekong Basin (LMB) is an economically and ecologically important region that experiences hydrologic hazards such as floods and droughts, which can directly affect human well-being and limit economic growth and development. To effectively develop long-term plans for addressing hydrologic hazards, the regional hydrological response to climate variability and land cover change needs to be evaluated. This research aims to investigate how climate variability, specifically variations in the precipitation regime, and land cover change will affect hydrologic parameters both spatially and temporally within the LMB. The research goal is achieved by (1) modeling land cover change for a baseline land cover change scenario as well as changes in land cover with increases in forest or agriculture and (2) using projected climate variables and modeled land cover data as inputs into the Variable Infiltration Capacity (VIC) hydrologic model to simulate the changes to the hydrologic system. The VIC model outputs were analyzed against historic values to understand the relative contribution of climate variability and land cover to change, where these changes occur, and to what degree these changes affect the hydrology. This study found that the LMB hydrologic system is more sensitive to climate variability than land cover change. On average, climate variability was found to increase discharge and evapotranspiration (ET) while decreasing water storage. The change in land cover show that increasing forest area will slightly decrease discharge and increase ET while increasing agriculture area increases discharge and decreases ET. These findings will help the LMB by supporting individual country policy to plan for future hydrologic changes as well as policy for the basin as a whole.

Hydrology↗