Satellite lidar and radar: Key components of the future climate observing system

NASA Astrophysics Data System (ADS)

Winker, D. M.

2017-12-01

Cloud feedbacks represent the dominant source of uncertainties in estimates of climate sensitivity and aerosols represent the largest source of uncertainty in climate forcing. Both observation of long-term changes and observational constraints on the processes responsible for those changes are necessary. The existing 30-year record of passive satellite observations has not yet provided constraints to significantly reduce these uncertainties, though. We now have more than a decade of experience with active sensors flying in the A-Train. These new observations have demonstrated the strengths of active sensors and the benefits of continued and more advanced active sensors. This talk will discuss the multiple roles for active sensors as an essential component of a global climate observing system.

Linking the Observation of Essential Variables to Societal Benefits

NASA Astrophysics Data System (ADS)

Sylak-Glassman, E.

2017-12-01

Different scientific communities have established sets of commonly agreed upon essential variables to help coordinate data collection in a variety of Earth observation areas. As an example, the World Meteorological Organization Global Climate Observing System has identified 50 Essential Climate Variables (ECVs), such as sea-surface temperature and carbon dioxide, which are required to monitoring the climate and detect and attribute climate change. In addition to supporting climate science, measuring these ECVs deliver many types of societal benefits, ranging from disaster mitigation to agricultural productivity to human health. While communicating the value in maintaining and improving observational records for these variables has been a challenge, quantifying how the measurement of these ECVs results in the delivery of many different societal benefits may help support their continued measurement. The 2016 National Earth Observation Assessment (EOA 2016) quantified the impact of individual Earth observation systems, sensors, networks, and surveys (or Earth observation systems, for short) on the achievement of 217 Federal objectives in 13 societal benefit areas (SBAs). This study will demonstrate the use of the EOA 2016 dataset to show the different Federal objectives and SBAs that are impacted by the Earth observation systems used to measure ECVs. Describing how the measurements from these Earth observation systems are used not only to maintain the climate record but also to meet additional Federal objectives may help articulate the continued measurement of the ECVs. This study will act as a pilot for the use of the EOA 2016 dataset to map between the measurements required to observe additional sets of variables, such as the Essential Ocean Variables and Essential Biodiversity Variables, and the ability to achieve a variety of societal benefits.

Carbon cycle observations: gaps threaten climate mitigation policies

Treesearch

Richard Birdsey; Nick Bates; MIke Behrenfeld; Kenneth Davis; Scott C. Doney; Richard Feely; Dennis Hansell; Linda Heath; et al.

2009-01-01

Successful management of carbon dioxide (CO2) requires robust and sustained carbon cycle observations. Yet key elements of a national observation network are lacking or at risk. A U.S. National Research Council review of the U.S. Climate Change Science Program earlier this year highlighted the critical need for a U.S. climate observing system to...

Observational Constraints on Cloud Feedbacks: The Role of Active Satellite Sensors

NASA Astrophysics Data System (ADS)

Winker, David; Chepfer, Helene; Noel, Vincent; Cai, Xia

2017-11-01

Cloud profiling from active lidar and radar in the A-train satellite constellation has significantly advanced our understanding of clouds and their role in the climate system. Nevertheless, the response of clouds to a warming climate remains one of the largest uncertainties in predicting climate change and for the development of adaptions to change. Both observation of long-term changes and observational constraints on the processes responsible for those changes are necessary. We review recent progress in our understanding of the cloud feedback problem. Capabilities and advantages of active sensors for observing clouds are discussed, along with the importance of active sensors for deriving constraints on cloud feedbacks as an essential component of a global climate observing system.

Characterization of the Dynamics of Climate Systems and Identification of Missing Mechanisms Impacting the Long Term Predictive Capabilities of Global Climate Models Utilizing Dynamical Systems Approaches to the Analysis of Observed and Modeled Climate

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

Bhatt, Uma S.; Wackerbauer, Renate; Polyakov, Igor V.

The goal of this research was to apply fractional and non-linear analysis techniques in order to develop a more complete characterization of climate change and variability for the oceanic, sea ice and atmospheric components of the Earth System. This research applied two measures of dynamical characteristics of time series, the R/S method of calculating the Hurst exponent and Renyi entropy, to observational and modeled climate data in order to evaluate how well climate models capture the long-term dynamics evident in observations. Fractional diffusion analysis was applied to ARGO ocean buoy data to quantify ocean transport. Self organized maps were appliedmore » to North Pacific sea level pressure and analyzed in ways to improve seasonal predictability for Alaska fire weather. This body of research shows that these methods can be used to evaluate climate models and shed light on climate mechanisms (i.e., understanding why something happens). With further research, these methods show promise for improving seasonal to longer time scale forecasts of climate.« less

On the Reprocessing and Reanalysis of Observations for Climate

NASA Technical Reports Server (NTRS)

Bosilovich, Michael G.; Kennedy, John; Dee, Dick; Allan, R.; O'Neill, Alan

2013-01-01

The long observational record is critical to our understanding of the Earths climate, but most observing systems were not developed with a climate objective in mind. As a result, tremendous efforts have gone into assessing and reprocessing the data records to improve their usefulness in climate studies. The purpose of this paper is to both review recent progress in reprocessing and reanalyzing observations, and to summarize the challenges that must be overcome in order to improve our understanding of climate and variability. Reprocessing improves data quality through more scrutiny and improved retrieval techniques for individual observing systems, while reanalysis merges many disparate observations with models through data assimilation, yet both aim to provide an climatology of Earth processes. Many challenges remain, such as tracking the improvement of processing algorithms and limited spatial coverage. Reanalyses have fostered significant research, yet reliable global trends in many physical fields are not yet attainable, despite significant advances in data assimilation and numerical modeling. Oceanic reanalyses have made significant advances in recent years, but will only be discussed here in terms of progress toward integrated Earth system analyses. Climate data sets are generally adequate for process studies and large-scale climate variability. Communication of the strengths, limitations and uncertainties of reprocessed observations and reanalysis data, not only among the community of developers, but also with the extended research community, including the new generations of researchers and the decision makers is crucial for further advancement of the observational data records. It must be emphasized that careful investigation of the data and processing methods are required to use the observations appropriately.

Extreme weather and climate events with ecological relevance: a review

PubMed Central

Meehl, Gerald A.

2017-01-01

Robust evidence exists that certain extreme weather and climate events, especially daily temperature and precipitation extremes, have changed in regard to intensity and frequency over recent decades. These changes have been linked to human-induced climate change, while the degree to which climate change impacts an individual extreme climate event (ECE) is more difficult to quantify. Rapid progress in event attribution has recently been made through improved understanding of observed and simulated climate variability, methods for event attribution and advances in numerical modelling. Attribution for extreme temperature events is stronger compared with other event types, notably those related to the hydrological cycle. Recent advances in the understanding of ECEs, both in observations and their representation in state-of-the-art climate models, open new opportunities for assessing their effect on human and natural systems. Improved spatial resolution in global climate models and advances in statistical and dynamical downscaling now provide climatic information at appropriate spatial and temporal scales. Together with the continued development of Earth System Models that simulate biogeochemical cycles and interactions with the biosphere at increasing complexity, these make it possible to develop a mechanistic understanding of how ECEs affect biological processes, ecosystem functioning and adaptation capabilities. Limitations in the observational network, both for physical climate system parameters and even more so for long-term ecological monitoring, have hampered progress in understanding bio-physical interactions across a range of scales. New opportunities for assessing how ECEs modulate ecosystem structure and functioning arise from better scientific understanding of ECEs coupled with technological advances in observing systems and instrumentation. This article is part of the themed issue ‘Behavioural, ecological and evolutionary responses to extreme climatic events’. PMID:28483866

Extreme weather and climate events with ecological relevance: a review.

PubMed

Ummenhofer, Caroline C; Meehl, Gerald A

2017-06-19

Robust evidence exists that certain extreme weather and climate events, especially daily temperature and precipitation extremes, have changed in regard to intensity and frequency over recent decades. These changes have been linked to human-induced climate change, while the degree to which climate change impacts an individual extreme climate event (ECE) is more difficult to quantify. Rapid progress in event attribution has recently been made through improved understanding of observed and simulated climate variability, methods for event attribution and advances in numerical modelling. Attribution for extreme temperature events is stronger compared with other event types, notably those related to the hydrological cycle. Recent advances in the understanding of ECEs, both in observations and their representation in state-of-the-art climate models, open new opportunities for assessing their effect on human and natural systems. Improved spatial resolution in global climate models and advances in statistical and dynamical downscaling now provide climatic information at appropriate spatial and temporal scales. Together with the continued development of Earth System Models that simulate biogeochemical cycles and interactions with the biosphere at increasing complexity, these make it possible to develop a mechanistic understanding of how ECEs affect biological processes, ecosystem functioning and adaptation capabilities. Limitations in the observational network, both for physical climate system parameters and even more so for long-term ecological monitoring, have hampered progress in understanding bio-physical interactions across a range of scales. New opportunities for assessing how ECEs modulate ecosystem structure and functioning arise from better scientific understanding of ECEs coupled with technological advances in observing systems and instrumentation.This article is part of the themed issue 'Behavioural, ecological and evolutionary responses to extreme climatic events'. © 2017 The Author(s).

The Impact of Ocean Observations in Seasonal Climate Prediction

NASA Technical Reports Server (NTRS)

Rienecker, Michele; Keppenne, Christian; Kovach, Robin; Marshak, Jelena

2010-01-01

The ocean provides the most significant memory for the climate system. Hence, a critical element in climate forecasting with coupled models is the initialization of the ocean with states from an ocean data assimilation system. Remotely-sensed ocean surface fields (e.g., sea surface topography, SST, winds) are now available for extensive periods and have been used to constrain ocean models to provide a record of climate variations. Since the ocean is virtually opaque to electromagnetic radiation, the assimilation of these satellite data is essential to extracting the maximum information content. More recently, the Argo drifters have provided unprecedented sampling of the subsurface temperature and salinity. Although the duration of this observation set has been too short to provide solid statistical evidence of its impact, there are indications that Argo improves the forecast skill of coupled systems. This presentation will address the impact these different observations have had on seasonal climate predictions with the GMAO's coupled model.

Climate-based seed zones for Mexico: guiding reforestation under observed and projected climate change

Treesearch

Dante Castellanos-Acuña; Kenneth W. Vance-Borland; J. Bradley St. Clair; Andreas Hamann; Javier López-Upton; Erika Gómez-Pineda; Juan Manuel Ortega-Rodríguez; Cuauhtémoc Sáenz-Romero

2018-01-01

Seed zones for forest tree species are a widely used tool in reforestation programs to ensure that seedlings are well adapted to their planting environments. Here, we propose a climate-based seed zone system for Mexico to address observed and projected climate change. The proposed seed zone classification is based on bands of climate variables often related to genetic...

Observing Climate with Satellites - Are We on Thin Ice?

NASA Technical Reports Server (NTRS)

Tucker, Compton

2012-01-01

The Earth s climate is determined by irradiance from the Sun and properties of the atmosphere, oceans, and land that determine the reflection, absorption, and emission of energy within our atmosphere and at the Earth s surface. Since the 1970s, Earth-viewing satellites have complimented non-satellite geophysical observations with consistent, quantitative, and spatially-continuous measurements that have led to an unprecedented understanding of the Earth s climate system. I will describe the Earth s climate system as elaborated by satellite and in situ observations, review arguments against global warming, and show the convergence of evidence for human-caused warming of our planet.

Using climate models to estimate the quality of global observational data sets.

PubMed

Massonnet, François; Bellprat, Omar; Guemas, Virginie; Doblas-Reyes, Francisco J

2016-10-28

Observational estimates of the climate system are essential to monitoring and understanding ongoing climate change and to assessing the quality of climate models used to produce near- and long-term climate information. This study poses the dual and unconventional question: Can climate models be used to assess the quality of observational references? We show that this question not only rests on solid theoretical grounds but also offers insightful applications in practice. By comparing four observational products of sea surface temperature with a large multimodel climate forecast ensemble, we find compelling evidence that models systematically score better against the most recent, advanced, but also most independent product. These results call for generalized procedures of model-observation comparison and provide guidance for a more objective observational data set selection. Copyright © 2016, American Association for the Advancement of Science.

Climate observing system studies: An element of the NASA Climate Research Program: Workshop report

NASA Technical Reports Server (NTRS)

1980-01-01

Plans for NASA's efforts in climatology were discussed. Targets for a comprehensive observing system for the early 1990's were considered. A program to provide useful data in the near and mid-term, and a program to provide for a feasibility assessment of instruments and methods for the development of a long-term system were discussed. Climate parameters that cannot be measured from space were identified. Long-term calibration, intercomparison, standards, and ground truth were discussed.

Toward GEOS-6, A Global Cloud System Resolving Atmospheric Model

NASA Technical Reports Server (NTRS)

Putman, William M.

2010-01-01

NASA is committed to observing and understanding the weather and climate of our home planet through the use of multi-scale modeling systems and space-based observations. Global climate models have evolved to take advantage of the influx of multi- and many-core computing technologies and the availability of large clusters of multi-core microprocessors. GEOS-6 is a next-generation cloud system resolving atmospheric model that will place NASA at the forefront of scientific exploration of our atmosphere and climate. Model simulations with GEOS-6 will produce a realistic representation of our atmosphere on the scale of typical satellite observations, bringing a visual comprehension of model results to a new level among the climate enthusiasts. In preparation for GEOS-6, the agency's flagship Earth System Modeling Framework [JDl] has been enhanced to support cutting-edge high-resolution global climate and weather simulations. Improvements include a cubed-sphere grid that exposes parallelism; a non-hydrostatic finite volume dynamical core, and algorithm designed for co-processor technologies, among others. GEOS-6 represents a fundamental advancement in the capability of global Earth system models. The ability to directly compare global simulations at the resolution of spaceborne satellite images will lead to algorithm improvements and better utilization of space-based observations within the GOES data assimilation system

Science Writers' Guide to TERRA

NASA Technical Reports Server (NTRS)

2000-01-01

The launch of NASA's Terra spacecraft marks a new era of comprehensive monitoring of the Earth's atmosphere, oceans, and continents from a single space-based platform. Data from the five Terra instruments will create continuous, long-term records of the state of the land, oceans, and atmosphere. Together with data from other satellite systems launched by NASA and other countries, Terra will inaugurate a new self-consistent data record that will be gathered over the next 15 years. The science objectives of NASAs Earth Observing System (EOS) program are to provide global observations and scientific understanding of land cover change and global productivity, climate variability and change, natural hazards, and atmospheric ozone. Observations by the Terra instruments will: provide the first global and seasonal measurements of the Earth system, including such critical functions as biological productivity of the land and oceans, snow and ice, surface temperature, clouds, water vapor, and land cover; improve our ability to detect human impacts on the Earth system and climate, identify the "fingerprint" of human activity on climate, and predict climate change by using the new global observations in climate models; help develop technologies for disaster prediction, characterization, and risk reduction from wildfires, volcanoes, floods, and droughts, and start long-term monitoring of global climate change and environmental change.

NASA's mission to planet Earth: Earth observing system

NASA Technical Reports Server (NTRS)

1993-01-01

The topics covered include the following: global climate change; radiation, clouds, and atmospheric water; the ocean; the troposphere - greenhouse gases; land cover and the water cycle; polar ice sheets and sea level; the stratosphere - ozone chemistry; volcanoes; the Earth Observing System (EOS) - how NASA will support studies of global climate change?; research and assessment - EOS Science Investigations; EOS Data and Information System (EOSDIS); EOS observations - instruments and spacecraft; a national international effort; and understanding the Earth System.

Exposure to fall hazards and safety climate in the aircraft maintenance industry.

PubMed

Neitzel, Richard L; Seixas, Noah S; Harris, Michael J; Camp, Janice

2008-01-01

Falls represent a significant occupational hazard, particularly in industries with dynamic work environments. This paper describes rates of noncompliance with fall hazard prevention requirements, perceived safety climate and worker knowledge and beliefs, and the association between fall exposure and safety climate measures in commercial aircraft maintenance activities. Walkthrough observations were conducted on aircraft mechanics at two participating facilities (Sites A and B) to ascertain the degree of noncompliance. Mechanics at each site completed questionnaires concerning fall hazard knowledge, personal safety beliefs, and safety climate. Questionnaire results were summarized into safety climate and belief scores by workgroup and site. Noncompliance rates observed during walkthroughs were compared to the climate-belief scores, and were expected to be inversely associated. Important differences were seen in fall safety performance between the sites. The study provided a characterization of aircraft maintenance fall hazards, and also demonstrated the effectiveness of an objective hazard assessment methodology. Noncompliance varied by height, equipment used, location of work on the aircraft, shift, and by safety system. Although the expected relationship between safety climate and noncompliance was seen for site-average climate scores, workgroups with higher safety climate scores had greater observed noncompliance within Site A. Overall, use of engineered safety systems had a significant impact on working safely, while safety beliefs and climate also contributed, though inconsistently. The results of this study indicate that safety systems are very important in reducing noncompliance with fall protection requirements in aircraft maintenance facilities. Site-level fall safety compliance was found to be related to safety climate, although an unexpected relationship between compliance and safety climate was seen at the workgroup level within site. Finally, observed fall safety compliance was found to differ from self-reported compliance.

Climate Information Responding to User Needs (CIRUN)

NASA Astrophysics Data System (ADS)

Busalacchi, A. J.

2009-05-01

For the past several decades many different US agencies have been involved in collecting Earth observations, e.g., NASA, NOAA, DoD, USGS, USDA. More recently, the US has led the international effort to design a Global Earth Observation System of Systems (GEOSS). Yet, there has been little substantive progress at the synthesis and integration of the various research and operational, space-based and in situ, observations. Similarly, access to such a range of observations across the atmosphere, ocean, and land surface remains fragmented. With respect to prediction of the Earth System, the US has not developed a comprehensive strategy. For climate, the US (e.g., NOAA, NASA, DoE) has taken a two-track strategy. At the more immediate time scale, coupled ocean-atmosphere models of the physical climate system have built upon the tradition of daily numerical weather prediction in order to extend the forecast window to seasonal to interannual times scales. At the century time scale, the nascent development of Earth System models, combining components of the physical climate system with biogeochemical cycles, are being used to provide future climate change projections in response to anticipated greenhouse gas forcings. Between these to two approaches to prediction lies a key deficiency of interest to decision makers, especially as it pertains to adaptation, i.e., deterministic prediction of the Earth System at time scales from days to decades with spatial scales from global to regional. One of many obstacles to be overcome is the design of present day observation and prediction products based on user needs. To date, most of such products have evolved from the technology and research "push" rather than the user or stakeholder "pull". In the future as planning proceeds for a national climate service, emphasis must be given to a more coordinated approach in which stakeholders' needs help design future Earth System observational and prediction products, and similarly, such products need to be tailored to provide decision support.

Assessing the observed impact of anthropogenic climate change

DOE PAGES

Hansen, Gerrit; Stone, Dáithí

2015-12-21

Impacts of recent regional changes in climate on natural and human systems are documented across the globe, yet studies explicitly linking these observations to anthropogenic forcing of the climate are scarce. Here in this work, we provide a systematic assessment of the role of anthropogenic climate change for the range of impacts of regional climate trends reported in the IPCC’s Fifth Assessment Report. We find that almost two-thirds of the impacts related to atmospheric and ocean temperature can be confidently attributed to anthropogenic forcing. In contrast, evidence connecting changes in precipitation and their respective impacts to human influence is stillmore » weak. Moreover, anthropogenic climate change has been a major influence for approximately three-quarters of the impacts observed on continental scales. Finally, hence the effects of anthropogenic emissions can now be discerned not only globally, but also at more regional and local scales for a variety of natural and human systems.« less

Climate Informatics

NASA Technical Reports Server (NTRS)

Monteleoni, Claire; Schmidt, Gavin A.; Alexander, Francis J.; Niculescu-Mizil, Alexandru; Steinhaeuser, Karsten; Tippett, Michael; Banerjee, Arindam; Blumenthal, M. Benno; Ganguly, Auroop R.; Smerdon, Jason E.;

Economic Value of an Advanced Climate Observing System

NASA Astrophysics Data System (ADS)

Wielicki, B. A.; Cooke, R.; Young, D. F.; Mlynczak, M. G.

2013-12-01

Scientific missions increasingly need to show the monetary value of knowledge advances in budget-constrained environments. For example, suppose a climate science mission promises to yield decisive information on the rate of human caused global warming within a shortened time frame. How much should society be willing to pay for this knowledge today? The US interagency memo on the social cost of carbon (SCC) creates a standard yardstick for valuing damages from carbon emissions. We illustrate how value of information (VOI) calculations can be used to monetize the relative value of different climate observations. We follow the SCC, setting uncertainty in climate sensitivity to a truncated Roe and Baker (2007) distribution, setting discount rates of 2.5%, 3% and 5%, and using one of the Integrated Assessment Models sanctioned in SCC (DICE, Nordhaus 2008). We consider three mitigation scenarios: Business as Usual (BAU), a moderate mitigation response DICE Optimal, and a strong response scenario (Stern). To illustrate results, suppose that we are on the BAU emissions scenario, and that we would switch to the Stern emissions path if we learn with 90% confidence that the decadal rate of temperature change reaches or exceeds 0.2 C/decade. Under the SCC assumptions, the year in which this happens, if it happens, depends on the uncertain climate sensitivity and on the emissions path. The year in which we become 90% certain that it happens depends, in addition, on our Earth observations, their accuracy, and their completeness. The basic concept is that more accurate observations can shorten the time for societal decisions. The economic value of the resulting averted damages depends on the discount rate, and the years in which the damages occur. A new climate observation would be economically justified if the net present value (NPV) of the difference in averted damages, relative to the existing systems, exceeds the NPV of the system costs. Our results (Cooke et al. 2013) compared the proposed CLARREO advance in satellite absolute calibration for climate change records to an existing system for detecting decadal temperature change using infrared spectra from weather satellites. New results extend this to observational detection of cloud feedback which is the largest uncertainty in determining climate sensitivity and therefore the uncertainty in economic impacts. New results also include the use of multiple societal decision triggers. While CLARREO is used as an example, the value should be considered as relevant to a complete high accuracy climate observing system, as societal decisions are unlikely to be based on one or a few observations. The VOI is found to depend on the required confidence level, the trigger value at which we would abandon the BAU emissions path, the path to which we switch, and the date at which the new system is launched. The VOI of advanced climate observations in this decision context is the surfeit of NPV of averted damages, relative to the existing system. Over all it is in the order of tens of trillions of US dollars in Net Present Value. The results conclude that the economic value of advanced climate observing systems is dramatically larger than their cost, and argues for the continual enhancement of the SCC assessment process.

A perspective on sustained marine observations for climate modelling and prediction

PubMed Central

Dunstone, Nick J.

2014-01-01

Here, I examine some of the many varied ways in which sustained global ocean observations are used in numerical modelling activities. In particular, I focus on the use of ocean observations to initialize predictions in ocean and climate models. Examples are also shown of how models can be used to assess the impact of both current ocean observations and to simulate that of potential new ocean observing platforms. The ocean has never been better observed than it is today and similarly ocean models have never been as capable at representing the real ocean as they are now. However, there remain important unanswered questions that can likely only be addressed via future improvements in ocean observations. In particular, ocean observing systems need to respond to the needs of the burgeoning field of near-term climate predictions. Although new ocean observing platforms promise exciting new discoveries, there is a delicate balance to be made between their funding and that of the current ocean observing system. Here, I identify the need to secure long-term funding for ocean observing platforms as they mature, from a mainly research exercise to an operational system for sustained observation over climate change time scales. At the same time, considerable progress continues to be made via ship-based observing campaigns and I highlight some that are dedicated to addressing uncertainties in key ocean model parametrizations. The use of ocean observations to understand the prominent long time scale changes observed in the North Atlantic is another focus of this paper. The exciting first decade of monitoring of the Atlantic meridional overturning circulation by the RAPID-MOCHA array is highlighted. The use of ocean and climate models as tools to further probe the drivers of variability seen in such time series is another exciting development. I also discuss the need for a concerted combined effort from climate models and ocean observations in order to understand the current slow-down in surface global warming. PMID:25157195

Climate change effects on North American inland fish populations and assemblages

USGS Publications Warehouse

Lynch, Abigail J.; Myers, Bonnie; Chu, Cindy; Eby, Lisa A.; Falke, Jeffrey A.; Kovach, Ryan P.; Krabbenhoft, Trevor J.; Kwak, Thomas J.; Lyons, John; Paukert, Craig P.; Whitney, James E.

2016-01-01

Climate is a critical driver of many fish populations, assemblages, and aquatic communities. However, direct observational studies of climate change impacts on North American inland fishes are rare. In this synthesis, we (1) summarize climate trends that may influence North American inland fish populations and assemblages, (2) compile 31 peer-reviewed studies of documented climate change effects on North American inland fish populations and assemblages, and (3) highlight four case studies representing a variety of observed responses ranging from warmwater systems in the southwestern and southeastern United States to coldwater systems along the Pacific Coast and Canadian Shield. We conclude by identifying key data gaps and research needs to inform adaptive, ecosystem-based approaches to managing North American inland fishes and fisheries in a changing climate.

International Collaboration in the field of GNSS-Meteorology and Climate Monitoring

NASA Astrophysics Data System (ADS)

Jones, J.; Guerova, G.; Dousa, J.; Bock, O.; Elgered, G.; Vedel, H.; Pottiaux, E.; de Haan, S.; Pacione, R.; Dick, G.; Wang, J.; Gutman, S. I.; Wickert, J.; Rannat, K.; Liu, G.; Braun, J. J.; Shoji, Y.

2012-12-01

International collaboration in the field of GNSS-meteorology and climate monitoring is essential, as severe weather and climate change have no respect for national boundaries. The use of Global Navigation Satellite Systems (GNSS) for meteorological purposes is an established atmospheric observing technique, which can accurately sense water vapour, the most abundant greenhouse gas, accounting for 60-70% of atmospheric warming. Severe weather forecasting is challenging, in part due to the high temporal and spatial variation of atmospheric water vapour. Water vapour is currently under-sampled and obtaining and exploiting more high-quality humidity observations is essential to severe weather forecasting and climate monitoring. A proposed EU COST Action (http://www.cost.eu) will address new and improved capabilities from concurrent developments in both GNSS and atmospheric communities to improve (short-range) weather forecasts and climate projections. For the first time, the synergy of the three GNSS systems, GPS, GLONASS and Galileo, will be used to develop new, advanced tropospheric products, stimulating the full potential exploitation of multi-GNSS water vapour estimates on a wide range of temporal and spatial scales, from real-time severe weather monitoring and forecasting to climate research. The Action will work in close collaboration with the Global Climate Observing System (GCOS) Reference Upper Air Network (GRUAN), GNSS Precipitable Water Task Team (TT). GRUAN is a global reference observing network, designed to meet climate requirements and to fill a major void in the current global observing system. GRUAN observations will provide long-term, high-quality data to determine climatic trends and to constrain and validate data from space-based remote sensors. Ground-based GNSS PW was identified as a Priority 1 measurement for GRUAN, and the GNSS-PW TT's goal is to develop explicit guidance on hardware, software and data management practices to obtain GNSS PW measurements of consistent quality at all GRUAN sites. The GRUAN GNSS-PW TT and the proposed COST Action will look to expand the international framework already in place with the European E-GVAP programme to facilitate global collaboration to facilitate knowledge and data exchange.

The Borderlands and climate change: Chapter 10 in United States-Mexican Borderlands: Facing tomorrow's challenges through USGS science

USGS Publications Warehouse

Fitzpatrick, Joan; Gray, Floyd; Dubiel, Russell; Langman, Jeff; Moring, J. Bruce; Norman, Laura M.; Page, William R.; Parcher, Jean W.

2013-01-01

The prediction of global climate change in response to both natural forces and human activity is one of the defining issues of our times. The unprecedented observational capacity of modern earth-orbiting satellites coupled with the development of robust computational representations (models) of the Earth’s weather and climate systems afford us the opportunity to observe and investigate how these systems work now, how they have worked in the past, and how they will work in the future when forced in specific ways. In the most recent report on global climate change by the Intergovernmental Panel on Climate Change (IPCC; Solomon and others, 2007), analyses using multiple climate models support recent observations that the Earth’s climate is changing in response to a combination of natural and human-induced causes. These changes will be significant in the United States–Mexican border region, where the process of climate change affects all of the Borderlands challenge themes discussed in the preceding chapters. The dual possibilities of both significantly-changed climate and increasing variability in climate make it challenging to take full measure of the potential effects because the Borderlands already experience a high degree of interannual variability and climatological extremes.

Complexity of Tropical Pacific Ecosystem and Biogeochemistry: Diurnal to Decadal, Plankters to Penguins

NASA Astrophysics Data System (ADS)

Murtugudde, R. G.; Wang, X.; Valsala, V.; Karnauskas, K. B.

2016-12-01

Tropical Pacific spans nearly 50% of the global tropics allowing to have its own mind in terms of climate variability and physical-biogeochemical interactions. While the El Niño-Southern Oscillation (ENSO) and its flavors get much attention, it is fairly clear by now that any further improvements in ENSO prediction skills and reliability of global warming projections must begin to observe and represent bio-physical interactions in the climate and Earth System models. Coupled climate variability over the tropical Pacific has a global reach with its diurnal to decadal timescales being manifest in ecosystem and biogechemistry. Zonal and meridional contrasts in biogeochemistry across the tropical Pacific is closely related to seasonal variability, ENSO diversity and the PDO. Apparent dominance of ocean dynamic controls on biogeochemistry belies the potential biogeochemical feedbacks on ocean dynamics which may well explain some of the chronic biases in the state-of-the-art climate models. The east Pacific cold-tongue is the most productive open ocean region in the world and home to a unique physical-biogeochmical laboratory, viz., the Galapagos. The Galapagos islands not only control the coupled climate variability via their ability to terminate the equatorial undercurrent but also offer a clear example of a biological loophole in terms of their impact on local upwelling and an expanding penguin habitat in the face of global warming. The complex bio-physical interactions in the cold-tongue and their influence on climate predictions and projections require a holisti thinking on future observing systems. Tropical Pacific offers a natural laboratory for designing a robust and sustained physical-biogeochemical observation system that can effectively bridge climate predictions and projections into a unified framework for subseasonal to multidecadal timescales. Such a system will be a foundation for establishing similar systems over the rest of the World ocean to seemlessly merge climate predictions and projections with the need to constantly monitor climate impacts on marine resources. This talk will focus on the zonal contrasts of the ocean dynamics and biogechemistry across the tropical Pacific to make a case for integrated physical-biogeochemical observations for climate predictions and projections.

Time series of Essential Climate Variables from Satellite Data

NASA Astrophysics Data System (ADS)

Werscheck, M.

2010-09-01

Climate change is a fact. We need to know how the climate system will develop in future and how this will affect workaday life. To do this we need climate models for prediction of the future on all time scales, and models to assess the impact of the prediction results to the various sectors of social and economic life. With this knowledge we can take measures to mitigate the causes and adapt to changes. Prerequisite for this is a careful and thorough monitoring of the climate systems. Satellite data are an increasing & valuable source of information to observe the climate system. For many decades now satellite data are available to derive information about our planet earth. EUMETSAT is the European Organisation in charge of the exploitation of satellite data for meteorology and (since the year 2000) climatology. Within the EUMETSAT Satellite Application Facility (SAF) Network, comprising 8 initiatives to derive geophysical parameters from satellite, the Satellite Application Facility on Climate Monitoring (CM SAF) is especially dedicated to provide climate relevant information from satellite data. Many products as e.g. water vapour, radiation at surface and top of atmosphere, cloud properties are available, some of these for more then 2 decades. Just recently the European Space Agency (ESA) launched the Climate Change Initiative (CCI) to derive Essential Climate Variables (ECVs) from satellite data, including e.g. cloud properties, aerosol, ozone, sea surface temperature etc.. The presentation will give an overview on some relevant European activities to derive Essential Climate Variables from satellite data and the links to Global Climate Observing System (GCOS), the Global Satellite Intercalibration System (GSICS) as well as the Sustained Co-ordinated Processing of Environmental Satellite Data for Climate Monitoring (SCOPE CM).

The GCOS Reference Upper-Air Network (GRUAN)

NASA Astrophysics Data System (ADS)

Vömel, H.; Berger, F. H.; Immler, F. J.; Seidel, D.; Thorne, P.

2009-04-01

While the global upper-air observing network has provided useful observations for operational weather forecasting for decades, its measurements lack the accuracy and long-term continuity needed for understanding climate change. Consequently, the scientific community faces uncertainty on such key issues as the trends of temperature in the upper troposphere and stratosphere or the variability and trends of stratospheric water vapour. To address these shortcomings, and to ensure that future climate records will be more useful than the records to date, the Global Climate Observing System (GCOS) program initiated the GCOS Reference Upper Air Network (GRUAN). GRUAN will be a network of about 30-40 observatories with a representative sampling of geographic regions and surface types. These stations will provide upper-air reference observations of the essential climate variables, i.e. temperature, geopotential, humidity, wind, radiation and cloud properties using specialized radiosondes and complementary remote sensing profiling instrumentation. Long-term stability, quality assurance / quality control, and a detailed assessment of measurement uncertainties will be the key aspects of GRUAN observations. The network will not be globally complete but will serve to constrain and adjust data from more spatially comprehensive global observing systems including satellites and the current radiosonde networks. This paper outlines the scientific rationale for GRUAN, its role in the Global Earth Observation System of Systems, network requirements and likely instrumentation, management structure, current status and future plans.

Data Integration Plans for the NOAA National Climate Model Portal (NCMP) (Invited)

NASA Astrophysics Data System (ADS)

Rutledge, G. K.; Williams, D. N.; Deluca, C.; Hankin, S. C.; Compo, G. P.

2010-12-01

NOAA’s National Climatic Data Center (NCDC) and its collaborators have initiated a five-year development and implementation of an operational access capability for the next generation weather and climate model datasets. The NOAA National Climate Model Portal (NCMP) is being designed using format neutral open web based standards and tools where users at all levels of expertise can gain access and understanding to many of NOAA’s climate and weather model products. NCMP will closely coordinate with and reside under the emerging NOAA Climate Services Portal (NCSP). To carry out its mission, NOAA must be able to successfully integrate model output and other data and information from all of its discipline specific areas to understand and address the complexity of many environmental problems. The NCMP will be an initial access point for the emerging NOAA Climate Services Portal (NCSP), which is the basis for unified access to NOAA climate products and services. NCMP is currently collaborating with the emerging Environmental Projection Center (EPC) expected to be developed at the Earth System Research Laboratory in Boulder CO. Specifically, NCMP is being designed to: - Enable policy makers and resource managers to make informed national and global policy decisions using integrated climate and weather model outputs, observations, information, products, and other services for the scientist and the non-scientist; - Identify model to observational interoperability requirements for climate and weather system analysis and diagnostics; - Promote the coordination of an international reanalysis observational clearinghouse (i.e.., Reanalysis.org) spanning the worlds numerical processing Center’s for an “Ongoing Analysis of the Climate System”. NCMP will initially provide access capabilities to 3 of NOAA’s high volume Reanalysis data sets of the weather and climate systems: 1) NCEP’s Climate Forecast System Reanalysis (CFS-R); 2) NOAA’s Climate Diagnostics Center/ Earth System Research Laboratory (ESRL) Twentieth Century Reanalysis Project data set (20CR, G. Compo, et al.), a historical reanalysis that will provide climate information dating back to 1850 to the present; and 3) the CPC’s Upper Air Reanlaysis. NCMP will advance the highly successful NOAA National Operational Model Archive and Distribution System (NOMADS, Rutledge, BAMS 2006), and standards already in use including Unidata’s THREDDS (TDS), PMEL’s Live Access Server (LAS) and the GrADS Data Server (GDS) from COLA; the Department of Energy (DOE) Earth System Grid (ESG) and the associated IPCC Climate model archive located at the Program for Climate Model Diagnostics and Inter-comparison (PCMDI) through the ESG; and NOAA’s Unified Access Framework (UAF) effort; and core standards developed by Open Geospatial Consortium (OGC). The format neutral OPeNDAP protocol as used in the NOMADS system will also be a key aspect of the design of NCMP.

Progress in Earth System Modeling since the ENIAC Calculation

NASA Astrophysics Data System (ADS)

Fung, I.

2009-05-01

The success of the first numerical weather prediction experiment on the ENIAC computer in 1950 was hinged on the expansion of the meteorological observing network, which led to theoretical advances in atmospheric dynamics and subsequently the implementation of the simplified equations on the computer. This paper briefly reviews the progress in Earth System Modeling and climate observations, and suggests a strategy to sustain and expand the observations needed to advance climate science and prediction.

Beyond equilibrium climate sensitivity

NASA Astrophysics Data System (ADS)

Knutti, Reto; Rugenstein, Maria A. A.; Hegerl, Gabriele C.

2017-10-01

Equilibrium climate sensitivity characterizes the Earth's long-term global temperature response to increased atmospheric CO2 concentration. It has reached almost iconic status as the single number that describes how severe climate change will be. The consensus on the 'likely' range for climate sensitivity of 1.5 °C to 4.5 °C today is the same as given by Jule Charney in 1979, but now it is based on quantitative evidence from across the climate system and throughout climate history. The quest to constrain climate sensitivity has revealed important insights into the timescales of the climate system response, natural variability and limitations in observations and climate models, but also concerns about the simple concepts underlying climate sensitivity and radiative forcing, which opens avenues to better understand and constrain the climate response to forcing. Estimates of the transient climate response are better constrained by observed warming and are more relevant for predicting warming over the next decades. Newer metrics relating global warming directly to the total emitted CO2 show that in order to keep warming to within 2 °C, future CO2 emissions have to remain strongly limited, irrespective of climate sensitivity being at the high or low end.

Keeping the lights on for global ocean salinity observation

DOE PAGES

Durack, Paul J.; Lee, Tong; Vinogradova, Nadya T.; ...

2016-02-24

Here, insights about climate are being uncovered thanks to improved capacities to observe ocean salinity, an essential climate variable. However, cracks are beginning to appear in the ocean observing system that require prompt attention if we are to maintain the existing, hard-won capacity into the near future.

Keeping the lights on for global ocean salinity observation

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

Durack, Paul J.; Lee, Tong; Vinogradova, Nadya T.

Here, insights about climate are being uncovered thanks to improved capacities to observe ocean salinity, an essential climate variable. However, cracks are beginning to appear in the ocean observing system that require prompt attention if we are to maintain the existing, hard-won capacity into the near future.

Climate Model Diagnostic Analyzer Web Service System

NASA Astrophysics Data System (ADS)

Lee, S.; Pan, L.; Zhai, C.; Tang, B.; Kubar, T. L.; Li, J.; Zhang, J.; Wang, W.

2015-12-01

Both the National Research Council Decadal Survey and the latest Intergovernmental Panel on Climate Change Assessment Report stressed the need for the comprehensive and innovative evaluation of climate models with the synergistic use of global satellite observations in order to improve our weather and climate simulation and prediction capabilities. The abundance of satellite observations for fundamental climate parameters and the availability of coordinated model outputs from CMIP5 for the same parameters offer a great opportunity to understand and diagnose model biases in climate models. In addition, the Obs4MIPs efforts have created several key global observational datasets that are readily usable for model evaluations. However, a model diagnostic evaluation process requires physics-based multi-variable comparisons that typically involve large-volume and heterogeneous datasets, making them both computationally- and data-intensive. In response, we have developed a novel methodology to diagnose model biases in contemporary climate models and implementing the methodology as a web-service based, cloud-enabled, provenance-supported climate-model evaluation system. The evaluation system is named Climate Model Diagnostic Analyzer (CMDA), which is the product of the research and technology development investments of several current and past NASA ROSES programs. The current technologies and infrastructure of CMDA are designed and selected to address several technical challenges that the Earth science modeling and model analysis community faces in evaluating and diagnosing climate models. In particular, we have three key technology components: (1) diagnostic analysis methodology; (2) web-service based, cloud-enabled technology; (3) provenance-supported technology. The diagnostic analysis methodology includes random forest feature importance ranking, conditional probability distribution function, conditional sampling, and time-lagged correlation map. We have implemented the new methodology as web services and incorporated the system into the Cloud. We have also developed a provenance management system for CMDA where CMDA service semantics modeling, service search and recommendation, and service execution history management are designed and implemented.

Orbital Noise in the Earth System and Climate Fluctuations

NASA Technical Reports Server (NTRS)

Liu, Han-Shou; Smith, David E. (Technical Monitor)

2001-01-01

Frequency noise in the variations of the Earth's obliquity (tilt) can modulate the insolation signal for climate change. Including this frequency noise effect on the incoming solar radiation, we have applied an energy balance climate model to calculate the climate fluctuations for the past one million years. Model simulation results are in good agreement with the geologically observed paleoclimate data. We conclude that orbital noise in the Earth system may be the major cause of the climate fluctuation cycles.

Climate Change Accuracy: Requirements and Economic Value

NASA Astrophysics Data System (ADS)

Wielicki, B. A.; Cooke, R.; Mlynczak, M. G.; Lukashin, C.; Thome, K. J.; Baize, R. R.

2014-12-01

Higher than normal accuracy is required to rigorously observe decadal climate change. But what level is needed? How can this be quantified? This presentation will summarize a new more rigorous and quantitative approach to determining the required accuracy for climate change observations (Wielicki et al., 2013, BAMS). Most current global satellite observations cannot meet this accuracy level. A proposed new satellite mission to resolve this challenge is CLARREO (Climate Absolute Radiance and Refractivity Observatory). CLARREO is designed to achieve advances of a factor of 10 for reflected solar spectra and a factor of 3 to 5 for thermal infrared spectra (Wielicki et al., Oct. 2013 BAMS). The CLARREO spectrometers are designed to serve as SI traceable benchmarks for the Global Satellite Intercalibration System (GSICS) and to greatly improve the utility of a wide range of LEO and GEO infrared and reflected solar passive satellite sensors for climate change observations (e.g. CERES, MODIS, VIIIRS, CrIS, IASI, Landsat, SPOT, etc). Providing more accurate decadal change trends can in turn lead to more rapid narrowing of key climate science uncertainties such as cloud feedback and climate sensitivity. A study has been carried out to quantify the economic benefits of such an advance as part of a rigorous and complete climate observing system. The study concludes that the economic value is $12 Trillion U.S. dollars in Net Present Value for a nominal discount rate of 3% (Cooke et al. 2013, J. Env. Sys. Dec.). A brief summary of these two studies and their implications for the future of climate science will be presented.

Canadian snow and sea ice: assessment of snow, sea ice, and related climate processes in Canada's Earth system model and climate-prediction system

NASA Astrophysics Data System (ADS)

Kushner, Paul J.; Mudryk, Lawrence R.; Merryfield, William; Ambadan, Jaison T.; Berg, Aaron; Bichet, Adéline; Brown, Ross; Derksen, Chris; Déry, Stephen J.; Dirkson, Arlan; Flato, Greg; Fletcher, Christopher G.; Fyfe, John C.; Gillett, Nathan; Haas, Christian; Howell, Stephen; Laliberté, Frédéric; McCusker, Kelly; Sigmond, Michael; Sospedra-Alfonso, Reinel; Tandon, Neil F.; Thackeray, Chad; Tremblay, Bruno; Zwiers, Francis W.

2018-04-01

The Canadian Sea Ice and Snow Evolution (CanSISE) Network is a climate research network focused on developing and applying state-of-the-art observational data to advance dynamical prediction, projections, and understanding of seasonal snow cover and sea ice in Canada and the circumpolar Arctic. This study presents an assessment from the CanSISE Network of the ability of the second-generation Canadian Earth System Model (CanESM2) and the Canadian Seasonal to Interannual Prediction System (CanSIPS) to simulate and predict snow and sea ice from seasonal to multi-decadal timescales, with a focus on the Canadian sector. To account for observational uncertainty, model structural uncertainty, and internal climate variability, the analysis uses multi-source observations, multiple Earth system models (ESMs) in Phase 5 of the Coupled Model Intercomparison Project (CMIP5), and large initial-condition ensembles of CanESM2 and other models. It is found that the ability of the CanESM2 simulation to capture snow-related climate parameters, such as cold-region surface temperature and precipitation, lies within the range of currently available international models. Accounting for the considerable disagreement among satellite-era observational datasets on the distribution of snow water equivalent, CanESM2 has too much springtime snow mass over Canada, reflecting a broader northern hemispheric positive bias. Biases in seasonal snow cover extent are generally less pronounced. CanESM2 also exhibits retreat of springtime snow generally greater than observational estimates, after accounting for observational uncertainty and internal variability. Sea ice is biased low in the Canadian Arctic, which makes it difficult to assess the realism of long-term sea ice trends there. The strengths and weaknesses of the modelling system need to be understood as a practical tradeoff: the Canadian models are relatively inexpensive computationally because of their moderate resolution, thus enabling their use in operational seasonal prediction and for generating large ensembles of multidecadal simulations. Improvements in climate-prediction systems like CanSIPS rely not just on simulation quality but also on using novel observational constraints and the ready transfer of research to an operational setting. Improvements in seasonal forecasting practice arising from recent research include accurate initialization of snow and frozen soil, accounting for observational uncertainty in forecast verification, and sea ice thickness initialization using statistical predictors available in real time.

Observing Human-induced Linkages between Urbanization and Earth's Climate System

NASA Technical Reports Server (NTRS)

Shepherd, J. Marshall; Jin, Menglin

2004-01-01

Urbanization is one of the extreme cases of land use change. Most of world s population has moved to urban areas. Although currently only 1.2% of the land is considered urban, the spatial coverage and density of cities are expected to rapidly increase in the near future. It is estimated that by the year 2025, 60% of the world s population will live in cities. Human activity in urban environments also alters atmospheric composition; impacts components of the water cycle; and modifies the carbon cycle and ecosystems. However, our understanding of urbanization on the total Earth-climate system is incomplete. Better understanding of how the Earth s atmosphere-ocean-land-biosphere components interact as a coupled system and the influence of the urban environment on this climate system is critical. The goal of the 2003 AGU Union session Human-induced climate variations on urban areas: From observations to modeling was to bring together scientists from interdisciplinary backgrounds to discuss the data, scientific approaches and recent results on observing and modeling components of the urban environment with the intent of sampling our current stand and discussing future direction on this topic. Herein, a summary and discussion of the observations component of the session are presented.

Clouds and the Earth's Radiant Energy System (CERES) Data Products for Climate Research

NASA Technical Reports Server (NTRS)

Kato, Seiji; Loeb, Norman G.; Rutan, David A.; Rose, Fred G.

2015-01-01

NASA's Clouds and the Earth's Radiant Energy System (CERES) project integrates CERES, Moderate Resolution Imaging Spectroradiometer (MODIS), and geostationary satellite observations to provide top-of-atmosphere (TOA) irradiances derived from broadband radiance observations by CERES instruments. It also uses snow cover and sea ice extent retrieved from microwave instruments as well as thermodynamic variables from reanalysis. In addition, these variables are used for surface and atmospheric irradiance computations. The CERES project provides TOA, surface, and atmospheric irradiances in various spatial and temporal resolutions. These data sets are for climate research and evaluation of climate models. Long-term observations are required to understand how the Earth system responds to radiative forcing. A simple model is used to estimate the time to detect trends in TOA reflected shortwave and emitted longwave irradiances.

Climate Informatics: Accelerating Discovering in Climate Science with Machine Learning

NASA Technical Reports Server (NTRS)

Monteleoni, Claire; Schmidt, Gavin A.; McQuade, Scott

2014-01-01

The goal of climate informatics, an emerging discipline, is to inspire collaboration between climate scientists and data scientists, in order to develop tools to analyze complex and ever-growing amounts of observed and simulated climate data, and thereby bridge the gap between data and understanding. Here, recent climate informatics work is presented, along with details of some of the field's remaining challenges. Given the impact of climate change, understanding the climate system is an international priority. The goal of climate informatics is to inspire collaboration between climate scientists and data scientists, in order to develop tools to analyze complex and ever-growing amounts of observed and simulated climate data, and thereby bridge the gap between data and understanding. Here, recent climate informatics work is presented, along with details of some of the remaining challenges.

A perspective on sustained marine observations for climate modelling and prediction.

PubMed

Dunstone, Nick J

2014-09-28

Here, I examine some of the many varied ways in which sustained global ocean observations are used in numerical modelling activities. In particular, I focus on the use of ocean observations to initialize predictions in ocean and climate models. Examples are also shown of how models can be used to assess the impact of both current ocean observations and to simulate that of potential new ocean observing platforms. The ocean has never been better observed than it is today and similarly ocean models have never been as capable at representing the real ocean as they are now. However, there remain important unanswered questions that can likely only be addressed via future improvements in ocean observations. In particular, ocean observing systems need to respond to the needs of the burgeoning field of near-term climate predictions. Although new ocean observing platforms promise exciting new discoveries, there is a delicate balance to be made between their funding and that of the current ocean observing system. Here, I identify the need to secure long-term funding for ocean observing platforms as they mature, from a mainly research exercise to an operational system for sustained observation over climate change time scales. At the same time, considerable progress continues to be made via ship-based observing campaigns and I highlight some that are dedicated to addressing uncertainties in key ocean model parametrizations. The use of ocean observations to understand the prominent long time scale changes observed in the North Atlantic is another focus of this paper. The exciting first decade of monitoring of the Atlantic meridional overturning circulation by the RAPID-MOCHA array is highlighted. The use of ocean and climate models as tools to further probe the drivers of variability seen in such time series is another exciting development. I also discuss the need for a concerted combined effort from climate models and ocean observations in order to understand the current slow-down in surface global warming. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

MOSAiC - Multidisciplinary drifting Observatory for the Study of Arctic Climate

NASA Astrophysics Data System (ADS)

Shupe, M.; Persson, O. P.; Tjernstrom, M. K.; Dethloff, K.

2012-12-01

The climate in the Arctic is changing faster than in other regions of the Earth, with near surface temperatures rising more than twice as fast as the global average and the perennial sea-ice cover shrinking fast, especially in summer. The Arctic is transitioning towards a new climate regime dominated by first year sea-ice. At the same time, the scientific understanding of processes and feedbacks causing this rapid change is poor and climate modeling in the Arctic remains problematic. Furthermore, the key physical processes and process-interactions in this new emerging Arctic system are likely different from those in the old system that was dominated by multi-year ice. Our understanding of this complex climate system, and ability to improve climate and weather models, is limited by the lack of observations in the extreme and remote central Arctic. Multi-year, detailed and comprehensive measurements, extending from the atmosphere through the sea-ice and into the ocean in the central Arctic Basin are needed to provide process-level understanding of the central Arctic climate system. To address this need, a manned, international drifting station will be installed in the young sea-ice of the western Arctic and follow the evolution of the ice pack as it proceeds through the transpolar drift towards the Fram Strait over the course of 1-2 years. The Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC), proposed to start in autumn 2017, will be guided by the broad theme: What are the causes and consequences of diminished Arctic sea-ice coverage? To address this theme requires a number of interdisciplinary investigations that target more specific science questions. *How do ongoing changes in the Arctic ice-ocean-atmosphere system drive heat and mass transfers of importance to climate and ecosystems? *What are the processes and feedbacks affecting sea ice cover, atmosphere-ocean stratification and energy budget in the Arctic? *Will an ice reduced Arctic become more biologically productive and what are the consequences of this to other components of the system? *How do the different scales of heterogeneity within the atmosphere ice and ocean interact to impact the linkages or feedbacks within the system? *How do interfacial exchange rates, biology and chemistry couple to regulate the major elemental cycles? MOSAiC will address these multi-disciplinary questions using intensive observations and modeling of processes that transfer energy, mass, and momentum through the atmosphere-ice-ocean system. The centerpiece of the observatory will be an icebreaker-based station to serve as a hub for intensive and comprehensive observations of climatically-significant physical, chemical, and biological processes through the vertical column. To provide important spatial context and horizontal variability, this facility will be the focal point for a constellation of coordinated observations made by drifting buoys, unmanned aerial and underwater vehicles, aircraft, ships, and satellites. These MOSAiC observational activities will serve as a testbed for evaluation and development of models at scales ranging from high-resolution, process models to regional and global climate models. MOSAiC observational and modeling activities will be linked at the outset, such that model needs will be integral in observational design, implementation, and analysis.

Climate Prediction Center - NCEP Global Ocean Data Assimilation System:

Science.gov Websites

home page National Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Monthly in NetCDF Other formats Links NOAA Ocean Climate Observation Program (OCO) Climate Test Bed About Prediction (NCEP) are a valuable community asset for monitoring different aspects of ocean climate

Demonstration of successful malaria forecasts for Botswana using an operational seasonal climate model

NASA Astrophysics Data System (ADS)

MacLeod, Dave A.; Jones, Anne; Di Giuseppe, Francesca; Caminade, Cyril; Morse, Andrew P.

2015-04-01

The severity and timing of seasonal malaria epidemics is strongly linked with temperature and rainfall. Advance warning of meteorological conditions from seasonal climate models can therefore potentially anticipate unusually strong epidemic events, building resilience and adapting to possible changes in the frequency of such events. Here we present validation of a process-based, dynamic malaria model driven by hindcasts from a state-of-the-art seasonal climate model from the European Centre for Medium-Range Weather Forecasts. We validate the climate and malaria models against observed meteorological and incidence data for Botswana over the period 1982-2006 the longest record of observed incidence data which has been used to validate a modeling system of this kind. We consider the impact of climate model biases, the relationship between climate and epidemiological predictability and the potential for skillful malaria forecasts. Forecast skill is demonstrated for upper tercile malaria incidence for the Botswana malaria season (January-May), using forecasts issued at the start of November; the forecast system anticipates six out of the seven upper tercile malaria seasons in the observational period. The length of the validation time series gives confidence in the conclusion that it is possible to make reliable forecasts of seasonal malaria risk, forming a key part of a health early warning system for Botswana and contributing to efforts to adapt to climate change.

Aerial Observation Needs Workshop, May 13-14, 2015

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

Nasiri, Shaima; Serbin, Shawn; Lesmes, David

2015-10-01

The mission of the Climate and Environmental Sciences Division (CESD) of the Office of Biological and Environmental Research (BER) within the U.S. Department of Energy's (DOE) Office of Science is "to advance a robust, predictive understanding of Earth's climate and environmental systems and to inform the development of sustainable solutions to the nation's energy and environmental challenges." Accomplishing this mission requires aerial observations of the atmospheric and terrestrial components of the climate system. CESD is assessing its current and future aerial observation needs to develop a strategy and roadmap of capability requirements for the next decade. To facilitate this process,more » a workshop was convened that consisted of invited experts in the atmospheric and terrestrial sciences, airborne observations, and modeling. This workshop report summarizes the community input prior to and during the workshop on research challenges and opportunities, as well as specific science questions and observational needs that require aerial observations to address.« less

Space observations for global and regional studies of the biosphere

NASA Technical Reports Server (NTRS)

Cihlar, J.; Li, Z.; Chen, J.; Sellers, P.; Hall, F.

1994-01-01

The capability to make space-based measurements of Earth at high spatial and temporal resolutions, which would not otherwise be economically or practically feasible, became available just in time to contribute to scientific understanding of the interactive processes governing the total Earth system. Such understanding has now become essential in order to take practical steps which would counteract or mitigate the pervasive impact of the growing human population on the future habitability of the Earth. The paper reviews the rationale for using space observations for studies of climate and terrestrial ecosystems at global and regional scales, as well as the requirements for such observations for studies of climate and ecosystem dynamics. The present status of these developments is reported along with initiatives under way to advance the use of satellite observations for Earth system studies. The most important contribution of space observations is the provision of physical or biophysical parameters for models representing various components of the Earth system. Examples of such parameters are given for climatic and ecosystem studies.

Dissemination of Climate Model Output to the Public and Commercial Sector

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

Robert Stockwell, PhD

2010-09-23

Climate is defined by the Glossary of Meteorology as the mean of atmospheric variables over a period of time ranging from as short as a few months to multiple years and longer. Although the term climate is often used to refer to long-term weather statistics, the broader definition of climate is the time evolution of a system consisting of the atmosphere, hydrosphere, lithosphere, and biosphere. Physical, chemical, and biological processes are involved in interactions among the components of the climate system. Vegetation, soil moisture, and glaciers are part of the climate system in addition to the usually considered temperature andmore » precipitation (Pielke, 2008). Climate change refers to any systematic change in the long-term statistics of climate elements (such as temperature, pressure, or winds) sustained over several decades or longer. Climate change can be initiated by external forces, such as cyclical variations in the Earth's solar orbit that are thought to have caused glacial and interglacial periods within the last 2 million years (Milankovitch, 1941). However, a linear response to astronomical forcing does not explain many other observed glacial and interglacial cycles (Petit et al., 1999). It is now understood that climate is influenced by the interaction of solar radiation with atmospheric greenhouse gasses (e.g., carbon dioxide, chlorofluorocarbons, methane, nitrous oxide, etc.), aerosols (airborne particles), and Earth's surface. A significant aspect of climate are the interannual cycles, such as the El Nino La Nina cycle which profoundly affects the weather in North America but is outside the scope of weather forecasts. Some of the most significant advances in understanding climate change have evolved from the recognition of the influence of ocean circulations upon the atmosphere (IPCC, 2007). Human activity can affect the climate system through increasing concentrations of atmospheric greenhouse gases, air pollution, increasing concentrations of aerosol, and land alteration. A particular concern is that atmospheric levels of CO{sub 2} may be rising faster than at any time in Earth's history, except possibly following rare events like impacts from large extraterrestrial objects (AMS, 2007). Atmospheric CO{sub 2} concentrations have increased since the mid-1700s through fossil fuel burning and changes in land use, with more than 80% of this increase occurring since 1900. The increased levels of CO{sub 2} will remain in the atmosphere for hundreds to thousands of years. The complexity of the climate system makes it difficult to predict specific aspects of human-induced climate change, such as exactly how and where changes will occur, and their magnitude. The Intergovernmental Panel for Climate Change (IPCC) was established by World Meteorological Organization (WMO) and the United Nations in 1988. The IPCC was tasked with assessing the scientific, technical and socioeconomic information needed to understand the risk of human-induced climate change, its observed and projected impacts, and options for adaptation and mitigation. The IPCC concluded in its Fourth Assessment Report (AR4) that warming of the climate system is unequivocal, and that most of the observed increase in globally averaged temperatures since the mid-20th century is very likely due to the observed increased in anthropogenic greenhouse gas concentrations (IPCC, 2007).« less

An assessment of global climate model-simulated climate for the western cordillera of Canada (1961-90)

NASA Astrophysics Data System (ADS)

Bonsal, Barrie R.; Prowse, Terry D.; Pietroniro, Alain

2003-12-01

Climate change is projected to significantly affect future hydrologic processes over many regions of the world. This is of particular importance for alpine systems that provide critical water supplies to lower-elevation regions. The western cordillera of Canada is a prime example where changes to temperature and precipitation could have profound hydro-climatic impacts not only for the cordillera itself, but also for downstream river systems and the drought-prone Canadian Prairies. At present, impact researchers primarily rely on global climate models (GCMs) for future climate projections. The main objective of this study is to assess several GCMs in their ability to simulate the magnitude and spatial variability of current (1961-90) temperature and precipitation over the western cordillera of Canada. In addition, several gridded data sets of observed climate for the study region are evaluated.Results reveal a close correspondence among the four gridded data sets of observed climate, particularly for temperature. There is, however, considerable variability regarding the various GCM simulations of this observed climate. The British, Canadian, German, Australian, and US GFDL models are superior at simulating the magnitude and spatial variability of mean temperature. The Japanese GCM is of intermediate ability, and the US NCAR model is least representative of temperature in this region. Nearly all the models substantially overestimate the magnitude of total precipitation, both annually and on a seasonal basis. An exception involves the British (Hadley) model, which best represents the observed magnitude and spatial variability of precipitation. This study improves our understanding regarding the accuracy of GCM climate simulations over the western cordillera of Canada. The findings may assist in producing more reliable future scenarios of hydro-climatic conditions over various regions of the country. Copyright

Detection of Historical and Future Precipitation Variations and Extremes Over the Continental United States

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

Anderson, Bruce T.

2015-12-11

Problem: The overall goal of this proposal is to detect observed seasonal-mean precipitation variations and extreme event occurrences over the United States. Detection, e.g. the process of demonstrating that an observed change in climate is unusual, first requires some means of estimating the range of internal variability absent any external drivers. Ideally, the internal variability would be derived from the observations themselves, however generally the observed variability is a confluence of both internal variability and variability in response to external drivers. Further, numerical climate models—the standard tool for detection studies—have their own estimates of intrinsic variability, which may differ substantiallymore » from that found in the observed system as well as other model systems. These problems are further compounded for weather and climate extremes, which as singular events are particularly ill-suited for detection studies because of their infrequent occurrence, limited spatial range, and underestimation within global and even regional numerical models. Rationale: As a basis for this research we will show how stochastic daily-precipitation models—models in which the simulated interannual-to-multidecadal precipitation variance is purely the result of the random evolution of daily precipitation events within a given time period—can be used to address many of these issues simultaneously. Through the novel application of these well-established models, we can first estimate the changes/trends in various means and extremes that can occur even with fixed daily-precipitation characteristics, e.g. that can occur simply as a result of the stochastic evolution of daily weather events within a given climate. Detection of a change in the observed climate—either naturally or anthropogenically forced—can then be defined as any change relative to this stochastic variability, e.g. as changes/trends in the means and extremes that could only have occurred through a change in the underlying climate. As such, this method is capable of detecting “hot spot” regions—as well as “flare ups” within the hot spot regions—that have experienced interannual to multi-decadal scale variations and trends in seasonal-mean precipitation and extreme events. Further by applying the same methods to numerical climate models we can discern the fidelity of the current-generation climate models in representing detectability within the observed climate system. In this way, we can objectively determine the utility of these model systems for performing detection studies of historical and future climate change.« less

NASA Tools for Climate Impacts on Water Resources

NASA Technical Reports Server (NTRS)

Toll, David; Doorn, Brad

2010-01-01

Climate and environmental change are expected to fundamentally alter the nation's hydrological cycle and water availability. Satellites provide global or near-global coverage using instruments, allowing for consistent, well-calibrated, and equivalent-quality data of the Earth system. A major goal for NASA climate and environmental change research is to create multi-instrument data sets to span the multi-decadal time scales of climate change and to combine these data with those from modeling and surface-based observing systems to improve process understanding and predictions. NASA and Earth science data and analyses will ultimately enable more accurate climate prediction, and characterization of uncertainties. NASA's Applied Sciences Program works with other groups, including other federal agencies, to transition demonstrated observational capabilities to operational capabilities. A summary of some of NASA tools for improved water resources management will be presented.

Fifth IPCC Assessment Report Now Out

NASA Astrophysics Data System (ADS)

Kundzewicz, Zbigniew W.

2014-01-01

The Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC) is now available. It provides policymakers with an assessment of information on climate change, its impacts and possible response options (adaptation and mitigation). Summaries for policymakers of three reports of IPCC working groups and of the Synthesis Report have now been approved by IPCC plenaries. This present paper reports on the most essential findings in AR5. It briefly informs on the contents of reports of all IPCC working groups. It discusses the physical science findings, therein observed changes (ubiquitous warming, shrinking cryosphere, sea level rise, changes in precipitation and extremes, and biogeochemical cycles). It deals with the drivers of climate change, progress in climate system understanding (evaluation of climate models, quantification of climate system responses), and projections for the future. It reviews impacts, adaptation and vulnerability, including observed changes, key risks, key reasons for concern, sectors and systems, and managing risks and building resilience. Finally, mitigation of climate change is discussed, including greenhouse gas emissions in the past, present and future, and mitigation in sectors. It is hoped that the present article will encourage the readership of this journal to dive into the AR5 report that provides a wealth of useful information.

Climate-driven polar motion

NASA Astrophysics Data System (ADS)

Celaya, Michael A.; Wahr, John M.; Bryan, Frank O.

1999-06-01

The output of a coupled climate system model provides a synthetic climate record with temporal and spatial coverage not attainable with observational data, allowing evaluation of climatic excitation of polar motion on timescales of months to decades. Analysis of the geodetically inferred Chandler excitation power shows that it has fluctuated by up to 90% since 1900 and that it has characteristics representative of a stationary Gaussian process. Our model-predicted climate excitation of the Chandler wobble also exhibits variable power comparable to the observed. Ocean currents and bottom pressure shifts acting together can alone drive the 14-month wobble. The same is true of the excitation generated by the combined effects of barometric pressure and winds. The oceanic and atmospheric contributions are this large because of a relatively high degree of constructive interference between seafloor pressure and currents and between atmospheric pressure and winds. In contrast, excitation by the redistribution of water on land appears largely insignificant. Not surprisingly, the full climate effect is even more capable of driving the wobble than the effects of the oceans or atmosphere alone are. Our match to the observed annual excitation is also improved, by about 17%, over previous estimates made with historical climate data. Efforts to explain the 30-year Markowitz wobble meet with less success. Even so, at periods ranging from months to decades, excitation generated by a model of a coupled climate system makes a close approximation to the amplitude of what is geodetically observed.

Chapter 3: Climate change and the relevance of historical forest conditions

Treesearch

H.D. Safford; M. North; M.D. Meyer

2012-01-01

Increasing human emissions of greenhouse gases are modifying the Earth's climate. According to the Intergovernmental Panel on Climate Change (IPCC), "Warming of the climate system is unequivocal, as is now evident from observation of increases in average air and ocean temperatures, widespread melting of snow and ice, and rising global average sea...

Analysis of biases from parallel observations of co-located manual and automatic weather stations in Indonesia

NASA Astrophysics Data System (ADS)

Sopaheluwakan, Ardhasena; Fajariana, Yuaning; Satyaningsih, Ratna; Aprilina, Kharisma; Astuti Nuraini, Tri; Ummiyatul Badriyah, Imelda; Lukita Sari, Dyah; Haryoko, Urip

2017-04-01

Inhomogeneities are often found in long records of climate data. These can occur because of various reasons, among others such as relocation of observation site, changes in observation method, and the transition to automated instruments. Changes to these automated systems are inevitable, and it is taking place worldwide in many of the National Meteorological Services. However this shift of observational practice must be done cautiously and a sufficient period of parallel observation of co-located manual and automated systems should take place as suggested by the World Meteorological Organization. With a sufficient parallel observation period, biases between the two systems can be analyzed. In this study we analyze the biases of a yearlong parallel observation of manual and automatic weather stations in 30 locations in Indonesia. The location of the sites spans from east to west of approximately 45 longitudinal degrees covering different climate characteristics and geographical settings. We study measurements taken by both sensors for temperature and rainfall parameters. We found that the biases from both systems vary from place to place and are more dependent to the setting of the instrument rather than to the climatic and geographical factors. For instance, daytime observations of the automatic weather stations are found to be consistently higher than the manual observation, and vice versa night time observations of the automatic weather stations are lower than the manual observation.

Cloud Feedbacks in the Climate System: A Critical Review.

NASA Astrophysics Data System (ADS)

Stephens, Graeme L.

2005-01-01

This paper offers a critical review of the topic of cloud-climate feedbacks and exposes some of the underlying reasons for the inherent lack of understanding of these feedbacks and why progress might be expected on this important climate problem in the coming decade. Although many processes and related parameters come under the influence of clouds, it is argued that atmospheric processes fundamentally govern the cloud feedbacks via the relationship between the atmospheric circulations, cloudiness, and the radiative and latent heating of the atmosphere. It is also shown how perturbations to the atmospheric radiation budget that are induced by cloud changes in response to climate forcing dictate the eventual response of the global-mean hydrological cycle of the climate model to climate forcing. This suggests that cloud feedbacks are likely to control the bulk precipitation efficiency and associated responses of the planet's hydrological cycle to climate radiative forcings.The paper provides a brief overview of the effects of clouds on the radiation budget of the earth-atmosphere system and a review of cloud feedbacks as they have been defined in simple systems, one being a system in radiative-convective equilibrium (RCE) and others relating to simple feedback ideas that regulate tropical SSTs. The systems perspective is reviewed as it has served as the basis for most feedback analyses. What emerges is the importance of being clear about the definition of the system. It is shown how different assumptions about the system produce very different conclusions about the magnitude and sign of feedbacks. Much more diligence is called for in terms of defining the system and justifying assumptions. In principle, there is also neither any theoretical basis to justify the system that defines feedbacks in terms of global-time-mean changes in surface temperature nor is there any compelling empirical evidence to do so. The lack of maturity of feedback analysis methods also suggests that progress in understanding climate feedback will require development of alternative methods of analysis.It has been argued that, in view of the complex nature of the climate system, and the cumbersome problems encountered in diagnosing feedbacks, understanding cloud feedback will be gleaned neither from observations nor proved from simple theoretical argument alone. The blueprint for progress must follow a more arduous path that requires a carefully orchestrated and systematic combination of model and observations. Models provide the tool for diagnosing processes and quantifying feedbacks while observations provide the essential test of the model's credibility in representing these processes. While GCM climate and NWP models represent the most complete description of all the interactions between the processes that presumably establish the main cloud feedbacks, the weak link in the use of these models lies in the cloud parameterization imbedded in them. Aspects of these parameterizations remain worrisome, containing levels of empiricism and assumptions that are hard to evaluate with current global observations. Clearly observationally based methods for evaluating cloud parameterizations are an important element in the road map to progress.Although progress in understanding the cloud feedback problem has been slow and confused by past analysis, there are legitimate reasons outlined in the paper that give hope for real progress in the future.

Are Global In-Situ Ocean Observations Fit-for-purpose? Applying the Framework for Ocean Observing in the Atlantic.

NASA Astrophysics Data System (ADS)

Visbeck, M.; Fischer, A. S.; Le Traon, P. Y.; Mowlem, M. C.; Speich, S.; Larkin, K.

2015-12-01

There are an increasing number of global, regional and local processes that are in need of integrated ocean information. In the sciences ocean information is needed to support physical ocean and climate studies for example within the World Climate Research Programme and its CLIVAR project, biogeochemical issues as articulated by the GCP, IMBER and SOLAS projects of ICSU-SCOR and Future Earth. This knowledge gets assessed in the area of climate by the IPCC and biodiversity by the IPBES processes. The recently released first World Ocean Assessment focuses more on ecosystem services and there is an expectation that the Sustainable Development Goals and in particular Goal 14 on the Ocean and Seas will generate new demands for integrated ocean observing from Climate to Fish and from Ocean Resources to Safe Navigation and on a healthy, productive and enjoyable ocean in more general terms. In recognition of those increasing needs for integrated ocean information we have recently launched the Horizon 2020 AtlantOS project to promote the transition from a loosely-coordinated set of existing ocean observing activities to a more integrated, more efficient, more sustainable and fit-for-purpose Atlantic Ocean Observing System. AtlantOS takes advantage of the Framework for Ocean observing that provided strategic guidance for the design of the project and its outcome. AtlantOS will advance the requirements and systems design, improving the readiness of observing networks and data systems, and engaging stakeholders around the Atlantic. AtlantOS will bring Atlantic nations together to strengthen their complementary contributions to and benefits from the internationally coordinated Global Ocean Observing System (GOOS) and the Blue Planet Initiative of the Global Earth Observation System of Systems (GEOSS). AtlantOS will fill gaps of the in-situ observing system networks and will ensure that their data are readily accessible and useable. AtlantOS will demonstrate the utility of integrating in-situ and remotely sensed Earth observations to produce information products supporting a wide range of sectors. AtlantOS will support activities to share best practice, integrate data streams and promote the standardization of in-situ observations. AtlantOS will promote network integration, optimization and new technologies.

Weather and climate

NASA Technical Reports Server (NTRS)

1975-01-01

Recommendations for using space observations of weather and climate to aid in solving earth based problems are given. Special attention was given to: (1) extending useful forecasting capability of space systems, (2) reducing social, economic, and human losses caused by weather, (3) development of space system capability to manage and control air pollutant concentrations, and (4) establish mechanisms for the national examination of deliberate and inadvertent means for modifying weather and climate.

Putting the Weather Back Into Climate

NASA Astrophysics Data System (ADS)

Smith, Leonard A.; Stainforth, David A.

2014-05-01

The literature contains a variety of definitions of climate, and the emphasis in these definitions has changed over time. Defining climate as a mean value is, of course, both limiting and misleading; definitions of climate based on averages have been deprecated as far back as 1931 [1]. In the context of current efforts to produce climate predictions for use in climate adaptation, it is timely to consider how well various definitions of climate serve the research for applications community. From a nonlinear dynamical systems perspective it is common to associate climate with a system's natural measure (or "attractor" if such an object exists). Such a definition is not easily applied to physical systems where we have limited observations over a restricted period of time; the duration of 30 years is often mentioned today and the origin of this period is discussed. Given a dynamic system in which parameters are evolving in time, the view of climate as a natural measure becomes problematic as, by definition, there may be no attractor per se. Attractors defined for particular parameter values cannot be expected to have any association with the probability of states under transient changes in the values of that parameter. Alternatively, distributions may be determined which reflect the transient situation, based on (rather broad) additional assumptions regarding the state of the system at some point in the past (say, an ice age planet vs an interglacial planet). Such distributions reflect many of the properties one would hope to be represented in a generalised definition of the system's climate. Here we trace how definitions of climate have changed over time and highlight a number of properties of definitions of climate which would facilitate common use across researchers, from observers to theoreticians, from climate modellers to mathematicians. We show while periodic changes in parameter values (such as those found in an annual cycle or a diurnal cycle) are easily incorporated within the traditional nonlinear dynamical systems view, non-periodic or secular changes (such as those due to increasing atmospheric greenhouse gas concentrations) yield an open challenge. We argue the need both for clarifying and for clearly meeting the open challenges of defining climate in relation to the state of an evolving system, and suggest a path forward. [1] Miller, A.A., 1931: Climatology. First Ed. Methuen.

Interaction of the Climate System and the Solid Earth: Analysis of Observations and Models

NASA Technical Reports Server (NTRS)

Bryan, Frank

2001-01-01

Under SENH funding we have carried out a number of diverse analyses of interactions of the climate system (atmosphere, ocean, land surface hydrology) with the solid Earth. While the original work plan emphasized analysis of excitation of variations in Earth rotation, with a lesser emphasis on time variable gravity, opportunities that developed during the proposal period in connection with preparations for the GRACE mission led us to a more balanced effort between these two topics. The results of our research are outlined in several topical sections: (1) oceanic excitation of variations in Earth rotation; (2) short period atmosphere-ocean excitation of variations in Earth rotation; (3) analysis of coupled climate system simulation; (4) observing system simulation studies for GRACE mission design; and (5) oceanic response to atmospheric pressure loading.

Climate Outreach Using Regional Coastal Ocean Observing System Portals

NASA Astrophysics Data System (ADS)

Anderson, D. M.; Hernandez, D. L.; Wakely, A.; Bochenek, R. J.; Bickel, A.

2015-12-01

Coastal oceans are dynamic, changing environments affected by processes ranging from seconds to millennia. On the east and west coast of the U.S., regional observing systems have deployed and sustained a remarkable diverse array of observing tools and sensors. Data portals visualize and provide access to real-time sensor networks. Portals have emerged as an interactive tool for educators to help students explore and understand climate. Bringing data portals to outreach events, into classrooms, and onto tablets and smartphones enables educators to address topics and phenomena happening right now. For example at the 2015 Charleston Science Technology Engineering and Math (STEM) Festival, visitors navigated the SECOORA (Southeast Coastal Ocean Observing regional Association) data portal to view the real-time marine meteorological conditions off South Carolina. Map-based entry points provide an intuitive interface for most students, an array of time series and other visualizations depict many of the essential principles of climate science manifest in the coastal zone, and data down-load/ extract options provide access to the data and documentation for further inquiry by advanced users. Beyond the exposition of climate principles, the portal experience reveals remarkable technologies in action and shows how the observing system is enabled by the activity of many different partners.

Towards the Prediction of Decadal to Centennial Climate Processes in the Coupled Earth System Model

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

Liu, Zhengyu; Kutzbach, J.; Jacob, R.

2011-12-05

In this proposal, we have made major advances in the understanding of decadal and long term climate variability. (a) We performed a systematic study of multidecadal climate variability in FOAM-LPJ and CCSM-T31, and are starting exploring decadal variability in the IPCC AR4 models. (b) We develop several novel methods for the assessment of climate feedbacks in the observation. (c) We also developed a new initialization scheme DAI (Dynamical Analogue Initialization) for ensemble decadal prediction. (d) We also studied climate-vegetation feedback in the observation and models. (e) Finally, we started a pilot program using Ensemble Kalman Filter in CGCM for decadalmore » climate prediction.« less

Developing a Carbon Observing System

NASA Astrophysics Data System (ADS)

Moore, B., III

2015-12-01

There is a clear need to better understand and predict future climate change, so that science can more confidently inform climate policy, including adaptation planning and future mitigation strategies. Understanding carbon cycle feedbacks, and the relationship between emissions (fossil and land use) and the resulting atmospheric carbon dioxide (CO2) and methane (CH4) concentrations in a changing climate has been recognized as an important goal by the IPCC. The existing surface greenhouse gas observing networks provide accurate and precise measurements of background values, but they are not configured to target the extended, complex and dynamic regions of the carbon budget. Space Agencies around the globe are committed to CO2 and CH4 observations: GOSAT-1/2, OCO-2/3, MERLin, TanSat, and CarbonSat. In addition to these Low Earth Orbit (LEO) missions, a new mission in Geostationary Orbit (GEO), geoCARB, which would provide mapping-like measurements of carbon dioxide, methane, and carbon monoxide concentrations over major land areas, has been recently proposed to the NASA Venture Program. These pioneering missions do not provide the spatial/temporal coverage to answer the key carbon-climate questions at process relevant scales nor do they address the distribution and quantification of anthropogenic sources at urban scales. They do demonstrate, however, that a well-planned future system of system integrating space-based LEO and GEO missions with extensive in situ observations could provide the accuracy, spatial resolution, and coverage needed to address critical open issues in the carbon-climate system. Dr. Diana Wickland devoted enormous energy in developing a comprehensive apprioach to understand the global carbon cycle; she understood well that an integrated, coordinated, international approach is needed. This shines through in her recent contribution in co-chairing the team that produced the "CEOS Strategy for Carbon Observations from Space." A NASA-funded community workshop in March 2015 addressed issues and prioritzed a set of research and observational needs in the study of the Carbon-Climate System. This paper will refect upon the past 30 plus years of carbon research supported by NASA and Dr. Wickland's role, and it will conclude with the findings of the March 2015 Workshop.

Impact of four-dimensional data assimilation (FDDA) on urban climate analysis

NASA Astrophysics Data System (ADS)

Pan, Linlin; Liu, Yubao; Liu, Yuewei; Li, Lei; Jiang, Yin; Cheng, Will; Roux, Gregory

2015-12-01

This study investigates the impact of four-dimensional data assimilation (FDDA) on urban climate analysis, which employs the NCAR (National Center for Atmospheric Research) WRF (the weather research and forecasting model) based on climate FDDA (CFDDA) technology to develop an urban-scale microclimatology database for the Shenzhen area, a rapidly developing metropolitan located along the southern coast of China, where uniquely high-density observations, including ultrahigh-resolution surface AWS (automatic weather station) network, radio sounding, wind profilers, radiometers, and other weather observation platforms, have been installed. CFDDA is an innovative dynamical downscaling regional climate analysis system that assimilates diverse regional observations; and has been employed to produce a 5 year multiscale high-resolution microclimate analysis by assimilating high-density observations at Shenzhen area. The CFDDA system was configured with four nested-grid domains at grid sizes of 27, 9, 3, and 1 km, respectively. This research evaluates the impact of assimilating high-resolution observation data on reproducing the refining features of urban-scale circulations. Two experiments were conducted with a 5 year run using CFSR (climate forecast system reanalysis) as boundary and initial conditions: one with CFDDA and the other without. The comparisons of these two experiments with observations indicate that CFDDA greatly reduces the model analysis error and is able to realistically analyze the microscale features such as urban-rural-coastal circulation, land/sea breezes, and local-hilly terrain thermal circulations. It is demonstrated that the urbanization can produce 2.5 k differences in 2 m temperatures, delays/speeds up the land/sea breeze development, and interacts with local mountain-valley circulations.

Impacts on Water Management and Crop Production of Regional Cropping System Adaptation to Climate Change

NASA Astrophysics Data System (ADS)

Zhong, H.; Sun, L.; Tian, Z.; Liang, Z.; Fischer, G.

2014-12-01

China is one of the most populous and fast developing countries, also faces a great pressure on grain production and food security. Multi-cropping system is widely applied in China to fully utilize agro-climatic resources and increase land productivity. As the heat resource keep improving under climate warming, multi-cropping system will also shifting northward, and benefit crop production. But water shortage in North China Plain will constrain the adoption of new multi-cropping system. Effectiveness of multi-cropping system adaptation to climate change will greatly depend on future hydrological change and agriculture water management. So it is necessary to quantitatively express the water demand of different multi-cropping systems under climate change. In this paper, we proposed an integrated climate-cropping system-crops adaptation framework, and specifically focused on: 1) precipitation and hydrological change under future climate change in China; 2) the best multi-cropping system and correspondent crop rotation sequence, and water demand under future agro-climatic resources; 3) attainable crop production with water constraint; and 4) future water management. In order to obtain climate projection and precipitation distribution, global climate change scenario from HADCAM3 is downscaled with regional climate model (PRECIS), historical climate data (1960-1990) was interpolated from more than 700 meteorological observation stations. The regional Agro-ecological Zone (AEZ) model is applied to simulate the best multi-cropping system and crop rotation sequence under projected climate change scenario. Finally, we use the site process-based DSSAT model to estimate attainable crop production and the water deficiency. Our findings indicate that annual land productivity may increase and China can gain benefit from climate change if multi-cropping system would be adopted. This study provides a macro-scale view of agriculture adaptation, and gives suggestions to national agriculture adaptation strategy decisions.

Globally Increased Crop Growth and Cropping Intensity from the Long-Term Satellite-Based Observations

NASA Astrophysics Data System (ADS)

Chen, Bin

2018-04-01

Understanding the spatiotemporal change trend of global crop growth and multiple cropping system under climate change scenarios is a critical requirement for supporting the food security issue that maintains the function of human society. Many studies have predicted the effects of climate changes on crop production using a combination of filed studies and models, but there has been limited evidence relating decadal-scale climate change to global crop growth and the spatiotemporal distribution of multiple cropping system. Using long-term satellite-derived Normalized Difference Vegetation Index (NDVI) and observed climate data from 1982 to 2012, we investigated the crop growth trend, spatiotemporal pattern trend of agricultural cropping intensity, and their potential correlations with respect to the climate change drivers at a global scale. Results show that 82.97 % of global cropland maximum NDVI witnesses an increased trend while 17.03 % of that shows a decreased trend over the past three decades. The spatial distribution of multiple cropping system is observed to expand from lower latitude to higher latitude, and the increased cropping intensity is also witnessed globally. In terms of regional major crop zones, results show that all nine selected zones have an obvious upward trend of crop maximum NDVI (p < 0.001), and as for climatic drivers, the gradual temperature and precipitation changes have had a measurable impact on the crop growth trend.

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

Hansen, Gerrit; Stone, Dáithí

Impacts of recent regional changes in climate on natural and human systems are documented across the globe, yet studies explicitly linking these observations to anthropogenic forcing of the climate are scarce. Here in this work, we provide a systematic assessment of the role of anthropogenic climate change for the range of impacts of regional climate trends reported in the IPCC’s Fifth Assessment Report. We find that almost two-thirds of the impacts related to atmospheric and ocean temperature can be confidently attributed to anthropogenic forcing. In contrast, evidence connecting changes in precipitation and their respective impacts to human influence is stillmore » weak. Moreover, anthropogenic climate change has been a major influence for approximately three-quarters of the impacts observed on continental scales. Finally, hence the effects of anthropogenic emissions can now be discerned not only globally, but also at more regional and local scales for a variety of natural and human systems.« less

Robust Engineering Designs for Infrastructure Adaptation to a Changing Climate

NASA Astrophysics Data System (ADS)

Samaras, C.; Cook, L.

2015-12-01

Infrastructure systems are expected to be functional, durable and safe over long service lives - 50 to over 100 years. Observations and models of climate science show that greenhouse gas emissions resulting from human activities have changed climate, weather and extreme events. Projections of future changes (albeit with uncertainties caused by inadequacies of current climate/weather models) can be made based on scenarios for future emissions, but actual future emissions are themselves uncertain. Most current engineering standards and practices for infrastructure assume that the probabilities of future extreme climate and weather events will match those of the past. Climate science shows that this assumption is invalid, but is unable, at present, to define these probabilities over the service lives of existing and new infrastructure systems. Engineering designs, plans, and institutions and regulations will need to be adaptable for a range of future conditions (conditions of climate, weather and extreme events, as well as changing societal demands for infrastructure services). For their current and future projects, engineers should: Involve all stakeholders (owners, financers, insurance, regulators, affected public, climate/weather scientists, etc.) in key decisions; Use low regret, adaptive strategies, such as robust decision making and the observational method, comply with relevant standards and regulations, and exceed their requirements where appropriate; Publish design studies and performance/failure investigations to extend the body of knowledge for advancement of practice. The engineering community should conduct observational and modeling research with climate/weather/social scientists and the concerned communities and account rationally for climate change in revised engineering standards and codes. This presentation presents initial research on decisionmaking under uncertainty for climate resilient infrastructure design.

A network-base analysis of CMIP5 "historical" experiments

NASA Astrophysics Data System (ADS)

Bracco, A.; Foudalis, I.; Dovrolis, C.

2012-12-01

In computer science, "complex network analysis" refers to a set of metrics, modeling tools and algorithms commonly used in the study of complex nonlinear dynamical systems. Its main premise is that the underlying topology or network structure of a system has a strong impact on its dynamics and evolution. By allowing to investigate local and non-local statistical interaction, network analysis provides a powerful, but only marginally explored, framework to validate climate models and investigate teleconnections, assessing their strength, range, and impacts on the climate system. In this work we propose a new, fast, robust and scalable methodology to examine, quantify, and visualize climate sensitivity, while constraining general circulation models (GCMs) outputs with observations. The goal of our novel approach is to uncover relations in the climate system that are not (or not fully) captured by more traditional methodologies used in climate science and often adopted from nonlinear dynamical systems analysis, and to explain known climate phenomena in terms of the network structure or its metrics. Our methodology is based on a solid theoretical framework and employs mathematical and statistical tools, exploited only tentatively in climate research so far. Suitably adapted to the climate problem, these tools can assist in visualizing the trade-offs in representing global links and teleconnections among different data sets. Here we present the methodology, and compare network properties for different reanalysis data sets and a suite of CMIP5 coupled GCM outputs. With an extensive model intercomparison in terms of the climate network that each model leads to, we quantify how each model reproduces major teleconnections, rank model performances, and identify common or specific errors in comparing model outputs and observations.

Monitoring Top-of-Atmosphere Radiative Energy Imbalance for Climate Prediction

NASA Technical Reports Server (NTRS)

Lin, Bing; Chambers, Lin H.; Stackhouse, Paul W., Jr.; Minnis, Patrick

2009-01-01

Large climate feedback uncertainties limit the prediction accuracy of the Earth s future climate with an increased CO2 atmosphere. One potential to reduce the feedback uncertainties using satellite observations of top-of-atmosphere (TOA) radiative energy imbalance is explored. Instead of solving the initial condition problem in previous energy balance analysis, current study focuses on the boundary condition problem with further considerations on climate system memory and deep ocean heat transport, which is more applicable for the climate. Along with surface temperature measurements of the present climate, the climate feedbacks are obtained based on the constraints of the TOA radiation imbalance. Comparing to the feedback factor of 3.3 W/sq m/K of the neutral climate system, the estimated feedback factor for the current climate system ranges from -1.3 to -1.0 W/sq m/K with an uncertainty of +/-0.26 W/sq m/K. That is, a positive climate feedback is found because of the measured TOA net radiative heating (0.85 W/sq m) to the climate system. The uncertainty is caused by the uncertainties in the climate memory length. The estimated time constant of the climate is large (70 to approx. 120 years), implying that the climate is not in an equilibrium state under the increasing CO2 forcing in the last century.

Earth System Modeling and Field Experiments in the Arctic-Boreal Zone - Report from a NASA Workshop

NASA Technical Reports Server (NTRS)

Sellers, Piers; Rienecker Michele; Randall, David; Frolking, Steve

2012-01-01

Early climate modeling studies predicted that the Arctic Ocean and surrounding circumpolar land masses would heat up earlier and faster than other parts of the planet as a result of greenhouse gas-induced climate change, augmented by the sea-ice albedo feedback effect. These predictions have been largely borne out by observations over the last thirty years. However, despite constant improvement, global climate models have greater difficulty in reproducing the current climate in the Arctic than elsewhere and the scatter between projections from different climate models is much larger in the Arctic than for other regions. Biogeochemical cycle (BGC) models indicate that the warming in the Arctic-Boreal Zone (ABZ) could lead to widespread thawing of the permafrost, along with massive releases of CO2 and CH4, and large-scale changes in the vegetation cover in the ABZ. However, the uncertainties associated with these BGC model predictions are even larger than those associated with the physical climate system models used to describe climate change. These deficiencies in climate and BGC models reflect, at least in part, an incomplete understanding of the Arctic climate system and can be related to inadequate observational data or analyses of existing data. A workshop was held at NASA/GSFC, May 22-24 2012, to assess the predictive capability of the models, prioritize the critical science questions; and make recommendations regarding new field experiments needed to improve model subcomponents. This presentation will summarize the findings and recommendations of the workshop, including the need for aircraft and flux tower measurements and extension of existing in-situ measurements to improve process modeling of both the physical climate and biogeochemical cycle systems. Studies should be directly linked to remote sensing investigations with a view to scaling up the improved process models to the Earth System Model scale. Data assimilation and observing system simulation studies should be used to guide the deployment pattern and schedule for inversion studies as well. Synthesis and integration of previously funded Arctic-Boreal projects (e.g., ABLE, BOREAS, ICESCAPE, ICEBRIDGE, ARCTAS) should also be undertaken. Such an effort would include the integration of multiple remotely sensed products from the EOS satellites and other resources.

Satellite Remote Sensing of Aerosol Forcing

NASA Technical Reports Server (NTRS)

Remer, Lorraine; Kaufman, Yoram; Ramaprasad, Jaya; Procopio, Aline; Levin, Zev

1999-01-01

Aerosol and cloud impacts on the earth's climate become a recent hot topic in climate studies. Having near future earth observing satellites, EOS-AM1 (Earth Observing System-AM1), ENVISAT (Environmental Satellites) and ADEOS-2 (Advanced Earth Observation Satellite-2), it will be a good timing to discuss how to obtain and use the microphysical parameters of aerosols and clouds for studying their climate impacts. Center for Climate System Research (CCSR) of the University of Tokyo invites you to 'Symposium on synergy between satellite-remote sensing and climate modeling in aerosol and cloud issues.' Here, we like to discuss the current and future issues in the remote sensing of aerosol and cloud microphysical parameters and their climate modeling studies. This workshop is also one of workshop series on aerosol remote sensing held in 1996, Washington D. C., and Meribel, France in 1999. It should be reminded that NASDA/ADEOS-1 & -2 (National Space Development Agency of Japan/Advanced Earth Observation Satellite-1 & -2) Workshop will be held in the following week (Dec. 6-10, 1999), so that this opportunity will be a perfect period for you to attend two meetings for satellite remote sensing in Japan. A weekend in Kyoto, the old capital of Japan, will add a nice memory to your visiting Japan. *Issues in the symposium: 1) most recent topics in aerosol and cloud remot sensing, and 2) utility of satellite products on climate modeling of cloud-aerosol effects.

Climate Model Evaluation using New Datasets from the Clouds and the Earth's Radiant Energy System (CERES)

NASA Technical Reports Server (NTRS)

Loeb, Norman G.; Wielicki, Bruce A.; Doelling, David R.

2008-01-01

There are some in the science community who believe that the response of the climate system to anthropogenic radiative forcing is unpredictable and we should therefore call off the quest . The key limitation in climate predictability is associated with cloud feedback. Narrowing the uncertainty in cloud feedback (and therefore climate sensitivity) requires optimal use of the best available observations to evaluate and improve climate model processes and constrain climate model simulations over longer time scales. The Clouds and the Earth s Radiant Energy System (CERES) is a satellite-based program that provides global cloud, aerosol and radiative flux observations for improving our understanding of cloud-aerosol-radiation feedbacks in the Earth s climate system. CERES is the successor to the Earth Radiation Budget Experiment (ERBE), which has widely been used to evaluate climate models both at short time scales (e.g., process studies) and at decadal time scales. A CERES instrument flew on the TRMM satellite and captured the dramatic 1998 El Nino, and four other CERES instruments are currently flying aboard the Terra and Aqua platforms. Plans are underway to fly the remaining copy of CERES on the upcoming NPP spacecraft (mid-2010 launch date). Every aspect of CERES represents a significant improvement over ERBE. While both CERES and ERBE measure broadband radiation, CERES calibration is a factor of 2 better than ERBE. In order to improve the characterization of clouds and aerosols within a CERES footprint, we use coincident higher-resolution imager observations (VIRS, MODIS or VIIRS) to provide a consistent cloud-aerosol-radiation dataset at climate accuracy. Improved radiative fluxes are obtained by using new CERES-derived Angular Distribution Models (ADMs) for converting measured radiances to fluxes. CERES radiative fluxes are a factor of 2 more accurate than ERBE overall, but the improvement by cloud type and at high latitudes can be as high as a factor of 5. Diurnal cycles are explicitly resolved by merging geostationary satellite observations with CERES and MODIS. Atmospheric state data are provided from a frozen version of the Global Modeling and Assimilation Office- Data Assimilation System at the NASA Goddard Space Flight Center. In addition to improving the accuracy of top-of-atmosphere (TOA) radiative fluxes, CERES also produces radiative fluxes at the surface and at several levels in the atmosphere using radiative transfer modeling, constrained at the TOA by CERES (ERBE was limited to the TOA). In all, CERES uses 11 instruments on 7 spacecraft all integrated to obtain climate accuracy in TOA to surface fluxes. This presentation will provide an overview of several new CERES datasets of interest to the climate community (including a new adjusted TOA flux dataset constrained by estimates of heat storage in the Earth system), show direct comparisons between CERES ad ERBE, and provide a detailed error analysis of CERES fluxes at various time and space scales. We discuss how observations can be used to reduce uncertainties in cloud feedback and climate sensitivity and strongly argue why we should NOT "call off the quest".

GFDL's ESM2 global coupled climate-carbon Earth System Models. Part I: physical formulation and baseline simulation characteristics

USGS Publications Warehouse

Dunne, John P.; John, Jasmin G.; Adcroft, Alistair J.; Griffies, Stephen M.; Hallberg, Robert W.; Shevalikova, Elena; Stouffer, Ronald J.; Cooke, William; Dunne, Krista A.; Harrison, Matthew J.; Krasting, John P.; Malyshev, Sergey L.; Milly, P.C.D.; Phillipps, Peter J.; Sentman, Lori A.; Samuels, Bonita L.; Spelman, Michael J.; Winton, Michael; Wittenberg, Andrew T.; Zadeh, Niki

2012-01-01

We describe the physical climate formulation and simulation characteristics of two new global coupled carbon-climate Earth System Models, ESM2M and ESM2G. These models demonstrate similar climate fidelity as the Geophysical Fluid Dynamics Laboratory's previous CM2.1 climate model while incorporating explicit and consistent carbon dynamics. The two models differ exclusively in the physical ocean component; ESM2M uses Modular Ocean Model version 4.1 with vertical pressure layers while ESM2G uses Generalized Ocean Layer Dynamics with a bulk mixed layer and interior isopycnal layers. Differences in the ocean mean state include the thermocline depth being relatively deep in ESM2M and relatively shallow in ESM2G compared to observations. The crucial role of ocean dynamics on climate variability is highlighted in the El Niño-Southern Oscillation being overly strong in ESM2M and overly weak ESM2G relative to observations. Thus, while ESM2G might better represent climate changes relating to: total heat content variability given its lack of long term drift, gyre circulation and ventilation in the North Pacific, tropical Atlantic and Indian Oceans, and depth structure in the overturning and abyssal flows, ESM2M might better represent climate changes relating to: surface circulation given its superior surface temperature, salinity and height patterns, tropical Pacific circulation and variability, and Southern Ocean dynamics. Our overall assessment is that neither model is fundamentally superior to the other, and that both models achieve sufficient fidelity to allow meaningful climate and earth system modeling applications. This affords us the ability to assess the role of ocean configuration on earth system interactions in the context of two state-of-the-art coupled carbon-climate models.

Climate Benchmark Missions: CLARREO

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A.; Young, David F.

2010-01-01

CLARREO (Climate Absolute Radiance and Refractivity Observatory) is one of the four Tier 1 missions recommended by the recent NRC decadal survey report on Earth Science and Applications from Space (NRC, 2007). The CLARREO mission addresses the need to rigorously observe climate change on decade time scales and to use decadal change observations as the most critical method to determine the accuracy of climate change projections such as those used in the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR4). A rigorously known accuracy of both decadal change observations as well as climate projections is critical in order to enable sound policy decisions. The CLARREO mission accomplishes this critical objective through highly accurate and SI traceable decadal change observations sensitive to many of the key uncertainties in climate radiative forcings, responses, and feedbacks that in turn drive uncertainty in current climate model projections. The same uncertainties also lead to uncertainty in attribution of climate change to anthropogenic forcing. The CLARREO breakthrough in decadal climate change observations is to achieve the required levels of accuracy and traceability to SI standards for a set of observations sensitive to a wide range of key decadal change variables. These accuracy levels are determined both by the projected decadal changes as well as by the background natural variability that such signals must be detected against. The accuracy for decadal change traceability to SI standards includes uncertainties of calibration, sampling, and analysis methods. Unlike most other missions, all of the CLARREO requirements are judged not by instantaneous accuracy, but instead by accuracy in large time/space scale average decadal changes. Given the focus on decadal climate change, the NRC Decadal Survey concluded that the single most critical issue for decadal change observations was their lack of accuracy and low confidence in observing the small but critical climate change signals. CLARREO is the recommended attack on this challenge, and builds on the last decade of climate observation advances in the Earth Observing System as well as metrological advances at NIST (National Institute of Standards and Technology) and other standards laboratories.

Advancing Climate Literacy through Investment in Science Education Faculty, and Future and Current Science Teachers: Providing Professional Learning, Instructional Materials, and a Model for Locally-Relevant and Culturally-Responsive Content

NASA Astrophysics Data System (ADS)

Halversen, C.; Apple, J. K.; McDonnell, J. D.; Weiss, E.

2014-12-01

The Next Generation Science Standards (NGSS) call for 5th grade students to "obtain and combine information about ways individual communities use science ideas to protect Earth's resources and environment". Achieving this, and other objectives in NGSS, will require changes in the educational system for both students and teachers. Teachers need access to high quality instructional materials and continuous professional learning opportunities starting in pre-service education. Students need highly engaging and authentic learning experiences focused on content that is strategically interwoven with science practices. Pre-service and early career teachers, even at the secondary level, often have relatively weak understandings of the complex Earth systems science required for understanding climate change and hold alternative ideas and naïve beliefs about the nature of science. These naïve understandings cause difficulties in portraying and teaching science, especially considering what is being called for in NGSS. The ACLIPSE program focuses on middle school pre-service science teachers and education faculty because: (1) the concepts that underlie climate change align well with the disciplinary core ideas and practices in NGSS for middle grades; and (2) middle school is a critical time for capturing students interest in science as student engagement by eighth grade is the most effective predictor of student pursuit of science in high school and college. Capturing student attention at this age is critical for recruitment to STEM careers and lifelong climate literacy. THE ACLIPSE program uses cutting edge research and technology in ocean observing systems to provide educators with new tools to engage students that will lead to deeper understanding of the interactions between the ocean and climate systems. Establishing authentic, meaningful connections between indigenous and place-based, and technological climate observations will help generate a more holistic perspective on climate change and demonstrate that observing systems can enhance understanding. ACLIPSE materials strive to translate research about climate change effectively into understandable narratives of real world phenomena using ocean data, creating meaningful pathways into ocean-climate science for students in ALL communities.

Characteristics of Tropical Cyclones in High-Resolution Models of the Present Climate

NASA Technical Reports Server (NTRS)

Shaevitz, Daniel A.; Camargo, Suzana J.; Sobel, Adam H.; Jonas, Jeffery A.; Kim, Daeyhun; Kumar, Arun; LaRow, Timothy E.; Lim, Young-Kwon; Murakami, Hiroyuki; Roberts, Malcolm J.;

Characteristics of Tropical Cyclones in High-resolution Models in the Present Climate

NASA Technical Reports Server (NTRS)

Shaevitz, Daniel A.; Camargo, Suzana J.; Sobel, Adam H.; Jonas, Jeffrey A.; Kim, Daehyun; Kumar, Arun; LaRow, Timothy E.; Lim, Young-Kwon; Murakami, Hiroyuki; Reed, Kevin;

Earth Radiation Budget Science, 1978. 1: Introduction. [to obtain radiation budget measurements by satellite observation

NASA Technical Reports Server (NTRS)

1978-01-01

An earth radiation budget satellite system (ERBSS) is planned in order to understand climate on various temporal and spatial scales. The system consists of three satellites and is designed to obtain radiation budget data from the earth's surface. Among the topics discussed are the climate modeling and climate diagnostics, the applications of radiation modeling to ERBSS, and the influence of albedo clouds on radiation budget and atmospheric circulation.

A Bayesian Approach to Evaluating Consistency between Climate Model Output and Observations

NASA Astrophysics Data System (ADS)

Braverman, A. J.; Cressie, N.; Teixeira, J.

2010-12-01

Like other scientific and engineering problems that involve physical modeling of complex systems, climate models can be evaluated and diagnosed by comparing their output to observations of similar quantities. Though the global remote sensing data record is relatively short by climate research standards, these data offer opportunities to evaluate model predictions in new ways. For example, remote sensing data are spatially and temporally dense enough to provide distributional information that goes beyond simple moments to allow quantification of temporal and spatial dependence structures. In this talk, we propose a new method for exploiting these rich data sets using a Bayesian paradigm. For a collection of climate models, we calculate posterior probabilities its members best represent the physical system each seeks to reproduce. The posterior probability is based on the likelihood that a chosen summary statistic, computed from observations, would be obtained when the model's output is considered as a realization from a stochastic process. By exploring how posterior probabilities change with different statistics, we may paint a more quantitative and complete picture of the strengths and weaknesses of the models relative to the observations. We demonstrate our method using model output from the CMIP archive, and observations from NASA's Atmospheric Infrared Sounder.

Exploratory Climate Data Visualization and Analysis Using DV3D and UVCDAT

NASA Technical Reports Server (NTRS)

Maxwell, Thomas

2012-01-01

Earth system scientists are being inundated by an explosion of data generated by ever-increasing resolution in both global models and remote sensors. Advanced tools for accessing, analyzing, and visualizing very large and complex climate data are required to maintain rapid progress in Earth system research. To meet this need, NASA, in collaboration with the Ultra-scale Visualization Climate Data Analysis Tools (UVCOAT) consortium, is developing exploratory climate data analysis and visualization tools which provide data analysis capabilities for the Earth System Grid (ESG). This paper describes DV3D, a UV-COAT package that enables exploratory analysis of climate simulation and observation datasets. OV3D provides user-friendly interfaces for visualization and analysis of climate data at a level appropriate for scientists. It features workflow inte rfaces, interactive 40 data exploration, hyperwall and stereo visualization, automated provenance generation, and parallel task execution. DV30's integration with CDAT's climate data management system (COMS) and other climate data analysis tools provides a wide range of high performance climate data analysis operations. DV3D expands the scientists' toolbox by incorporating a suite of rich new exploratory visualization and analysis methods for addressing the complexity of climate datasets.

NASA and the U.S. climate program - A problem in data management

NASA Technical Reports Server (NTRS)

Quann, J. J.

1978-01-01

NASA's contribution to the total data base for the National Climate Plan will be to produce climate data sets from its experimental space observing systems and to maximize the value of these data for climate analysis and prediction. Validated data sets will be provided to NOAA for inclusion into their overall diagnostic data base. NASA data management for the Climate Plan will involve: (1) cataloging and retrieval of large integrated and distributed data sets upon user demand, and (2) the storage equivalent of 100,000 digital data tapes. It will be the largest, most complex data system ever developed by NASA

NOAA's Role in Sustaining Global Ocean Observations: Future Plans for OAR's Ocean Observing and Monitoring Division

NASA Astrophysics Data System (ADS)

Todd, James; Legler, David; Piotrowicz, Stephen; Raymond, Megan; Smith, Emily; Tedesco, Kathy; Thurston, Sidney

2017-04-01

The Ocean Observing and Monitoring Division (OOMD, formerly the Climate Observation Division) of the National Oceanic and Atmospheric Administration (NOAA) Climate Program Office provides long-term, high-quality global observations, climate information and products for researchers, forecasters, assessments and other users of environmental information. In this context, OOMD-supported activities serve a foundational role in an enterprise that aims to advance 1) scientific understanding, 2) monitoring and prediction of climate and 3) understanding of potential impacts to enable a climate resilient society. Leveraging approximately 50% of the Global Ocean Observing System, OOMD employs an internationally-coordinated, multi-institution global strategy that brings together data from multiple platforms including surface drifting buoys, Argo profiling floats, flux/transport moorings (RAMA, PIRATA, OceanSITES), GLOSS tide gauges, SOOP-XBT and SOOP-CO2, ocean gliders and repeat hydrographic sections (GO-SHIP). OOMD also engages in outreach, education and capacity development activities to deliver training on the social-economic applications of ocean data. This presentation will highlight recent activities and plans for 2017 and beyond.

On the Reprocessing and Reanalysis of Observations for Climate

NASA Technical Reports Server (NTRS)

Bosilovich, Michael G.; Kennedy, John; Dee, Dick; ONeill, Alan

2012-01-01

The long observational record is critical to our understanding of the Earth s climate, but most observing systems were not developed with a climate objective in mind. As a result, tremendous efforts have gone into assessing and reprocessing the data records to improve their usefulness in climate studies. Many challenges remain, such as tracking the improvement of processing algorithms and limited spatial coverage. Reanalyses have fostered significant research, yet reliable global trends in many physical fields are not yet attainable, despite significant advances in data assimilation and numerical modeling. Communication of the strengths, limitations and uncertainties of reprocessed observations and reanalysis data, not only among the community of developers, but also with the extended research community, including the new generations of researchers and the decision makers is crucial for further advancement of the observational data records. WCRP provides the means to bridge the different motivating objectives on which national efforts focus.

Empirically Derived and Simulated Sensitivity of Vegetation to Climate Across Global Gradients of Temperature and Precipitation

NASA Astrophysics Data System (ADS)

Quetin, G. R.; Swann, A. L. S.

2017-12-01

Successfully predicting the state of vegetation in a novel environment is dependent on our process level understanding of the ecosystem and its interactions with the environment. We derive a global empirical map of the sensitivity of vegetation to climate using the response of satellite-observed greenness and leaf area to interannual variations in temperature and precipitation. Our analysis provides observations of ecosystem functioning; the vegetation interactions with the physical environment, across a wide range of climates and provide a functional constraint for hypotheses engendered in process-based models. We infer mechanisms constraining ecosystem functioning by contrasting how the observed and simulated sensitivity of vegetation to climate varies across climate space. Our analysis yields empirical evidence for multiple physical and biological mediators of the sensitivity of vegetation to climate as a systematic change across climate space. Our comparison of remote sensing-based vegetation sensitivity with modeled estimates provides evidence for which physiological mechanisms - photosynthetic efficiency, respiration, water supply, atmospheric water demand, and sunlight availability - dominate the ecosystem functioning in places with different climates. Earth system models are generally successful in reproducing the broad sign and shape of ecosystem functioning across climate space. However, this general agreement breaks down in hot wet climates where models simulate less leaf area during a warmer year, while observations show a mixed response but overall more leaf area during warmer years. In addition, simulated ecosystem interaction with temperature is generally larger and changes more rapidly across a gradient of temperature than is observed. We hypothesize that the amplified interaction and change are both due to a lack of adaptation and acclimation in simulations. This discrepancy with observations suggests that simulated responses of vegetation to global warming, and feedbacks between vegetation and climate, are too strong in the models.

Proceedings of the Ocean Climate Data Workshop

NASA Technical Reports Server (NTRS)

Churgin, James (Compiler)

1992-01-01

The First Consultative Meeting on Responsible National Oceanographic Data Centres (RNODC's) and Climate DataServices met in February 1988 and made a number of recommendations related to improving services to meet the needs of climate programmes. Included in these discussions was a recommendation for a Workshop on Ocean Climate Data Management. This workshop will be talking about ways to establish a Global Ocean Observing System (GOOS).

Arctic climate tipping points.

PubMed

Lenton, Timothy M

2012-02-01

There is widespread concern that anthropogenic global warming will trigger Arctic climate tipping points. The Arctic has a long history of natural, abrupt climate changes, which together with current observations and model projections, can help us to identify which parts of the Arctic climate system might pass future tipping points. Here the climate tipping points are defined, noting that not all of them involve bifurcations leading to irreversible change. Past abrupt climate changes in the Arctic are briefly reviewed. Then, the current behaviour of a range of Arctic systems is summarised. Looking ahead, a range of potential tipping phenomena are described. This leads to a revised and expanded list of potential Arctic climate tipping elements, whose likelihood is assessed, in terms of how much warming will be required to tip them. Finally, the available responses are considered, especially the prospects for avoiding Arctic climate tipping points.

Measuring Skin Temperatures with the IASI Hyperspectral Mission

NASA Astrophysics Data System (ADS)

Safieddine, S.; George, M.; Clarisse, L.; Clerbaux, C.

2017-12-01

Although the role of satellites in observing the variability of the Earth system has increased in recent decades, remote-sensing observations are still underexploited to accurately assess climate change fingerprints, in particular temperature variations. The IASI - Flux and Temperature (IASI-FT) project aims at providing new benchmarks for temperature observations using the calibrated radiances measured twice a day at any location by the IASI thermal infrared instrument on the suite of MetOp satellites (2006-2025). The main challenge is to achieve the accuracy and stability needed for climate studies, particularly that required for climate trends. Time series for land and sea skin surface temperatures are derived and compared with in situ measurements and atmospheric reanalysis. The observed trends are analyzed at seasonal and regional scales in order to disentangle natural (weather/dynamical) variability and human-induced climate forcings.

Improving Performance of the System Safety Function at Marshall Space Flight Center

NASA Technical Reports Server (NTRS)

Kiessling, Ed; Tippett, Donald D.; Shivers, Herb

2004-01-01

The Columbia Accident Investigation Board (CAIB) determined that organizational and management issues were significant contributors to the loss of Space Shuttle Columbia. In addition, the CAIB observed similarities between the organizational and management climate that preceded the Challenger accident and the climate that preceded the Columbia accident. To prevent recurrence of adverse organizational and management climates, effective implementation of the system safety function is suggested. Attributes of an effective system safety program are presented. The Marshall Space Flight Center (MSFC) system safety program is analyzed using the attributes. Conclusions and recommendations for improving the MSFC system safety program are offered in this case study.

[CLIMATE CHANGE AND ALLERGIC AIRWAY DISEASE] OBSERVATIONAL,LABORATORY, AND MODELING STUDIES OF THE IMPACTS OF CLIMATE CHANGE ONALLERGIC AIRWAY DISEASE

EPA Science Inventory

Based on these data and preliminary studies, this proposal will be composed of a multiscale source-to-dose analysis approach for assessing the exposure interactions of environmental and biological systems. Once the entire modeling system is validated, it will run f...

Characteristics of tropical cyclones in high-resolution models in the present climate

DOE PAGES

Shaevitz, Daniel A.; Camargo, Suzana J.; Sobel, Adam H.; ...

2014-12-05

The global characteristics of tropical cyclones (TCs) simulated by several climate models are analyzed and compared with observations. The global climate models were forced by the same sea surface temperature (SST) fields in two types of experiments, using climatological SST and interannually varying SST. TC tracks and intensities are derived from each model's output fields by the group who ran that model, using their own preferred tracking scheme; the study considers the combination of model and tracking scheme as a single modeling system, and compares the properties derived from the different systems. Overall, the observed geographic distribution of global TCmore » frequency was reasonably well reproduced. As expected, with the exception of one model, intensities of the simulated TC were lower than in observations, to a degree that varies considerably across models.« less

CLARREO Cornerstone of the Earth Observing System: Measuring Decadal Change Through Accurate Emitted Infrared and Reflected Solar Spectra and Radio Occultation

NASA Technical Reports Server (NTRS)

Sandford, Stephen P.

2010-01-01

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) is one of four Tier 1 missions recommended by the recent NRC Decadal Survey report on Earth Science and Applications from Space (NRC, 2007). The CLARREO mission addresses the need to provide accurate, broadly acknowledged climate records that are used to enable validated long-term climate projections that become the foundation for informed decisions on mitigation and adaptation policies that address the effects of climate change on society. The CLARREO mission accomplishes this critical objective through rigorous SI traceable decadal change observations that are sensitive to many of the key uncertainties in climate radiative forcings, responses, and feedbacks that in turn drive uncertainty in current climate model projections. These same uncertainties also lead to uncertainty in attribution of climate change to anthropogenic forcing. For the first time CLARREO will make highly accurate, global, SI-traceable decadal change observations sensitive to the most critical, but least understood, climate forcings, responses, and feedbacks. The CLARREO breakthrough is to achieve the required levels of accuracy and traceability to SI standards for a set of observations sensitive to a wide range of key decadal change variables. The required accuracy levels are determined so that climate trend signals can be detected against a background of naturally occurring variability. Climate system natural variability therefore determines what level of accuracy is overkill, and what level is critical to obtain. In this sense, the CLARREO mission requirements are considered optimal from a science value perspective. The accuracy for decadal change traceability to SI standards includes uncertainties associated with instrument calibration, satellite orbit sampling, and analysis methods. Unlike most space missions, the CLARREO requirements are driven not by the instantaneous accuracy of the measurements, but by accuracy in the large time/space scale averages that are key to understanding decadal changes.

NOAA's Scientific Data Stewardship Program

NASA Astrophysics Data System (ADS)

Bates, J. J.

2004-12-01

The NOAA mission is to understand and predict changes in the Earth's environment and conserve and manage coastal and marine resources to meet the Nation's economic, social and environmental needs. NOAA has responsibility for long-term archiving of the United States environmental data and has recently integrated several data management functions into a concept called Scientific Data Stewardship. Scientific Data Stewardship a new paradigm in data management consisting of an integrated suite of functions to preserve and exploit the full scientific value of NOAA's, and the world's, environmental data These functions include careful monitoring of observing system performance for long-term applications, the generation of authoritative long-term climate records from multiple observing platforms, and the proper archival of and timely access to data and metadata. NOAA has developed a conceptual framework to implement the functions of scientific data stewardship. This framework has five objectives: 1) develop real-time monitoring of all satellite observing systems for climate applications, 2) process large volumes of satellite data extending up to decades in length to account for systematic errors and to eliminate artifacts in the raw data (referred to as fundamental climate data records, FCDRs), 3) generate retrieved geophysical parameters from the FCDRs (referred to as thematic climate data records TCDRs) including combining observations from all sources, 4) conduct monitoring and research by analyzing data sets to uncover climate trends and to provide evaluation and feedback for steps 2) and 3), and 5) provide archives of metadata, FCDRs, and TCDRs, and facilitate distribution of these data to the user community. The term `climate data record' and related terms, such as climate data set, have been used for some time, but the climate community has yet to settle on a concensus definition. A recent United States National Academy of Sciences report recommends using the following definition: a climate data record (CDR) is a time series of measurements of sufficient length, consistency, and continuity to determine climate variability and change.

Self-organization of the climate system: Synchronized polar and oceanic teleconnections

NASA Astrophysics Data System (ADS)

Reischmann, Elizabeth Piccard

Synchronization is a widespread phenomenon in nonlinear, physical systems. It describes the phenomena of two or more weakly interacting, nonlinear oscillators adjust their natural frequencies until they come into phase and frequency lock. This behavior has been observed in biological, chemical and electronic systems, including neurons, fireflies, and computers, but has not been widely studied in climate. This thesis presents a study of several major examples of synchronized climatic systems, starting with ice age timings seemingly caused by the global climate's gradual synchronization to the Earth's 413kyr orbital eccentricity band, which may be responsible for the shift of ice age timings and amplitudes at the Mid-Pleistocene transition. The focus of the thesis, however, is centered the second major example of stable synchronization in the climate system: the continuous, 90 degree phase relationship of the polar climate signals for the entirety of the available ice record. The existence of a relationship between polar climates has been widely observed since ice core proxies became available in both Greenland and Antarctica. However, my work focuses on refining this phase relationship, utilizing it's linear nature to apply deconvolution and establish an energy transfer function. This transfer function shows a distinctly singular frequency, suggesting that climate signal is predominately communicated north to south with a period of 1.6kyrs. This narrows down possible mechanisms of polar connection dramatically, and is further investigated via a collection of intermediate proxy datasets and a set of more contemporary, synchronized, sea surface temperature dipoles. While the former fails to show any strong indication of the nature of the polar signal due in part to the overwhelming uncertainties present on the centennial and millennial scales, the latter demonstrates a large set of synchronized climate oscillations exist, communicate in a variety of networks, and have a direct connection to larger climate patterns (in this case, precipitation anomalies). Overall, this thesis represents a clear advance in our understanding of global climate dynamics, presents a new method of climate time series analysis, evidence of 16, stable, synchronized sea surface temperature dipoles, and provides a detailed sediment core database with explanations of age model limitations for future investigation.

Evaluating the Sensitivity of Agricultural Model Performance to Different Climate Inputs: Supplemental Material

NASA Technical Reports Server (NTRS)

Glotter, Michael J.; Ruane, Alex C.; Moyer, Elisabeth J.; Elliott, Joshua W.

2015-01-01

Projections of future food production necessarily rely on models, which must themselves be validated through historical assessments comparing modeled and observed yields. Reliable historical validation requires both accurate agricultural models and accurate climate inputs. Problems with either may compromise the validation exercise. Previous studies have compared the effects of different climate inputs on agricultural projections but either incompletely or without a ground truth of observed yields that would allow distinguishing errors due to climate inputs from those intrinsic to the crop model. This study is a systematic evaluation of the reliability of a widely used crop model for simulating U.S. maize yields when driven by multiple observational data products. The parallelized Decision Support System for Agrotechnology Transfer (pDSSAT) is driven with climate inputs from multiple sources reanalysis, reanalysis that is bias corrected with observed climate, and a control dataset and compared with observed historical yields. The simulations show that model output is more accurate when driven by any observation-based precipitation product than when driven by non-bias-corrected reanalysis. The simulations also suggest, in contrast to previous studies, that biased precipitation distribution is significant for yields only in arid regions. Some issues persist for all choices of climate inputs: crop yields appear to be oversensitive to precipitation fluctuations but under sensitive to floods and heat waves. These results suggest that the most important issue for agricultural projections may be not climate inputs but structural limitations in the crop models themselves.

Evaluating the sensitivity of agricultural model performance to different climate inputs

PubMed Central

Glotter, Michael J.; Moyer, Elisabeth J.; Ruane, Alex C.; Elliott, Joshua W.

2017-01-01

Projections of future food production necessarily rely on models, which must themselves be validated through historical assessments comparing modeled to observed yields. Reliable historical validation requires both accurate agricultural models and accurate climate inputs. Problems with either may compromise the validation exercise. Previous studies have compared the effects of different climate inputs on agricultural projections, but either incompletely or without a ground truth of observed yields that would allow distinguishing errors due to climate inputs from those intrinsic to the crop model. This study is a systematic evaluation of the reliability of a widely-used crop model for simulating U.S. maize yields when driven by multiple observational data products. The parallelized Decision Support System for Agrotechnology Transfer (pDSSAT) is driven with climate inputs from multiple sources – reanalysis, reanalysis bias-corrected with observed climate, and a control dataset – and compared to observed historical yields. The simulations show that model output is more accurate when driven by any observation-based precipitation product than when driven by un-bias-corrected reanalysis. The simulations also suggest, in contrast to previous studies, that biased precipitation distribution is significant for yields only in arid regions. However, some issues persist for all choices of climate inputs: crop yields appear oversensitive to precipitation fluctuations but undersensitive to floods and heat waves. These results suggest that the most important issue for agricultural projections may be not climate inputs but structural limitations in the crop models themselves. PMID:29097985

Using Climate Regionalization to Understand Climate Forecast System Version 2 (CFSv2) Precipitation Performance for the Conterminous United States (CONUS)

NASA Technical Reports Server (NTRS)

Regonda, Satish K.; Zaitchik, Benjamin F.; Badr, Hamada S.; Rodell, Matthew

2016-01-01

Dynamically based seasonal forecasts are prone to systematic spatial biases due to imperfections in the underlying global climate model (GCM). This can result in low-forecast skill when the GCM misplaces teleconnections or fails to resolve geographic barriers, even if the prediction of large-scale dynamics is accurate. To characterize and address this issue, this study applies objective climate regionalization to identify discrepancies between the Climate Forecast SystemVersion 2 (CFSv2) and precipitation observations across the Contiguous United States (CONUS). Regionalization shows that CFSv2 1 month forecasts capture the general spatial character of warm season precipitation variability but that forecast regions systematically differ from observation in some transition zones. CFSv2 predictive skill for these misclassified areas is systematically reduced relative to correctly regionalized areas and CONUS as a whole. In these incorrectly regionalized areas, higher skill can be obtained by using a regional-scale forecast in place of the local grid cell prediction.

Test Plan for a Calibration Demonstration System for the Reflected Solar Instrument for the Climate Absolute Radiance and Refractivity Observatory

NASA Technical Reports Server (NTRS)

Thome, Kurtis; McCorkel, Joel; Hair, Jason; McAndrew, Brendan; Daw, Adrian; Jennings, Donald; Rabin, Douglas

2012-01-01

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission addresses the need to observe high-accuracy, long-term climate change trends and to use decadal change observations as the most critical method to determine the accuracy of climate change. One of the major objectives of CLARREO is to advance the accuracy of SI traceable absolute calibration at infrared and reflected solar wavelengths. This advance is required to reach the on-orbit absolute accuracy required to allow climate change observations to survive data gaps while remaining sufficiently accurate to observe climate change to within the uncertainty of the limit of natural variability. While these capabilities exist at NIST in the laboratory, there is a need to demonstrate that it can move successfully from NIST to NASA and/or instrument vendor capabilities for future spaceborne instruments. The current work describes the test plan for the Solar, Lunar for Absolute Reflectance Imaging Spectroradiometer (SOLARIS) which is the calibration demonstration system (CDS) for the reflected solar portion of CLARREO. The goal of the CDS is to allow the 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. The end result of efforts with the SOLARIS CDS will be an SI-traceable error budget for reflectance retrieval using solar irradiance as a reference and methods for laboratory-based, absolute calibration suitable for climate-quality data collections. The CLARREO mission addresses the need to observe high-accuracy, long-term climate change trends and advance the accuracy of SI traceable absolute calibration. The current work describes the test plan for the SOLARIS which is the calibration demonstration system for the reflected solar portion of CLARREO. SOLARIS provides a test-bed for detector technologies, non-linearity determination and uncertainties, and application of future technology developments and suggested spacecraft instrument design modifications. The end result will be an SI-traceable error budget for reflectance retrieval using solar irradiance as a reference and methods for laboratory-based, absolute calibration suitable for climate-quality data collections.

An observational and modeling study of the August 2017 Florida climate extreme event.

NASA Astrophysics Data System (ADS)

Konduru, R.; Singh, V.; Routray, A.

2017-12-01

A special report on the climate extremes by the Intergovernmental Panel on Climate Change (IPCC) elucidates that the sole cause of disasters is due to the exposure and vulnerability of the human and natural system to the climate extremes. The cause of such a climate extreme could be anthropogenic or non-anthropogenic. Therefore, it is challenging to discern the critical factor of influence for a particular climate extreme. Such kind of perceptive study with reasonable confidence on climate extreme events is possible only if there exist any past case studies. A similar rarest climate extreme problem encountered in the case of Houston floods and extreme rainfall over Florida in August 2017. A continuum of hurricanes like Harvey and Irma targeted the Florida region and caused catastrophe. Due to the rarity of August 2017 Florida climate extreme event, it requires the in-depth study on this case. To understand the multi-faceted nature of the event, a study on the development of the Harvey hurricane and its progression and dynamics is significant. Current article focus on the observational and modeling study on the Harvey hurricane. A global model named as NCUM (The global UK Met office Unified Model (UM) operational at National Center for Medium Range Weather Forecasting, India, was utilized to simulate the Harvey hurricane. The simulated rainfall and wind fields were compared with the observational datasets like Tropical Rainfall Measuring Mission rainfall datasets and Era-Interim wind fields. The National Centre for Environmental Prediction (NCEP) automated tracking system was utilized to track the Harvey hurricane, and the tracks were analyzed statistically for different forecasts concerning the Harvey hurricane track of Joint Typhon Warning Centre. Further, the current study will be continued to investigate the atmospheric processes involved in the August 2017 Florida climate extreme event.

The cloud-phase feedback in the Super-parameterized Community Earth System Model

NASA Astrophysics Data System (ADS)

Burt, M. A.; Randall, D. A.

2016-12-01

Recent comparisons of observations and climate model simulations by I. Tan and colleagues have suggested that the Wegener-Bergeron-Findeisen (WBF) process tends to be too active in climate models, making too much cloud ice, and resulting in an exaggerated negative cloud-phase feedback on climate change. We explore the WBF process and its effect on shortwave cloud forcing in present-day and future climate simulations with the Community Earth System Model, and its super-parameterized counterpart. Results show that SP-CESM has much less cloud ice and a weaker cloud-phase feedback than CESM.

Climate forcings and feedbacks

NASA Technical Reports Server (NTRS)

Hansen, James

1993-01-01

Global temperature has increased significantly during the past century. Understanding the causes of observed global temperature change is impossible in the absence of adequate monitoring of changes in global climate forcings and radiative feedbacks. Climate forcings are changes imposed on the planet's energy balance, such as change of incoming sunlight or a human-induced change of surface properties due to deforestation. Radiative feedbacks are radiative changes induced by climate change, such as alteration of cloud properties or the extent of sea ice. Monitoring of global climate forcings and feedbacks, if sufficiently precise and long-term, can provide a very strong constraint on interpretation of observed temperature change. Such monitoring is essential to eliminate uncertainties about the relative importance of various climate change mechanisms including tropospheric sulfate aerosols from burning of coal and oil smoke from slash and burn agriculture, changes of solar irradiance changes of several greenhouse gases, and many other mechanisms. The considerable variability of observed temperature, together with evidence that a substantial portion of this variability is unforced indicates that observations of climate forcings and feedbacks must be continued for decades. Since the climate system responds to the time integral of the forcing, a further requirement is that the observations be carried out continuously. However, precise observations of forcings and feedbacks will also be able to provide valuable conclusions on shorter time scales. For example, knowledge of the climate forcing by increasing CFC's relative to the forcing by changing ozone is important to policymakers, as is information on the forcing by CO2 relative to the forcing by sulfate aerosols. It will also be possible to obtain valuable tests of climate models on short time scales, if there is precise monitoring of all forcings and feedbacks during and after events such as a large volcanic eruption or an El Nino.

Studying Climate Response to Forcing by the Nonlinear Dynamical Mode Decomposition

NASA Astrophysics Data System (ADS)

Mukhin, Dmitry; Gavrilov, Andrey; Loskutov, Evgeny; Feigin, Alexander

2017-04-01

An analysis of global climate response to external forcing, both anthropogenic (mainly, CO2 and aerosol) and natural (solar and volcanic), is needed for adequate predictions of global climate change. Being complex dynamical system, the climate reacts to external perturbations exciting feedbacks (both positive and negative) making the response non-trivial and poorly predictable. Thus an extraction of internal modes of climate system, investigation of their interaction with external forcings and further modeling and forecast of their dynamics, are all the problems providing the success of climate modeling. In the report the new method for principal mode extraction from climate data is presented. The method is based on the Nonlinear Dynamical Mode (NDM) expansion [1,2], but takes into account a number of external forcings applied to the system. Each NDM is represented by hidden time series governing the observed variability, which, together with external forcing time series, are mapped onto data space. While forcing time series are considered to be known, the hidden unknown signals underlying the internal climate dynamics are extracted from observed data by the suggested method. In particular, it gives us an opportunity to study the evolution of principal system's mode structure in changing external conditions and separate the internal climate variability from trends forced by external perturbations. Furthermore, the modes so obtained can be extrapolated beyond the observational time series, and long-term prognosis of modes' structure including characteristics of interconnections and responses to external perturbations, can be carried out. In this work the method is used for reconstructing and studying the principal modes of climate variability on inter-annual and decadal time scales accounting the external forcings such as anthropogenic emissions, variations of the solar activity and volcanic activity. The structure of the obtained modes as well as their response to external factors, e.g. forecast their change in 21 century under different CO2 emission scenarios, are discussed. [1] Mukhin, D., Gavrilov, A., Feigin, A., Loskutov, E., & Kurths, J. (2015). Principal nonlinear dynamical modes of climate variability. Scientific Reports, 5, 15510. http://doi.org/10.1038/srep15510 [2] Gavrilov, A., Mukhin, D., Loskutov, E., Volodin, E., Feigin, A., & Kurths, J. (2016). Method for reconstructing nonlinear modes with adaptive structure from multidimensional data. Chaos: An Interdisciplinary Journal of Nonlinear Science, 26(12), 123101. http://doi.org/10.1063/1.4968852

Research priorities in land use and land-cover change for the Earth system and integrated assessment modelling

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

Hibbard, Kathleen A.; Janetos, Anthony C.; Van Vuuren, Detlef

2010-11-15

This special issue has highlighted recent and innovative methods and results that integrate observations and AQ3 modelling analyses of regional to global aspect of biophysical and biogeochemical interactions of land-cover change with the climate system. Both the Earth System and the Integrated Assessment modeling communities recognize the importance of an accurate representation of land use and land-cover change to understand and quantify the interactions and feedbacks with the climate and socio-economic systems, respectively. To date, cooperation between these communities has been limited. Based on common interests, this work discusses research priorities in representing land use and land-cover change for improvedmore » collaboration across modelling, observing and measurement communities. Major research topics in land use and land-cover change are those that help us better understand (1) the interaction of land use and land cover with the climate system (e.g. carbon cycle feedbacks), (2) the provision of goods and ecosystem services by terrestrial (natural and anthropogenic) land-cover types (e.g. food production), (3) land use and management decisions and (4) opportunities and limitations for managing climate change (for both mitigation and adaptation strategies).« less

Detection and attribution of climate extremes in the observed record

DOE PAGES

Easterling, David R.; Kunkel, Kenneth E.; Wehner, Michael F.; ...

2016-01-18

We present an overview of practices and challenges related to the detection and attribution of observed changes in climate extremes. Detection is the identification of a statistically significant change in the extreme values of a climate variable over some period of time. Issues in detection discussed include data quality, coverage, and completeness. Attribution takes that detection of a change and uses climate model simulations to evaluate whether a cause can be assigned to that change. Additionally, we discuss a newer field of attribution, event attribution, where individual extreme events are analyzed for the express purpose of assigning some measure ofmore » whether that event was directly influenced by anthropogenic forcing of the climate system.« less

Climatological temperature senstivity of soil carbon turnover: Observations, simple scaling models, and ESMs

NASA Astrophysics Data System (ADS)

Koven, C. D.; Hugelius, G.; Lawrence, D. M.; Wieder, W. R.

2016-12-01

The projected loss of soil carbon to the atmosphere resulting from climate change is a potentially large but highly uncertain feedback to warming. The magnitude of this feedback is poorly constrained by observations and theory, and is disparately represented in Earth system models. To assess the likely long-term response of soils to climate change, spatial gradients in soil carbon turnover times can identify broad-scale and long-term controls on the rate of carbon cycling as a function of climate and other factors. Here we show that the climatological temperature control on carbon turnover in the top meter of global soils is more sensitive in cold climates than in warm ones. We present a simplified model that explains the high cold-climate sensitivity using only the physical scaling of soil freeze-thaw state across climate gradients. Critically, current Earth system models (ESMs) fail to capture this pattern, however it emerges from an ESM that explicitly resolves vertical gradients in soil climate and turnover. The weak tropical temperature sensitivity emerges from a different model that explicitly resolves mineralogical control on decomposition. These results support projections of strong future carbon-climate feedbacks from northern soils and demonstrate a method for ESMs to capture this emergent behavior.

Land-Atmosphere Interactions in Cold Environments (LATICE): The role of Atmosphere - Biosphere - Cryosphere - Hydrosphere interactions in a changing climate

NASA Astrophysics Data System (ADS)

Burkhart, J. F.; Tallaksen, L. M.; Stordal, F.; Berntsen, T.; Westermann, S.; Kristjansson, J. E.; Etzelmuller, B.; Hagen, J. O.; Schuler, T.; Hamran, S. E.; Lande, T. S.; Bryn, A.

2015-12-01

Climate change is impacting the high latitudes more rapidly and significantly than any other region of the Earth because of feedback processes between the atmosphere and the underlying surface. A warmer climate has already led to thawing of permafrost, reducing snow cover and a longer growing season; changes, which in turn influence the atmospheric circulation and the hydrological cycle. Still, many studies rely on one-way coupling between the atmosphere and the land surface, thereby neglecting important interactions and feedbacks. The observation, understanding and prediction of such processes from local to regional and global scales, represent a major scientific challenge that requires multidisciplinary scientific effort. The successful integration of earth observations (remote and in-situ data) and model development requires a harmonized research effort between earth system scientists, modelers and the developers of technologies and sensors. LATICE, which is recognized as a priority research area by the Faculty of Mathematics and Natural Sciences at the University of Oslo, aims to advance the knowledge base concerning land atmosphere interactions and their role in controlling climate variability and climate change at high northern latitudes. The consortium consists of an interdisciplinary team of experts from the atmospheric and terrestrial (hydrosphere, cryosphere and biosphere) research groups, together with key expertise on earth observations and novel sensor technologies. LATICE addresses critical knowledge gaps in the current climate assessment capacity through: Improving parameterizations of processes in earth system models controlling the interactions and feedbacks between the land (snow, ice, permafrost, soil and vegetation) and the atmosphere at high latitudes, including the boreal, alpine and artic zone. Assessing the influence of climate and land cover changes on water and energy fluxes. Integrating remote earth observations with in-situ data and suitable models to allow studies of finer-scale processes governing land-atmosphere interactions. Addressing observational challenges through the development of novel observational products and networks.

Antarctic Meteorology and Climatology

NASA Astrophysics Data System (ADS)

King, J. C.; Turner, J.

1997-07-01

This book is a comprehensive survey of the climatology and meteorology of Antarctica. The first section of the book reviews the methods by which we can observe the Antarctic atmosphere and presents a synthesis of climatological measurements. In the second section, the authors consider the processes that maintain the observed climate, from large-scale atmospheric circulation to small-scale processes. The final section reviews our current knowledge of the variability of Antarctic climate and the possible effects of "greenhouse" warming. The authors stress links among the Antarctic atmosphere, other elements of the Antarctic climate system (oceans, sea ice and ice sheets), and the global climate system. This volume will be of greatest interest to meteorologists and climatologists with a specialized interest in Antarctica, but it will also appeal to researchers in Antarctic glaciology, oceanography and biology. Graduates and undergraduates studying physical geography, and the earth, atmospheric and environmental sciences will find much useful background material in the book.

Aeolian Dunes: New High-Resolution Archives of Past Wind-Intensity and -Direction

NASA Astrophysics Data System (ADS)

Lindhorst, S.; Betzler, C.

2017-12-01

The understanding of the long-term variability of local wind-fields is most relevant for calibrating climate models and for the prediction of the socio-economic consequences of climate change. Continuous instrumental-based weather observations go back less than two centuries; aeolian dunes, however, contain an archive of past wind-field fluctuations which is basically unread. We present new ways to reconstruct annual to seasonal changes of wind intensity and predominant wind direction from dune-sediment composition and -geometries based on ground-penetrating radar (GPR) data, grain-size analyses and different age-dating approaches. Resulting proxy-based data series on wind are validated against instrumental based weather observations. Our approach can be applied to both recent as well as fossil dunes. Potential applications include the validation of climate models, the reconstruction of past supra-regional wind systems and the monitoring of future shifts in the climate system.

Physiological basis of climate change impacts on North American inland fishes

USGS Publications Warehouse

Whitney, James E.; Al-Chokhachy, Robert K.; Bunnell, David B.; Caldwell, Colleen A.; Cooke, Steven J.; Eliason, Erika J.; Rogers, Mark W.; Lynch, Abigail J.; Paukert, Craig P.

2016-01-01

Global climate change is altering freshwater ecosystems and affecting fish populations and communities. Underpinning changes in fish distribution and assemblage-level responses to climate change are individual-level physiological constraints. In this review, we synthesize the mechanistic effects of climate change on neuroendocrine, cardiorespiratory, immune, osmoregulatory, and reproductive systems of freshwater and diadromous fishes. Observed climate change effects on physiological systems are varied and numerous, including exceedance of critical thermal tolerances, decreased cardiorespiratory performance, compromised immune function, and altered patterns of individual reproductive investment. However, effects vary widely among and within species because of species, population, and even sex-specific differences in sensitivity and resilience and because of habitat-specific variation in the magnitude of climate-related environmental change. Research on the interactive effects of climate change with other environmental stressors across a broader range of fish diversity is needed to further our understanding of climate change effects on fish physiology.

Trends in seasonal warm anomalies across the contiguous United States: Contributions from natural climate variability

Treesearch

Lejiang Yu; Shiyuan Zhong; Warren E. Heilman; Xindi Bian

2018-01-01

Many studies have shown the importance of anthropogenic greenhouse gas emissions in contributing to observed upward trends in the occurrences of temperature extremes over the U.S. However, few studies have investigated the contributions of internal variability in the climate system to these observed trends. Here we use daily maximum temperature time series from the...

Earth System Modeling 2.0: A Blueprint for Models That Learn From Observations and Targeted High-Resolution Simulations

NASA Astrophysics Data System (ADS)

Schneider, Tapio; Lan, Shiwei; Stuart, Andrew; Teixeira, João.

2017-12-01

Climate projections continue to be marred by large uncertainties, which originate in processes that need to be parameterized, such as clouds, convection, and ecosystems. But rapid progress is now within reach. New computational tools and methods from data assimilation and machine learning make it possible to integrate global observations and local high-resolution simulations in an Earth system model (ESM) that systematically learns from both and quantifies uncertainties. Here we propose a blueprint for such an ESM. We outline how parameterization schemes can learn from global observations and targeted high-resolution simulations, for example, of clouds and convection, through matching low-order statistics between ESMs, observations, and high-resolution simulations. We illustrate learning algorithms for ESMs with a simple dynamical system that shares characteristics of the climate system; and we discuss the opportunities the proposed framework presents and the challenges that remain to realize it.

Climate change: Conflict of observational science, theory, and politics

USGS Publications Warehouse

Gerhard, L.C.

2004-01-01

Debate over whether human activity causes Earth climate change obscures the immensity of the dynamic systems that create and maintain climate on the planet. Anthropocentric debate leads people to believe that they can alter these planetary dynamic systems to prevent that they perceive as negative climate impacts on human civilization. Although politicians offer simplistic remedies, such as the Kyoto Protocol, global climate continues to change naturally. Better planning for the inevitable dislocations that have followed natural global climate changes throughout human history requires us to accept the fact that climate will change, and that human society must adapt to the changes. Over the last decade, the scientific literature reported a shift in emphasis from attempting to build theoretical models of putative human impacts on climate to understanding the planetwide dynamic processes that are the natural climate drivers. The current scientific literature is beginning to report the history of past climate change, the extent of natural climate variability, natural system drivers, and the episodicity of many climate changes. The scientific arguments have broadened from focus upon human effects on climate to include the array of natural phenomena that have driven global climate change for eons. However, significant political issues with long-term social consequences continue their advance. This paper summarizes recent scientific progress in climate science and arguments about human influence on climate. ?? 2004. The American Association of Petroleum Geologists. All rights reserved.

Simulating North American mesoscale convective systems with a convection-permitting climate model

NASA Astrophysics Data System (ADS)

Prein, Andreas F.; Liu, Changhai; Ikeda, Kyoko; Bullock, Randy; Rasmussen, Roy M.; Holland, Greg J.; Clark, Martyn

2017-10-01

Deep convection is a key process in the climate system and the main source of precipitation in the tropics, subtropics, and mid-latitudes during summer. Furthermore, it is related to high impact weather causing floods, hail, tornadoes, landslides, and other hazards. State-of-the-art climate models have to parameterize deep convection due to their coarse grid spacing. These parameterizations are a major source of uncertainty and long-standing model biases. We present a North American scale convection-permitting climate simulation that is able to explicitly simulate deep convection due to its 4-km grid spacing. We apply a feature-tracking algorithm to detect hourly precipitation from Mesoscale Convective Systems (MCSs) in the model and compare it with radar-based precipitation estimates east of the US Continental Divide. The simulation is able to capture the main characteristics of the observed MCSs such as their size, precipitation rate, propagation speed, and lifetime within observational uncertainties. In particular, the model is able to produce realistically propagating MCSs, which was a long-standing challenge in climate modeling. However, the MCS frequency is significantly underestimated in the central US during late summer. We discuss the origin of this frequency biases and suggest strategies for model improvements.

Improved spectral comparisons of paleoclimate models and observations via proxy system modeling: Implications for multi-decadal variability

NASA Astrophysics Data System (ADS)

Dee, S. G.; Parsons, L. A.; Loope, G. R.; Overpeck, J. T.; Ault, T. R.; Emile-Geay, J.

2017-10-01

The spectral characteristics of paleoclimate observations spanning the last millennium suggest the presence of significant low-frequency (multi-decadal to centennial scale) variability in the climate system. Since this low-frequency climate variability is critical for climate predictions on societally-relevant scales, it is essential to establish whether General Circulation models (GCMs) are able to simulate it faithfully. Recent studies find large discrepancies between models and paleoclimate data at low frequencies, prompting concerns surrounding the ability of GCMs to predict long-term, high-magnitude variability under greenhouse forcing (Laepple and Huybers, 2014a, 2014b). However, efforts to ground climate model simulations directly in paleoclimate observations are impeded by fundamental differences between models and the proxy data: proxy systems often record a multivariate and/or nonlinear response to climate, precluding a direct comparison to GCM output. In this paper we bridge this gap via a forward proxy modeling approach, coupled to an isotope-enabled GCM. This allows us to disentangle the various contributions to signals embedded in ice cores, speleothem calcite, coral aragonite, tree-ring width, and tree-ring cellulose. The paper addresses the following questions: (1) do forward-modeled ;pseudoproxies; exhibit variability comparable to proxy data? (2) if not, which processes alter the shape of the spectrum of simulated climate variability, and are these processes broadly distinguishable from climate? We apply our method to representative case studies, and broaden these insights with an analysis of the PAGES2k database (PAGES2K Consortium, 2013). We find that current proxy system models (PSMs) can help resolve model-data discrepancies on interannual to decadal timescales, but cannot account for the mismatch in variance on multi-decadal to centennial timescales. We conclude that, specific to this set of PSMs and isotope-enabled model, the paleoclimate record may exhibit larger low-frequency variability than GCMs currently simulate, indicative of incomplete physics and/or forcings.

Earth radiation balance and climate: Why the Moon is the wrong place to observe the Earth

NASA Astrophysics Data System (ADS)

Kandel, Robert S.

1994-06-01

Increasing 'greenhouse' gases in the Earth's atmosphere will perturb the Earth's radiation balance, forcing climate change over coming decades. Climate sensitivity depends critically on cloud-radiation feedback: its evaluation requires continual observation of changing patterns of Earth radiation balance and cloud cover. The Moon is the wrong place for such observations, with many disadvantages compared to an observation system combining platforms in low polar, intermediate-inclination and geostationary orbits. From the Moon, active observations are infeasible; thermal infrared observations require very large instruments to reach spatial resolutions obtained at much lower cost from geostationary or lower orbits. The Earth's polar zones are never well observed from the Moon; other zones are invisible more than half the time. The monthly illumination cycle leads to further bias in radiation budget determinations. The Earth will be a pretty sight from the Earth-side of the Moon, but serious Earth observations will be made elsewhere.

Status and Plans for Reanalysis at NASA/GMAO

NASA Technical Reports Server (NTRS)

Gelaro, Ron

2017-01-01

Reanalysis plays a critical role in GMAOs goal to enhance NASA's program of Earth observations, providing vital data sets for climate research and the development of future missions. As the breadth of NASAs observations expands to include multiple components of the Earth system, so does the need to assimilate observations from currently uncoupled components of the system in a more physically consistent manner. GMAOs most recent reanalysis of the satellite era, MERRA-2, has completed the period 1980-present, and is now running as a continuing global climate analysis with two- to three-week latency. MERRA-2 assimilates meteorological and aerosol observations as a weakly coupled assimilation system as a first step toward GMAOs longer term goal of developing an integrated Earth system analysis (IESA) capability that will couple assimilation systems for the atmosphere, ocean, land and chemistry. The GMAO strategy is to progress incrementally toward an IESA through an evolving combination of coupled systems and offline component reanalyses driven by, for example, MERRA-2 atmospheric forcing. Most recently, the GMAO has implemented a weakly coupled assimilation scheme for analyzing ocean skin temperature within the existing atmospheric analysis. The scheme uses background fields from a near-surface ocean diurnal layer model to assimilate surface-sensitive radiances plus in-situ observations along with all other observations in the atmospheric assimilation system. In addition, MERRA-2-driven simulations of the ocean (plus sea ice) and atmospheric chemistry (for the EOS period) are currently underway, as is the development of a coupled atmosphere-ocean assimilation system. This talk will describe the status of these ongoing efforts and the planned steps toward an IESA capability for climate research.

Ecological optimality in water-limited natural soil-vegetation systems. II - Tests and applications

NASA Technical Reports Server (NTRS)

Eagleson, P. S.; Tellers, T. E.

1982-01-01

The long-term optimal climatic climax soil-vegetation system is defined for several climates according to previous hypotheses in terms of two free parameters, effective porosity and plant water use coefficient. The free parameters are chosen by matching the predicted and observed average annual water yield. The resulting climax soil and vegetation properties are tested by comparison with independent observations of canopy density and average annual surface runoff. The climax properties are shown also to satisfy a previous hypothesis for short-term optimization of canopy density and water use coefficient. Using these hypotheses, a relationship between average evapotranspiration and optimum vegetation canopy density is derived and is compared with additional field observations. An algorithm is suggested by which the climax soil and vegetation properties can be calculated given only the climate parameters and the soil effective porosity. Sensitivity of the climax properties to the effective porosity is explored.

The Community Earth System Model-Polar Climate Working Group and the status of CESM2.

NASA Astrophysics Data System (ADS)

Bailey, D. A.; Holland, M. M.; DuVivier, A. K.

2017-12-01

The Polar Climate Working Group (PCWG) is a consortium of scientists who are interested in modeling and understanding the climate in the Arctic and the Antarctic, and how polar climate processes interact with and influence climate at lower latitudes. Our members come from universities and laboratories, and our interests span all elements of polar climate, from the ocean depths to the top of the atmosphere. In addition to conducting scientific modeling experiments, we are charged with contributing to the development and maintenance of the state-of-the-art sea ice model component (CICE) used in the Community Earth System Model (CESM). A recent priority for the PCWG has been to come up with innovative ways to bring the observational and modeling communities together. This will allow for more robust validation of climate model simulations, the development and implementation of more physically-based model parameterizations, improved data assimilation capabilities, and the better use of models to design and implement field experiments. These have been informed by topical workshops and scientific visitors that we have hosted in these areas. These activities will be discussed and information on how the better integration of observations and models has influenced the new version of the CESM, which is due to be released in late 2017, will be provided. Additionally, we will address how enhanced interactions with the observational community will contribute to model developments and validation moving forward.

Importance of anthropogenic climate impact, sampling error and urban development in sewer system design.

PubMed

Egger, C; Maurer, M

2015-04-15

Urban drainage design relying on observed precipitation series neglects the uncertainties associated with current and indeed future climate variability. Urban drainage design is further affected by the large stochastic variability of precipitation extremes and sampling errors arising from the short observation periods of extreme precipitation. Stochastic downscaling addresses anthropogenic climate impact by allowing relevant precipitation characteristics to be derived from local observations and an ensemble of climate models. This multi-climate model approach seeks to reflect the uncertainties in the data due to structural errors of the climate models. An ensemble of outcomes from stochastic downscaling allows for addressing the sampling uncertainty. These uncertainties are clearly reflected in the precipitation-runoff predictions of three urban drainage systems. They were mostly due to the sampling uncertainty. The contribution of climate model uncertainty was found to be of minor importance. Under the applied greenhouse gas emission scenario (A1B) and within the period 2036-2065, the potential for urban flooding in our Swiss case study is slightly reduced on average compared to the reference period 1981-2010. Scenario planning was applied to consider urban development associated with future socio-economic factors affecting urban drainage. The impact of scenario uncertainty was to a large extent found to be case-specific, thus emphasizing the need for scenario planning in every individual case. The results represent a valuable basis for discussions of new drainage design standards aiming specifically to include considerations of uncertainty. Copyright © 2015 Elsevier Ltd. All rights reserved.

A climate trend analysis of Uganda

USGS Publications Warehouse

Funk, Christopher C.; Rowland, Jim; Eilerts, Gary; White, Libby

2012-01-01

This brief report, drawing from a multi-year effort by the U.S. Agency for International Development (USAID) Famine Early Warning Systems Network (FEWS NET), identifies observed changes in rainfall and temperature in Uganda, based on an analysis of a quality-controlled, long time series of station observations throughout Uganda. Extending recent trends forward, it also provides a current and near-future context for understanding the actual nature of climate change impacts in the country, and a basis for identifying climate adaptations that may protect and improve the country's food security.

Higher climatological temperature sensitivity of soil carbon in cold than warm climates

NASA Astrophysics Data System (ADS)

Koven, Charles D.; Hugelius, Gustaf; Lawrence, David M.; Wieder, William R.

2017-11-01

The projected loss of soil carbon to the atmosphere resulting from climate change is a potentially large but highly uncertain feedback to warming. The magnitude of this feedback is poorly constrained by observations and theory, and is disparately represented in Earth system models (ESMs). To assess the climatological temperature sensitivity of soil carbon, we calculate apparent soil carbon turnover times that reflect long-term and broad-scale rates of decomposition. Here, we show that the climatological temperature control on carbon turnover in the top metre of global soils is more sensitive in cold climates than in warm climates and argue that it is critical to capture this emergent ecosystem property in global-scale models. We present a simplified model that explains the observed high cold-climate sensitivity using only the physical scaling of soil freeze-thaw state across climate gradients. Current ESMs fail to capture this pattern, except in an ESM that explicitly resolves vertical gradients in soil climate and carbon turnover. An observed weak tropical temperature sensitivity emerges in a different model that explicitly resolves mineralogical control on decomposition. These results support projections of strong carbon-climate feedbacks from northern soils and demonstrate a method for ESMs to capture this emergent behaviour.

Evaluation of Oceanic Surface Observation for Reproducing the Upper Ocean Structure in ECHAM5/MPI-OM

NASA Astrophysics Data System (ADS)

Luo, Hao; Zheng, Fei; Zhu, Jiang

2017-12-01

Better constraints of initial conditions from data assimilation are necessary for climate simulations and predictions, and they are particularly important for the ocean due to its long climate memory; as such, ocean data assimilation (ODA) is regarded as an effective tool for seasonal to decadal predictions. In this work, an ODA system is established for a coupled climate model (ECHAM5/MPI-OM), which can assimilate all available oceanic observations using an ensemble optimal interpolation approach. To validate and isolate the performance of different surface observations in reproducing air-sea climate variations in the model, a set of observing system simulation experiments (OSSEs) was performed over 150 model years. Generally, assimilating sea surface temperature, sea surface salinity, and sea surface height (SSH) can reasonably reproduce the climate variability and vertical structure of the upper ocean, and assimilating SSH achieves the best results compared to the true states. For the El Niño-Southern Oscillation (ENSO), assimilating different surface observations captures true aspects of ENSO well, but assimilating SSH can further enhance the accuracy of ENSO-related feedback processes in the coupled model, leading to a more reasonable ENSO evolution and air-sea interaction over the tropical Pacific. For ocean heat content, there are still limitations in reproducing the long time-scale variability in the North Atlantic, even if SSH has been taken into consideration. These results demonstrate the effectiveness of assimilating surface observations in capturing the interannual signal and, to some extent, the decadal signal but still highlight the necessity of assimilating profile data to reproduce specific decadal variability.

The Monash University Interactive Simple Climate Model

NASA Astrophysics Data System (ADS)

Dommenget, D.

2013-12-01

The Monash university interactive simple climate model is a web-based interface that allows students and the general public to explore the physical simulation of the climate system with a real global climate model. It is based on the Globally Resolved Energy Balance (GREB) model, which is a climate model published by Dommenget and Floeter [2011] in the international peer review science journal Climate Dynamics. The model simulates most of the main physical processes in the climate system in a very simplistic way and therefore allows very fast and simple climate model simulations on a normal PC computer. Despite its simplicity the model simulates the climate response to external forcings, such as doubling of the CO2 concentrations very realistically (similar to state of the art climate models). The Monash simple climate model web-interface allows you to study the results of more than a 2000 different model experiments in an interactive way and it allows you to study a number of tutorials on the interactions of physical processes in the climate system and solve some puzzles. By switching OFF/ON physical processes you can deconstruct the climate and learn how all the different processes interact to generate the observed climate and how the processes interact to generate the IPCC predicted climate change for anthropogenic CO2 increase. The presentation will illustrate how this web-base tool works and what are the possibilities in teaching students with this tool are.

ICEX: Ice and Climate Experiment. Report of science and applications working group

NASA Technical Reports Server (NTRS)

1979-01-01

The Ice and Climate Experiment (ICEX), a proposed program of coordinated investigations of the ice and snow masses of the Earth (the "cryosphere") is described. These investigations are to be carried out with the help of satellite, aircraft, and surface based observations. Measurements derived from the investigations will be applied to an understanding of the role of the cryosphere in the system that determines the Earth's climate, to a better prediction of the responses of the ice and snow to climatic change, to studies of the basic nature of ice forms and ice dynamics, and to the development of operational techniques for assisting such activities in the polar regions as transportation, exploitation of natural resources, and petroleum exploration and production. A high-inclination satellite system with a set of remote-sensing instruments specially tailored to the task of observing the important features of snow, sea ice, and the ice sheets of Greenland and the Antarctic is to be used to record the near-simultaneous observations of multiple geophysical parameters by complementary sensors.

Utility of AIRS Retrievals for Climate Studies

NASA Technical Reports Server (NTRS)

Molnar, Guyla I.; Susskind, Joel

2007-01-01

Satellites provide an ideal platform to study the Earth-atmosphere system on practically all spatial and temporal scales. Thus, one may expect that their rapidly growing datasets could provide crucial insights not only for short-term weather processes/predictions but into ongoing and future climate change processes as well. Though Earth-observing satellites have been around for decades, extracting climatically reliable information from their widely varying datasets faces rather formidable challenges. AIRS/AMSU is a state of the art infrared/microwave sounding system that was launched on the EOS Aqua platform on May 4, 2002, and has been providing operational quality measurements since September 2002. In addition to temperature and atmospheric constituent profiles, outgoing longwave radiation and basic cloud parameters are also derived from the AIRS/AMSU observations. However, so far the AIRS products have not been rigorously evaluated and/or validated on a large scale. Here we present preliminary assessments of monthly and 8-day mean AIRS "Version 4.0" retrieved products (available to the public through the DAAC at NASA/GSFC) to assess their utility for climate studies. First we present "consistency checks" by evaluating the time series of means, and "anomalies" (relative to the first 4 full years' worth of AIRS "climate statistics") of several climatically important retrieved parameters. Finally, we also present preliminary results regarding interrelationships of some of these geophysical variables, to assess to what extent they are consistent with the known physics of climate variability/change. In particular, we find at least one observed relationship which contradicts current general circulation climate (GCM) model results: the global water vapor climate feedback which is expected to be strongly positive is deduced to be slightly negative (shades of the "Lindzen effect"?). Though the current AIRS climatology covers only -4.5 years, it will hopefully extend much further into the future.

Ground-water/surface-water responses to global climate simulations, Santa Clara-Calleguas basin, Ventura County, California, 1950-93

USGS Publications Warehouse

Hanson, Randall T.; Dettinger, Michael D.

2005-01-01

Climate variations can play an important, if not always crucial, role in successful conjunctive management of ground water and surface water resources. This will require accurate accounting of the links between variations in climate, recharge, and withdrawal from the resource systems, accurate projection or predictions of the climate variations, and accurate simulation of the responses of the resource systems. To assess linkages and predictability of climate influences on conjunctive management, global climate model (GCM) simulated precipitation rates were used to estimate inflows and outflows from a regional ground water model (RGWM) of the coastal aquifers of the Santa Clara-Calleguas Basin at Ventura, California, for 1950 to 1993. Interannual to interdecadal time scales of the El Niño Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) climate variations are imparted to simulated precipitation variations in the Southern California area and are realistically imparted to the simulated ground water level variations through the climate-driven recharge (and discharge) variations. For example, the simulated average ground water level response at a key observation well in the basin to ENSO variations of tropical Pacific sea surface temperatures is 1.2 m/°C, compared to 0.9 m/°C in observations. This close agreement shows that the GCM-RGWM combination can translate global scale climate variations into realistic local ground water responses. Probability distributions of simulated ground water level excursions above a local water level threshold for potential seawater intrusion compare well to the corresponding distributions from observations and historical RGWM simulations, demonstrating the combination's potential usefulness for water management and planning. Thus the GCM-RGWM combination could be used for planning purposes and — when the GCM forecast skills are adequate — for near term predictions.

Ground water/surface water responses to global climate simulations, Santa Clara-Calleguas Basin, Ventura, California

USGS Publications Warehouse

Hanson, R.T.; Dettinger, M.D.

2005-01-01

Climate variations can play an important, if not always crucial, role in successful conjunctive management of ground water and surface water resources. This will require accurate accounting of the links between variations in climate, recharge, and withdrawal from the resource systems, accurate projection or predictions of the climate variations, and accurate simulation of the responses of the resource systems. To assess linkages and predictability of climate influences on conjunctive management, global climate model (GCM) simulated precipitation rates were used to estimate inflows and outflows from a regional ground water model (RGWM) of the coastal aquifers of the Santa ClaraCalleguas Basin at Ventura, California, for 1950 to 1993. Interannual to interdecadal time scales of the El Nin??o Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) climate variations are imparted to simulated precipitation variations in the Southern California area and are realistically imparted to the simulated ground water level variations through the climate-driven recharge (and discharge) variations. For example, the simulated average ground water level response at a key observation well in the basin to ENSO variations of tropical Pacific sea surface temperatures is 1.2 m/??C, compared to 0.9 m/??C in observations. This close agreement shows that the GCM-RGWM combination can translate global scale climate variations into realistic local ground water responses. Probability distributions of simulated ground water level excursions above a local water level threshold for potential seawater intrusion compare well to the corresponding distributions from observations and historical RGWM simulations, demonstrating the combination's potential usefulness for water management and planning. Thus the GCM-RGWM combination could be used for planning purposes and - when the GCM forecast skills are adequate - for near term predictions.

Evidence and implications of recent climate change in Northern Alaska and other Arctic regions

USGS Publications Warehouse

Hinzman, L.D.; Bettez, N.D.; Bolton, W.R.; Chapin, F.S.; Dyurgerov, M.B.; Fastie, C.L.; Griffith, B.; Hollister, R.D.; Hope, Allen; Huntington, H.P.; Jensen, A.M.; Jia, G.J.; Jorgenson, T.; Kane, D.L.; Klein, D.R.; Kofinas, G.; Lynch, A.H.; Lloyd, A.H.; McGuire, A.D.; Nelson, Frederick E.; Oechel, W.C.; Osterkamp, T.E.; Racine, C.H.; Romanovsky, V.E.; Stone, R.S.; Stow, D.A.; Sturm, M.; Tweedie, C.E.; Vourlitis, G.L.; Walker, M.D.; Walker, D.A.; Webber, P.J.; Welker, J.M.; Winker, K.S.; Yoshikawa, K.

2005-01-01

The Arctic climate is changing. Permafrost is warming, hydrological processes are changing and biological and social systems are also evolving in response to these changing conditions. Knowing how the structure and function of arctic terrestrial ecosystems are responding to recent and persistent climate change is paramount to understanding the future state of the Earth system and how humans will need to adapt. Our holistic review presents a broad array of evidence that illustrates convincingly; the Arctic is undergoing a system-wide response to an altered climatic state. New extreme and seasonal surface climatic conditions are being experienced, a range of biophysical states and processes influenced by the threshold and phase change of freezing point are being altered, hydrological and biogeochemical cycles are shifting, and more regularly human sub-systems are being affected. Importantly, the patterns, magnitude and mechanisms of change have sometimes been unpredictable or difficult to isolate due to compounding factors. In almost every discipline represented, we show how the biocomplexity of the Arctic system has highlighted and challenged a paucity of integrated scientific knowledge, the lack of sustained observational and experimental time series, and the technical and logistic constraints of researching the Arctic environment. This study supports ongoing efforts to strengthen the interdisciplinarity of arctic system science and improve the coupling of large scale experimental manipulation with sustained time series observations by incorporating and integrating novel technologies, remote sensing and modeling. ?? Springer 2005.

Impacts of Interactive Stratospheric Chemistry on Antarctic and Southern Ocean Climate Change in the Goddard Earth Observing System Version 5 (GEOS-5)

NASA Technical Reports Server (NTRS)

Li, Feng; Vikhliaev, Yury V.; Newman, Paul A.; Pawson, Steven; Perlwitz, Judith; Waugh, Darryn W.; Douglass, Anne R.

2016-01-01

Stratospheric ozone depletion plays a major role in driving climate change in the Southern Hemisphere. To date, many climate models prescribe the stratospheric ozone layer's evolution using monthly and zonally averaged ozone fields. However, the prescribed ozone underestimates Antarctic ozone depletion and lacks zonal asymmetries. In this study we investigate the impact of using interactive stratospheric chemistry instead of prescribed ozone on climate change simulations of the Antarctic and Southern Ocean. Two sets of 1960-2010 ensemble transient simulations are conducted with the coupled ocean version of the Goddard Earth Observing System Model, version 5: one with interactive stratospheric chemistry and the other with prescribed ozone derived from the same interactive simulations. The model's climatology is evaluated using observations and reanalysis. Comparison of the 1979-2010 climate trends between these two simulations reveals that interactive chemistry has important effects on climate change not only in the Antarctic stratosphere, troposphere, and surface, but also in the Southern Ocean and Antarctic sea ice. Interactive chemistry causes stronger Antarctic lower stratosphere cooling and circumpolar westerly acceleration during November-December-January. It enhances stratosphere-troposphere coupling and leads to significantly larger tropospheric and surface westerly changes. The significantly stronger surface wind stress trends cause larger increases of the Southern Ocean Meridional Overturning Circulation, leading to year-round stronger ocean warming near the surface and enhanced Antarctic sea ice decrease.

Low degree Earth's gravity coefficients determined from different space geodetic observations and climate models

NASA Astrophysics Data System (ADS)

Wińska, Małgorzata; Nastula, Jolanta

2017-04-01

Large scale mass redistribution and its transport within the Earth system causes changes in the Earth's rotation in space, gravity field and Earth's ellipsoid shape. These changes are observed in the ΔC21, ΔS21, and ΔC20 spherical harmonics gravity coefficients, which are proportional to the mass load-induced Earth rotational excitations. In this study, linear trend, decadal, inter-annual, and seasonal variations of low degree spherical harmonics coefficients of Earth's gravity field, determined from different space geodetic techniques, Gravity Recovery and Climate Experiment (GRACE), satellite laser ranging (SLR), Global Navigation Satellite System (GNSS), Earth rotation, and climate models, are examined. In this way, the contribution of each measurement technique to interpreting the low degree surface mass density of the Earth is shown. Especially, we evaluate an usefulness of several climate models from the Coupled Model Intercomparison Project phase 5 (CMIP5) to determine the low degree Earth's gravity coefficients using GRACE satellite observations. To do that, Terrestrial Water Storage (TWS) changes from several CMIP5 climate models are determined and then these simulated data are compared with the GRACE observations. Spherical harmonics ΔC21, ΔS21, and ΔC20 changes are calculated as the sum of atmosphere and ocean mass effect (GAC values) taken from GRACE and a land surface hydrological estimate from the selected CMIP5 climate models. Low degree Stokes coefficients of the surface mass density determined from GRACE, SLR, GNSS, Earth rotation measurements and climate models are compared to each other in order to assess their consistency. The comparison is done by using different types of statistical and signal processing methods.

The PIRATA Observing System in the Tropical Atlantic: Enhancements and perspectives

NASA Astrophysics Data System (ADS)

Hernandez, Fabrice; Araujo, Moacyr; Bourlès, Bernard; Brandt, Peter; Campos, Edmo; Giordani, Hervé; Lumpkin, Rick; McPhaden, Michael J.; Nobre, Paulo; Saravanan, Ramalingam

2017-04-01

PIRATA (Prediction and Research Moored Array in the Tropical Atlantic) is a multinational program established to improve our knowledge and understanding of ocean-atmosphere variability in the tropical Atlantic, a region that strongly influences the regional hydro-climates and, consequently, the economies of the regions bordering the Atlantic Ocean (e.g. West Africa, North-Eastern Brazil, the West Indies and the United States). PIRATA is motivated not only by fundamental scientific questions but also by societal needs for improved prediction of climatic variability and its impacts. PIRATA, initiated in 1997, is based around an array of moored buoys providing meteorological and oceanographic measurements transmitted in real-time, disseminated via GTS and Global Data Servers. Then, through yearly mooring maintenance, recorded high frequency data are collected and calibrated. The dedicated cruises of yearly maintenance allow complementary acquisition of a large number of measurements along repeated ship track lines and also provide platforms for deployments of other components of the observing system. Several kinds of operations are carried out in collaboration with other international programs. PIRATA provides invaluable data for numerous and varied applications, among which are analyses of climate variability on intraseasonal-to-decadal timescales, equatorial dynamics, mixed-layer temperature and salinity budgets, air-sea fluxes, data assimilation, and weather and climate forecasts. PIRATA is now 20 years old, well established and recognized as the backbone of the tropical Atlantic sustained observing system. Several enhancements have been achieved during recent years, including progressive updating of mooring systems and sensors, also in collaborations with and as a contribution to other programs (such as EU PREFACE and AtlantOS). Recent major accomplishments in terms of air-sea exchanges and climate predictability will be highlighted in this presentation. Future perspectives for the network will also be discussed in the framework of a sustainable Atlantic Ocean Observing System.

Preview of Our Changing Planet. The U.S. Climate Change Science Program for Fiscal Year 2008

DTIC Science & Technology

2007-04-01

reduce the uncertainty in predictions of the global and regional water cycle and surface climate. Sunlight not reflected back to space provides the...research elements include atmospheric composition, climate variability and change, the global water cycle , land-use and land-cover change, the global...entire planet, and researchers with the ability to better explain observed changes in the climate system. Global Water Cycle – Research associated with

Intraseasonal Variability in the Atmosphere-Ocean Climate System. Second Edition

NASA Technical Reports Server (NTRS)

Lau, William K. M.; Waliser, Duane E.

2011-01-01

Understanding and predicting the intraseasonal variability (ISV) of the ocean and atmosphere is crucial to improving long-range environmental forecasts and the reliability of climate change projections through climate models. This updated, comprehensive and authoritative second edition has a balance of observation, theory and modeling and provides a single source of reference for all those interested in this important multi-faceted natural phenomenon and its relation to major short-term climatic variations.

A conditional approach to determining the effect of anthropogenic climate change on very rare events.

NASA Astrophysics Data System (ADS)

Wehner, Michael; Pall, Pardeep; Zarzycki, Colin; Stone, Daithi

2016-04-01

Probabilistic extreme event attribution is especially difficult for weather events that are caused by extremely rare large-scale meteorological patterns. Traditional modeling techniques have involved using ensembles of climate models, either fully coupled or with prescribed ocean and sea ice. Ensemble sizes for the latter case ranges from several 100 to tens of thousand. However, even if the simulations are constrained by the observed ocean state, the requisite large-scale meteorological pattern may not occur frequently enough or even at all in free running climate model simulations. We present a method to ensure that simulated events similar to the observed event are modeled with enough fidelity that robust statistics can be determined given the large scale meteorological conditions. By initializing suitably constrained short term ensemble hindcasts of both the actual weather system and a counterfactual weather system where the human interference in the climate system is removed, the human contribution to the magnitude of the event can be determined. However, the change (if any) in the probability of an event of the observed magnitude is conditional not only on the state of the ocean/sea ice system but also on the prescribed initial conditions determined by the causal large scale meteorological pattern. We will discuss the implications of this technique through two examples; the 2013 Colorado flood and the 2014 Typhoon Haiyan.

Regional Arctic System Model (RASM): A Tool to Advance Understanding and Prediction of Arctic Climate Change at Process Scales

NASA Astrophysics Data System (ADS)

Maslowski, W.; Roberts, A.; Osinski, R.; Brunke, M.; Cassano, J. J.; Clement Kinney, J. L.; Craig, A.; Duvivier, A.; Fisel, B. J.; Gutowski, W. J., Jr.; Hamman, J.; Hughes, M.; Nijssen, B.; Zeng, X.

2014-12-01

The Arctic is undergoing rapid climatic changes, which are some of the most coordinated changes currently occurring anywhere on Earth. They are exemplified by the retreat of the perennial sea ice cover, which integrates forcing by, exchanges with and feedbacks between atmosphere, ocean and land. While historical reconstructions from Global Climate and Global Earth System Models (GC/ESMs) are in broad agreement with these changes, the rate of change in the GC/ESMs remains outpaced by observations. Reasons for that stem from a combination of coarse model resolution, inadequate parameterizations, unrepresented processes and a limited knowledge of physical and other real world interactions. We demonstrate the capability of the Regional Arctic System Model (RASM) in addressing some of the GC/ESM limitations in simulating observed seasonal to decadal variability and trends in the sea ice cover and climate. RASM is a high resolution, fully coupled, pan-Arctic climate model that uses the Community Earth System Model (CESM) framework. It uses the Los Alamos Sea Ice Model (CICE) and Parallel Ocean Program (POP) configured at an eddy-permitting resolution of 1/12° as well as the Weather Research and Forecasting (WRF) and Variable Infiltration Capacity (VIC) models at 50 km resolution. All RASM components are coupled via the CESM flux coupler (CPL7) at 20-minute intervals. RASM is an example of limited-area, process-resolving, fully coupled earth system model, which due to the additional constraints from lateral boundary conditions and nudging within a regional model domain facilitates detailed comparisons with observational statistics that are not possible with GC/ESMs. In this talk, we will emphasize the utility of RASM to understand sensitivity to variable parameter space, importance of critical processes, coupled feedbacks and ultimately to reduce uncertainty in arctic climate change projections.

NASA Earth Observations Informing Renewable Energy Management and Policy Decision Making

NASA Technical Reports Server (NTRS)

Eckman, Richard S.; Stackhouse, Paul W., Jr.

2008-01-01

The NASA Applied Sciences Program partners with domestic and international governmental organizations, universities, and private entities to improve their decisions and assessments. These improvements are enabled by using the knowledge generated from research resulting from spacecraft observations and model predictions conducted by NASA and providing these as inputs to the decision support and scenario assessment tools used by partner organizations. The Program is divided into eight societal benefit areas, aligned in general with the Global Earth Observation System of Systems (GEOSS) themes. The Climate Application of the Applied Sciences Program has as one of its focuses, efforts to provide for improved decisions and assessments in the areas of renewable energy technologies, energy efficiency, and climate change impacts. The goals of the Applied Sciences Program are aligned with national initiatives such as the U.S. Climate Change Science and Technology Programs and with those of international organizations including the Group on Earth Observations (GEO) and the Committee on Earth Observation Satellites (CEOS). Activities within the Program are funded principally through proposals submitted in response to annual solicitations and reviewed by peers.

Extra-Tropical Cyclones at Climate Scales: Comparing Models to Observations

NASA Astrophysics Data System (ADS)

Tselioudis, G.; Bauer, M.; Rossow, W.

2009-04-01

Climate is often defined as the accumulation of weather, and weather is not the concern of climate models. Justification for this latter sentiment has long been hidden behind coarse model resolutions and blunt validation tools based on climatological maps. The spatial-temporal resolutions of today's climate models and observations are converging onto meteorological scales, however, which means that with the correct tools we can test the largely unproven assumption that climate model weather is correct enough that its accumulation results in a robust climate simulation. Towards this effort we introduce a new tool for extracting detailed cyclone statistics from observations and climate model output. These include the usual cyclone characteristics (centers, tracks), but also adaptive cyclone-centric composites. We have created a novel dataset, the MAP Climatology of Mid-latitude Storminess (MCMS), which provides a detailed 6 hourly assessment of the areas under the influence of mid-latitude cyclones, using a search algorithm that delimits the boundaries of each system from the outer-most closed SLP contour. Using this we then extract composites of cloud, radiation, and precipitation properties from sources such as ISCCP and GPCP to create a large comparative dataset for climate model validation. A demonstration of the potential usefulness of these tools in process-based climate model evaluation studies will be shown.

Climate Central World Weather Attribution (WWA) project: Real-time extreme weather event attribution analysis

NASA Astrophysics Data System (ADS)

Haustein, Karsten; Otto, Friederike; Uhe, Peter; Allen, Myles; Cullen, Heidi

2015-04-01

Extreme weather detection and attribution analysis has emerged as a core theme in climate science over the last decade or so. By using a combination of observational data and climate models it is possible to identify the role of climate change in certain types of extreme weather events such as sea level rise and its contribution to storm surges, extreme heat events and droughts or heavy rainfall and flood events. These analyses are usually carried out after an extreme event has occurred when reanalysis and observational data become available. The Climate Central WWA project will exploit the increasing forecast skill of seasonal forecast prediction systems such as the UK MetOffice GloSea5 (Global seasonal forecasting system) ensemble forecasting method. This way, the current weather can be fed into climate models to simulate large ensembles of possible weather scenarios before an event has fully emerged yet. This effort runs along parallel and intersecting tracks of science and communications that involve research, message development and testing, staged socialization of attribution science with key audiences, and dissemination. The method we employ uses a very large ensemble of simulations of regional climate models to run two different analyses: one to represent the current climate as it was observed, and one to represent the same events in the world that might have been without human-induced climate change. For the weather "as observed" experiment, the atmospheric model uses observed sea surface temperature (SST) data from GloSea5 (currently) and present-day atmospheric gas concentrations to simulate weather events that are possible given the observed climate conditions. The weather in the "world that might have been" experiments is obtained by removing the anthropogenic forcing from the observed SSTs, thereby simulating a counterfactual world without human activity. The anthropogenic forcing is obtained by comparing the CMIP5 historical and natural simulations from a variety of CMIP5 model ensembles. Here, we present results for the UK 2013/14 winter floods as proof of concept and we show validation and testing results that demonstrate the robustness of our method. We also revisit the record temperatures over Europe in 2014 and present a detailed analysis of this attribution exercise as it is one of the events to demonstrate that we can make a sensible statement of how the odds for such a year to occur have changed while it still unfolds.

The Climate Variability & Predictability (CVP) Program at NOAA - Recent Program Advancements in Understanding AMOC

NASA Astrophysics Data System (ADS)

Lucas, S. E.

2016-12-01

The Climate Variability & Predictability (CVP) Program supports research aimed at providing process-level understanding of the climate system through observation, modeling, analysis, and field studies. This vital knowledge is needed to improve climate models and predictions so that scientists can better anticipate the impacts of future climate variability and change. To achieve its mission, the CVP Program supports research carried out at NOAA and other federal laboratories, NOAA Cooperative Institutes, and academic institutions. The Program also coordinates its sponsored projects with major national and international scientific bodies including the World Climate Research Programme (WCRP), the International and U.S. Climate Variability and Predictability (CLIVAR/US CLIVAR) Program, and the U.S. Global Change Research Program (USGCRP). The CVP program sits within NOAA's Climate Program Office (http://cpo.noaa.gov/CVP). This poster will present the recently funded CVP projects on improving the understanding Atlantic Meridional Overturning Circulation (AMOC), its impact on decadal predictability, and its relationship with the overall climate system.

Identification of reliable gridded reference data for statistical downscaling methods in Alberta

NASA Astrophysics Data System (ADS)

Eum, H. I.; Gupta, A.

2017-12-01

Climate models provide essential information to assess impacts of climate change at regional and global scales. However, statistical downscaling methods have been applied to prepare climate model data for various applications such as hydrologic and ecologic modelling at a watershed scale. As the reliability and (spatial and temporal) resolution of statistically downscaled climate data mainly depend on a reference data, identifying the most reliable reference data is crucial for statistical downscaling. A growing number of gridded climate products are available for key climate variables which are main input data to regional modelling systems. However, inconsistencies in these climate products, for example, different combinations of climate variables, varying data domains and data lengths and data accuracy varying with physiographic characteristics of the landscape, have caused significant challenges in selecting the most suitable reference climate data for various environmental studies and modelling. Employing various observation-based daily gridded climate products available in public domain, i.e. thin plate spline regression products (ANUSPLIN and TPS), inverse distance method (Alberta Townships), and numerical climate model (North American Regional Reanalysis) and an optimum interpolation technique (Canadian Precipitation Analysis), this study evaluates the accuracy of the climate products at each grid point by comparing with the Adjusted and Homogenized Canadian Climate Data (AHCCD) observations for precipitation, minimum and maximum temperature over the province of Alberta. Based on the performance of climate products at AHCCD stations, we ranked the reliability of these publically available climate products corresponding to the elevations of stations discretized into several classes. According to the rank of climate products for each elevation class, we identified the most reliable climate products based on the elevation of target points. A web-based system was developed to allow users to easily select the most reliable reference climate data at each target point based on the elevation of grid cell. By constructing the best combination of reference data for the study domain, the accurate and reliable statistically downscaled climate projections could be significantly improved.

Guess-Work and Reasonings on Centennial Evolution of Surface Air Temperature in Russia. Part IV: Towards Economic Estimations of Climate-Related Damages from the Bifurcation Analysis Viewpoint

NASA Astrophysics Data System (ADS)

Kolokolov, Yury; Monovskaya, Anna

The paper completes the cycle of the research devoted to the development of the experimental bifurcation analysis (not computer simulations) in order to answer the following questions: whether qualitative changes occur in the dynamics of local climate systems in a centennial timescale?; how to analyze such qualitative changes with daily resolution for local and regional space-scales?; how to establish one-to-one daily correspondence between the dynamics evolution and economic consequences for productions? To answer the questions, the unconventional conceptual model to describe the local climate dynamics was proposed and verified in the previous parts. That model (HDS-model) originates from the hysteresis regulator with double synchronization and has a variable structure due to competition between the amplitude quantization and the time quantization. The main advantage of the HDS-model is connected with the possibility to describe “internally” (on the basis of the self-regulation) the specific causal effects observed in the dynamics of local climate systems instead of “external” description of three states of the hysteresis behavior of climate systems (upper, lower and transient states). As a result, the evolution of the local climate dynamics is based on the bifurcation diagrams built by processing the data of meteorological observations, where the strange effects of the essential interannual daily variability of annual temperature variation are taken into account and explained. It opens the novel possibilities to analyze the local climate dynamics taking into account the observed resultant of all internal and external influences on each local climate system. In particular, the paper presents the viewpoint on how to estimate economic damages caused by climate-related hazards through the bifurcation analysis. That viewpoint includes the following ideas: practically each local climate system is characterized by its own time pattern of the natural qualitative changes in temperature dynamics over a century, so, any unified time window to determine the local climatic norms seems to be questionable; the temperature limits determined for climate-related technological hazards should be reasoned by the conditions of artificial human activity, but not by the climatic norms; the damages caused by such hazards can be approximately estimated in relation to the average annual profit of each production. Now, it becomes possible to estimate the minimal and maximal numbers of the specified hazards per year in order, first of all, to avoid unforeseen latent damages. Also, it becomes possible to make some useful relative estimation concerning damage and profit. We believe that the results presented in the cycle illustrate great practical competence of the current advances in the experimental bifurcation analysis. In particular, the developed QHS-analysis provides the novel prospects towards both how to adapt production to climatic changes and how to compensate negative technological impacts on environment.

Sustained Satellite Missions for Climate Data Records

NASA Technical Reports Server (NTRS)

Halpern, David

2012-01-01

Satellite CDRs possess the accuracy, longevity, and stability for sustained moni toring of critical variables to enhance understanding of the global integrated Earth system and predict future conditions. center dot Satellite CDRs are a critical element of a global climate observing system. center dot Satellite CDRs are a difficult challenge and require high - level managerial commitment, extensive intellectual capital, and adequate funding.

The computational future for climate and Earth system models: on the path to petaflop and beyond.

PubMed

Washington, Warren M; Buja, Lawrence; Craig, Anthony

2009-03-13

The development of the climate and Earth system models has had a long history, starting with the building of individual atmospheric, ocean, sea ice, land vegetation, biogeochemical, glacial and ecological model components. The early researchers were much aware of the long-term goal of building the Earth system models that would go beyond what is usually included in the climate models by adding interactive biogeochemical interactions. In the early days, the progress was limited by computer capability, as well as by our knowledge of the physical and chemical processes. Over the last few decades, there has been much improved knowledge, better observations for validation and more powerful supercomputer systems that are increasingly meeting the new challenges of comprehensive models. Some of the climate model history will be presented, along with some of the successes and difficulties encountered with present-day supercomputer systems.

Climatic variability effects on summer cropping systems of the Iberian Peninsula

NASA Astrophysics Data System (ADS)

Capa-Morocho, M.; Rodríguez-Fonseca, B.; Ruiz-Ramos, M.

2012-04-01

Climate variability and changes in the frequency of extremes events have a direct impact on crop yield and damages. Climate anomalies projections at monthly and yearly timescale allows us for adapting a cropping system (crops, varieties and management) to take advantage of favorable conditions or reduce the effect of adverse conditions. The objective of this work is to develop indices to evaluate the effect of climatic variability in summer cropping systems of Iberian Peninsula, in an attempt of relating yield variability to climate variability, extending the work of Rodríguez-Puebla (2004). This paper analyses the evolution of the yield anomalies of irrigated maize in several representative agricultural locations in Spain with contrasting temperature and precipitation regimes and compare it to the evolution of different patterns of climate variability, extending the methodology of Porter and Semenov (2005). To simulate maize yields observed daily data of radiation, maximum and minimum temperature and precipitation were used. These data were obtained from the State Meteorological Agency of Spain (AEMET). Time series of simulated maize yields were computed with CERES-maize model for periods ranging from 22 to 49 years, depending on the observed climate data available for each location. The computed standardized anomalies yields were projected on different oceanic and atmospheric anomalous fields and the resulting patterns were compared with a set of documented patterns from the National Oceanic and Atmospheric Administration (NOAA). The results can be useful also for climate change impact assessment, providing a scientific basis for selection of climate change scenarios where combined natural and forced variability represent a hazard for agricultural production. Interpretation of impact projections would also be enhanced.

Promoting Climate Literacy and Conceptual Understanding among In-service Secondary Science Teachers requires an Epistemological Perspective

NASA Astrophysics Data System (ADS)

Bhattacharya, D.; Forbes, C.; Roehrig, G.; Chandler, M. A.

2017-12-01

Promoting climate literacy among in-service science teachers necessitates an understanding of fundamental concepts about the Earth's climate System (USGCRP, 2009). Very few teachers report having any formal instruction in climate science (Plutzer et al., 2016), therefore, rather simple conceptions of climate systems and their variability exist, which has implications for students' science learning (Francies et al., 1993; Libarkin, 2005; Rebich, 2005). This study uses the inferences from a NASA Innovations in Climate Education (NICE) teacher professional development program (CYCLES) to establish the necessity for developing an epistemological perspective among teachers. In CYCLES, 19 middle and high school (male=8, female=11) teachers were assessed for their understanding of global climate change (GCC). A qualitative analysis of their concept maps and an alignment of their conceptions with the Essential Principles of Climate Literacy (NOAA, 2009) demonstrated that participants emphasized on EPCL 1, 3, 6, 7 focusing on the Earth system, atmospheric, social and ecological impacts of GCC. However, EPCL 4 (variability in climate) and 5 (data-based observations and modeling) were least represented and emphasized upon. Thus, participants' descriptions about global climatic patterns were often factual rather than incorporating causation (why the temperatures are increasing) and/or correlation (describing what other factors might influence global temperatures). Therefore, engaging with epistemic dimensions of climate science to understand the processes, tools, and norms through which climate scientists study the Earth's climate system (Huxter et al., 2013) is critical for developing an in-depth conceptual understanding of climate. CLiMES (Climate Modeling and Epistemology of Science), a NSF initiative proposes to use EzGCM (EzGlobal Climate Model) to engage students and teachers in designing and running simulations, performing data processing activities, and analyzing computational models to develop their own evidence-based claims about the Earth's climate system. We describe how epistemological investigations can be conducted using EzGCM to bring the scientific process and authentic climate science practice to middle and high school classrooms.

Climate change and observed climate trends in the fort cobb experimental watershed.

PubMed

Garbrecht, J D; Zhang, X C; Steiner, J L

2014-07-01

Recurring droughts in the Southern Great Plains of the United States are stressing the landscape, increasing uncertainty and risk in agricultural production, and impeding optimal agronomic management of crop, pasture, and grazing systems. The distinct possibility that the severity of recent droughts may be related to a greenhouse-gas induced climate change introduces new challenges for water resources managers because the intensification of droughts could represent a permanent feature of the future climate. Climate records of the Fort Cobb watershed in central Oklahoma were analyzed to determine if recent decade-long trends in precipitation and air temperature were consistent with climate change projections for central Oklahoma. The historical precipitation record did not reveal any compelling evidence that the recent 20-yr-long decline in precipitation was related to climate change. Also, precipitation projections by global circulation models (GCMs) displayed a flat pattern through the end of the 21st century. Neither observed nor projected precipitation displayed a multidecadal monotonic rising or declining trend consistent with an ongoing warming climate. The recent trend in observed annual precipitation was probably a decade-scale variation not directly related to the warming climate. On the other hand, the observed monotonic warming trend of 0.34°C decade that started around 1978 is consistent with GCM projections of increasing temperature for central Oklahoma. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Promise and Capability of NASA's Earth Observing System to Monitor Human-Induced Climate Variations

NASA Technical Reports Server (NTRS)

King, M. D.

2003-01-01

The Earth Observing System (EOS) is a space-based observing system comprised of a series of satellite sensors by which scientists can monitor the Earth, a Data and Information System (EOSDIS) enabling researchers worldwide to access the satellite data, and an interdisciplinary science research program to interpret the satellite data. The Moderate Resolution Imaging Spectroradiometer (MODIS), developed as part of the Earth Observing System (EOS) and launched on Terra in December 1999 and Aqua in May 2002, is designed to meet the scientific needs for satellite remote sensing of clouds, aerosols, water vapor, and land and ocean surface properties. This sensor and multi-platform observing system is especially well suited to observing detailed interdisciplinary components of the Earth s surface and atmosphere in and around urban environments, including aerosol optical properties, cloud optical and microphysical properties of both liquid water and ice clouds, land surface reflectance, fire occurrence, and many other properties that influence the urban environment and are influenced by them. In this presentation I will summarize the current capabilities of MODIS and other EOS sensors currently in orbit to study human-induced climate variations.

Designing domestic rainwater harvesting systems under different climatic regimes in Italy.

PubMed

Campisano, A; Gnecco, I; Modica, C; Palla, A

2013-01-01

Nowadays domestic rainwater harvesting practices are recognized as effective tools to improve the sustainability of drainage systems within the urban environment, by contributing to limiting the demand for potable water and, at the same time, by mitigating the generation of storm water runoff at the source. The final objective of this paper is to define regression curves to size domestic rainwater harvesting (DRWH) systems in the main Italian climatic regions. For this purpose, the Köppen-Geiger climatic classification is used and, furthermore, suitable precipitation sites are selected for each climatic region. A behavioural model is implemented to assess inflow, outflow and change in storage volume of a rainwater harvesting system according to daily mass balance simulations based on historical rainfall observations. The performance of the DRWH system under various climate and operational conditions is examined as a function of two non-dimensional parameters, namely the demand fraction (d) and the modified storage fraction (sm). This last parameter allowed the evaluation of the effects of the rainfall intra-annual variability on the system performance.

The Paleoclimate Uncertainty Cascade: Tracking Proxy Errors Via Proxy System Models.

NASA Astrophysics Data System (ADS)

Emile-Geay, J.; Dee, S. G.; Evans, M. N.; Adkins, J. F.

2014-12-01

Paleoclimatic observations are, by nature, imperfect recorders of climate variables. Empirical approaches to their calibration are challenged by the presence of multiple sources of uncertainty, which may confound the interpretation of signals and the identifiability of the noise. In this talk, I will demonstrate the utility of proxy system models (PSMs, Evans et al, 2013, 10.1016/j.quascirev.2013.05.024) to quantify the impact of all known sources of uncertainty. PSMs explicitly encode the mechanistic knowledge of the physical, chemical, biological and geological processes from which paleoclimatic observations arise. PSMs may be divided into sensor, archive and observation components, all of which may conspire to obscure climate signals in actual paleo-observations. As an example, we couple a PSM for the δ18O of speleothem calcite to an isotope-enabled climate model (Dee et al, submitted) to analyze the potential of this measurement as a proxy for precipitation amount. A simple soil/karst model (Partin et al, 2013, 10.1130/G34718.1) is used as sensor model, while a hiatus-permitting chronological model (Haslett & Parnell, 2008, 10.1111/j.1467-9876.2008.00623.x) is used as part of the observation model. This subdivision allows us to explicitly model the transformation from precipitation amount to speleothem calcite δ18O as a multi-stage process via a physical and chemical sensor model, and a stochastic archive model. By illustrating the PSM's behavior within the context of the climate simulations, we show how estimates of climate variability may be affected by each submodel's transformation of the signal. By specifying idealized climate signals(periodic vs. episodic, slow vs. fast) to the PSM, we investigate how frequency and amplitude patterns are modulated by sensor and archive submodels. To the extent that the PSM and the climate models are representative of real world processes, then the results may help us more accurately interpret existing paleodata, characterize their uncertainties, and design sampling strategies that exploit their strengths while mitigating their weaknesses.

DOE Contribution to the 2015 US CLIVAR Project Office Budget

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

DeWeaver, Eric; Patterson, Michael

The primary goal of the US Climate Variability and Predictability (CLIVAR) Project Office is to enable science community planning and implementation of research to understand and predict climate variability and change on intraseasonal-to-centennial timescales, through observations and modeling with emphasis on the role of the ocean and its interaction with other elements of the Earth system, and to serve the climate community and society through the coordination and facilitation of research on outstanding climate questions.

Check-Up of Planet Earth at the Turn of the Millennium: Anticipated New Phase in Earth Sciences

NASA Technical Reports Server (NTRS)

Kaufman, Y. J.; Ramanathan, V.

1998-01-01

Langley's remarkable solar and lunar spectra collected from Mt. Whitney inspired Arrhenius to develop the first quantitative climate model in 1896. In 1999, NASA's Earth Observing AM Satellite (EOS-AM) will repeat Langley's experiment, but for the entire planet, thus pioneering calibrated spectral observations from space. Conceived in response to real environmental problems, EOS-AM, in conjunction with other international satellite efforts, will fill a major gap in current efforts by providing quantitative global data sets with a resolution of few kilometers on the physical, chemical and biological elements of the earth system. Thus, like Langley's data, EOS-AM can revolutionize climate research by inspiring a new generation of climate system models and enable us to assess the human impact on the environment.

Regional-Scale Climate Change: Observations and Model Simulations

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

Bradley, Raymond S; Diaz, Henry F

2010-12-14

This collaborative proposal addressed key issues in understanding the Earth's climate system, as highlighted by the U.S. Climate Science Program. The research focused on documenting past climatic changes and on assessing future climatic changes based on suites of global and regional climate models. Geographically, our emphasis was on the mountainous regions of the world, with a particular focus on the Neotropics of Central America and the Hawaiian Islands. Mountain regions are zones where large variations in ecosystems occur due to the strong climate zonation forced by the topography. These areas are particularly susceptible to changes in critical ecological thresholds, andmore » we conducted studies of changes in phonological indicators based on various climatic thresholds.« less

Potential for added value in precipitation simulated by high-resolution nested Regional Climate Models and observations

NASA Astrophysics Data System (ADS)

di Luca, Alejandro; de Elía, Ramón; Laprise, René

2012-03-01

Regional Climate Models (RCMs) constitute the most often used method to perform affordable high-resolution regional climate simulations. The key issue in the evaluation of nested regional models is to determine whether RCM simulations improve the representation of climatic statistics compared to the driving data, that is, whether RCMs add value. In this study we examine a necessary condition that some climate statistics derived from the precipitation field must satisfy in order that the RCM technique can generate some added value: we focus on whether the climate statistics of interest contain some fine spatial-scale variability that would be absent on a coarser grid. The presence and magnitude of fine-scale precipitation variance required to adequately describe a given climate statistics will then be used to quantify the potential added value (PAV) of RCMs. Our results show that the PAV of RCMs is much higher for short temporal scales (e.g., 3-hourly data) than for long temporal scales (16-day average data) due to the filtering resulting from the time-averaging process. PAV is higher in warm season compared to cold season due to the higher proportion of precipitation falling from small-scale weather systems in the warm season. In regions of complex topography, the orographic forcing induces an extra component of PAV, no matter the season or the temporal scale considered. The PAV is also estimated using high-resolution datasets based on observations allowing the evaluation of the sensitivity of changing resolution in the real climate system. The results show that RCMs tend to reproduce relatively well the PAV compared to observations although showing an overestimation of the PAV in warm season and mountainous regions.

Mesoscale weather and climate modeling with the global non-hydrostatic Goddard Earth Observing System Model (GEOS-5) at cloud-permitting resolutions

NASA Astrophysics Data System (ADS)

Putman, W. M.; Suarez, M.

2009-12-01

The Goddard Earth Observing System Model (GEOS-5), an earth system model developed in the NASA Global Modeling and Assimilation Office (GMAO), has integrated the non-hydrostatic finite-volume dynamical core on the cubed-sphere grid. The extension to a non-hydrostatic dynamical framework and the quasi-uniform cubed-sphere geometry permits the efficient exploration of global weather and climate modeling at cloud permitting resolutions of 10- to 4-km on today's high performance computing platforms. We have explored a series of incremental increases in global resolution with GEOS-5 from it's standard 72-level 27-km resolution (~5.5 million cells covering the globe from the surface to 0.1 hPa) down to 3.5-km (~3.6 billion cells). We will present results from a series of forecast experiments exploring the impact of the non-hydrostatic dynamics at transition resolutions of 14- to 7-km, and the influence of increased horizontal/vertical resolution on convection and physical parameterizations within GEOS-5. Regional and mesoscale features of 5- to 10-day weather forecasts will be presented and compared with satellite observations. Our results will highlight the impact of resolution on the structure of cloud features including tropical convection and tropical cyclone predicability, cloud streets, von Karman vortices, and the marine stratocumulus cloud layer. We will also present experiment design and early results from climate impact experiments for global non-hydrostatic models using GEOS-5. Our climate experiments will focus on support for the Year of Tropical Convection (YOTC). We will also discuss a seasonal climate time-slice experiment design for downscaling coarse resolution century scale climate simulations to global non-hydrostatic resolutions of 14- to 7-km with GEOS-5.

Evaluation of a Mesoscale Convective System in Variable-Resolution CESM

NASA Astrophysics Data System (ADS)

Payne, A. E.; Jablonowski, C.

2017-12-01

Warm season precipitation over the Southern Great Plains (SGP) follows a well observed diurnal pattern of variability, peaking at night-time, due to the eastward propagation of mesoscale convection systems that develop over the eastern slopes of the Rockies in the late afternoon. While most climate models are unable to adequately capture the organization of convection and characteristic pattern of precipitation over this region, models with high enough resolution to explicitly resolve convection show improvement. However, high resolution simulations are computationally expensive and, in the case of regional climate models, are subject to boundary conditions. Newly developed variable resolution global climate models strike a balance between the benefits of high-resolution regional climate models and the large-scale dynamics of global climate models and low computational cost. Recently developed parameterizations that are insensitive to the model grid scale provide a way to improve model performance. Here, we present an evaluation of the newly available Cloud Layers Unified by Binormals (CLUBB) parameterization scheme in a suite of variable-resolution CESM simulations with resolutions ranging from 110 km to 7 km within a regionally refined region centered over the SGP Atmospheric Radiation Measurement (ARM) site. Simulations utilize the hindcast approach developed by the Department of Energy's Cloud-Associated Parameterizations Testbed (CAPT) for the assessment of climate models. We limit our evaluation to a single mesoscale convective system that passed over the region on May 24, 2008. The effects of grid-resolution on the timing and intensity of precipitation, as well as, on the transition from shallow to deep convection are assessed against ground-based observations from the SGP ARM site, satellite observations and ERA-Interim reanalysis.

Application of a stochastic weather generator to assess climate change impacts in a semi-arid climate: The Upper Indus Basin

NASA Astrophysics Data System (ADS)

Forsythe, N.; Fowler, H. J.; Blenkinsop, S.; Burton, A.; Kilsby, C. G.; Archer, D. R.; Harpham, C.; Hashmi, M. Z.

2014-09-01

Assessing local climate change impacts requires downscaling from Global Climate Model simulations. Here, a stochastic rainfall model (RainSim) combined with a rainfall conditioned weather generator (CRU WG) have been successfully applied in a semi-arid mountain climate, for part of the Upper Indus Basin (UIB), for point stations at a daily time-step to explore climate change impacts. Validation of the simulated time-series against observations (1961-1990) demonstrated the models' skill in reproducing climatological means of core variables with monthly RMSE of <2.0 mm for precipitation and ⩽0.4 °C for mean temperature and daily temperature range. This level of performance is impressive given complexity of climate processes operating in this mountainous context at the boundary between monsoonal and mid-latitude (westerly) weather systems. Of equal importance the model captures well the observed interannual variability as quantified by the first and last decile of 30-year climatic periods. Differences between a control (1961-1990) and future (2071-2100) regional climate model (RCM) time-slice experiment were then used to provide change factors which could be applied within the rainfall and weather models to produce perturbed ‘future' weather time-series. These project year-round increases in precipitation (maximum seasonal mean change:+27%, annual mean change: +18%) with increased intensity in the wettest months (February, March, April) and year-round increases in mean temperature (annual mean +4.8 °C). Climatic constraints on the productivity of natural resource-dependent systems were also assessed using relevant indices from the European Climate Assessment (ECA) and indicate potential future risk to water resources and local agriculture. However, the uniformity of projected temperature increases is in stark contrast to recent seasonally asymmetrical trends in observations, so an alternative scenario of extrapolated trends was also explored. We conclude that interannual variability in climate will continue to have the dominant impact on water resources management whichever trajectory is followed. This demonstrates the need for sophisticated downscaling methods which can evaluate changes in variability and sequencing of events to explore climate change impacts in this region.

The two-box model of climate: limitations and applications to planetary habitability and maximum entropy production studies.

PubMed

Lorenz, Ralph D

2010-05-12

The 'two-box model' of planetary climate is discussed. This model has been used to demonstrate consistency of the equator-pole temperature gradient on Earth, Mars and Titan with what would be predicted from a principle of maximum entropy production (MEP). While useful for exposition and for generating first-order estimates of planetary heat transports, it has too low a resolution to investigate climate systems with strong feedbacks. A two-box MEP model agrees well with the observed day : night temperature contrast observed on the extrasolar planet HD 189733b.

The two-box model of climate: limitations and applications to planetary habitability and maximum entropy production studies

PubMed Central

Lorenz, Ralph D.

2010-01-01

The ‘two-box model’ of planetary climate is discussed. This model has been used to demonstrate consistency of the equator–pole temperature gradient on Earth, Mars and Titan with what would be predicted from a principle of maximum entropy production (MEP). While useful for exposition and for generating first-order estimates of planetary heat transports, it has too low a resolution to investigate climate systems with strong feedbacks. A two-box MEP model agrees well with the observed day : night temperature contrast observed on the extrasolar planet HD 189733b. PMID:20368253

Sun's influence on climate: Explored with SDO

NASA Astrophysics Data System (ADS)

Lundstedt, H.

2010-09-01

Stunning images and movies recorded of the Sun, with Solar Dynamics Observatory (SDO), makes one wonder: How would this change our view on the Sun-Earth climate coupling? SDO shows a much more variable Sun, on all spatial and temporal scales. Detailed pictures of solar storms are foreseen to improve our understanding of the direct Sun-Earth coupling. Dynamo models, described by dynamical systems using input from helioseismic observations, are foreseen to improve our knowledge of the the Sun's cyclic influence on climate. Both the direct-, and the cycle-influence will be discussed in view of the new SDO observations.

An integrated, indicator framework for assessing large-scale variations and change in seasonal timing and phenology (Invited)

NASA Astrophysics Data System (ADS)

Betancourt, J. L.; Weltzin, J. F.

2013-12-01

As part of an effort to develop an Indicator System for the National Climate Assessment (NCA), the Seasonality and Phenology Indicators Technical Team (SPITT) proposed an integrated, continental-scale framework for understanding and tracking seasonal timing in physical and biological systems. The framework shares several metrics with the EPA's National Climate Change Indicators. The SPITT framework includes a comprehensive suite of national indicators to track conditions, anticipate vulnerabilities, and facilitate intervention or adaptation to the extent possible. Observed, modeled, and forecasted seasonal timing metrics can inform a wide spectrum of decisions on federal, state, and private lands in the U.S., and will be pivotal for international efforts to mitigation and adaptation. Humans use calendars both to understand the natural world and to plan their lives. Although the seasons are familiar concepts, we lack a comprehensive understanding of how variability arises in the timing of seasonal transitions in the atmosphere, and how variability and change translate and propagate through hydrological, ecological and human systems. For example, the contributions of greenhouse warming and natural variability to secular trends in seasonal timing are difficult to disentangle, including earlier spring transitions from winter (strong westerlies) to summer (weak easterlies) patterns of atmospheric circulation; shifts in annual phasing of daily temperature means and extremes; advanced timing of snow and ice melt and soil thaw at higher latitudes and elevations; and earlier start and longer duration of the growing and fire seasons. The SPITT framework aims to relate spatiotemporal variability in surface climate to (1) large-scale modes of natural climate variability and greenhouse gas-driven climatic change, and (2) spatiotemporal variability in hydrological, ecological and human responses and impacts. The hierarchical framework relies on ground and satellite observations, and includes metrics of surface climate seasonality, seasonality of snow and ice, land surface phenology, ecosystem disturbance seasonality, and organismal phenology. Recommended metrics met the following requirements: (a) easily measured by day-of-year, number of days, or in the case of species migrations, by the latitude of the observation on a given date; (b) are observed or can be calculated across a high density of locations in many different regions of the U.S.; and (c) unambiguously describe both spatial and temporal variability and trends in seasonal timing that are climatically driven. The SPITT framework is meant to provide climatic and strategic guidance for the growth and application of seasonal timing and phenological monitoring efforts. The hope is that additional national indicators based on observed phenology, or evidence-based algorithms calibrated with observational data, will evolve with sustained and broad-scale monitoring of climatically sensitive species and ecological processes.

Quantifying Key Climate Parameter Uncertainties Using an Earth System Model with a Dynamic 3D Ocean

NASA Astrophysics Data System (ADS)

Olson, R.; Sriver, R. L.; Goes, M. P.; Urban, N.; Matthews, D.; Haran, M.; Keller, K.

2011-12-01

Climate projections hinge critically on uncertain climate model parameters such as climate sensitivity, vertical ocean diffusivity and anthropogenic sulfate aerosol forcings. Climate sensitivity is defined as the equilibrium global mean temperature response to a doubling of atmospheric CO2 concentrations. Vertical ocean diffusivity parameterizes sub-grid scale ocean vertical mixing processes. These parameters are typically estimated using Intermediate Complexity Earth System Models (EMICs) that lack a full 3D representation of the oceans, thereby neglecting the effects of mixing on ocean dynamics and meridional overturning. We improve on these studies by employing an EMIC with a dynamic 3D ocean model to estimate these parameters. We carry out historical climate simulations with the University of Victoria Earth System Climate Model (UVic ESCM) varying parameters that affect climate sensitivity, vertical ocean mixing, and effects of anthropogenic sulfate aerosols. We use a Bayesian approach whereby the likelihood of each parameter combination depends on how well the model simulates surface air temperature and upper ocean heat content. We use a Gaussian process emulator to interpolate the model output to an arbitrary parameter setting. We use Markov Chain Monte Carlo method to estimate the posterior probability distribution function (pdf) of these parameters. We explore the sensitivity of the results to prior assumptions about the parameters. In addition, we estimate the relative skill of different observations to constrain the parameters. We quantify the uncertainty in parameter estimates stemming from climate variability, model and observational errors. We explore the sensitivity of key decision-relevant climate projections to these parameters. We find that climate sensitivity and vertical ocean diffusivity estimates are consistent with previously published results. The climate sensitivity pdf is strongly affected by the prior assumptions, and by the scaling parameter for the aerosols. The estimation method is computationally fast and can be used with more complex models where climate sensitivity is diagnosed rather than prescribed. The parameter estimates can be used to create probabilistic climate projections using the UVic ESCM model in future studies.

The Global Observing System in the Assimilation Context

NASA Technical Reports Server (NTRS)

Reinecker, Michele M.; Gelaro, R.; Pawson, S.; Reichle, R.; McCarty, W.

2011-01-01

Weather and climate analyses and predictions all rely on the global observing system. However, the observing system, whether atmosphere, ocean, or land surface, yields a diverse set of incomplete observations of the different components of Earth s environment. Data assimilation systems are essential to synthesize the wide diversity of in situ and remotely sensed observations into four-dimensional state estimates by combining the various observations with model-based estimates. Assimilation, or associated tools and products, are also useful in providing guidance for the evolution of the observing system of the future. This paper provides a brief overview of the global observing system and information gleaned through assimilation tools, and presents some evaluations of observing system gaps and issues.

Paleoclimate diagnostics: consistent large-scale temperature responses in warm and cold climates

NASA Astrophysics Data System (ADS)

Izumi, Kenji; Bartlein, Patrick; Harrison, Sandy

2015-04-01

The CMIP5 model simulations of the large-scale temperature responses to increased raditative forcing include enhanced land-ocean contrast, stronger response at higher latitudes than in the tropics, and differential responses in warm and cool season climates to uniform forcing. Here we show that these patterns are also characteristic of CMIP5 model simulations of past climates. The differences in the responses over land as opposed to over the ocean, between high and low latitudes, and between summer and winter are remarkably consistent (proportional and nearly linear) across simulations of both cold and warm climates. Similar patterns also appear in historical observations and paleoclimatic reconstructions, implying that such responses are characteristic features of the climate system and not simple model artifacts, thereby increasing our confidence in the ability of climate models to correctly simulate different climatic states. We also show the possibility that a small set of common mechanisms control these large-scale responses of the climate system across multiple states.

Climate: Into the 21st Century

NASA Astrophysics Data System (ADS)

Burroughs, William

2003-08-01

Toward the end of the twentieth century, it became evident to professionals working within the meterological arena that the world's climate system was showing signs of change that could not be adequately explained in terms of natural variation. Since that time there has been an increasing recognition that the climate system is changing as a result of human industries and lifestyles, and that the outcomes may prove catastrophic to the world's escalating population. Compiled by an international team formed under the auspices of the World Meteorological Organization (WMO), Climate: Into the 21st Century features an unrivalled collection of essays by the world's leading meteorological experts. These fully integrated contributions provide a perspective of the global climate system across the twentieth century, and describe some of the most arresting and extreme climatic events and their effects that have occurred during that time. In addition, the book traces the development of our capabilities to observe and monitor the climate system, and outlines our understanding of the predictability of climate on time-scales of months and longer. It concludes with a summary of the prospects for applying the twentieth century climate experience in order to benefit society in the twenty-first century. Lavishly illustrated in color, Climate is an accessible acccount of the challenges that climate poses at the start of the twenty-first century. Filled with fascinating facts and diagrams, it is written for a wide audience and will captivate the general reader interested in climate issues, and will be a valuable teaching resource. William Burroughs is a successful science author of books on climate, including Weather (Time Life, 2000), and Climate Change: A Multidisciplinary Approach (2001), Does the Weather Really Matter? (1997) and The Climate Revealed (1999), all published by Cambridge University Press.

Technical Report Series on Global Modeling and Data Assimilation, Volume 43. MERRA-2; Initial Evaluation of the Climate

NASA Technical Reports Server (NTRS)

Koster, Randal D. (Editor); Bosilovich, Michael G.; Akella, Santha; Lawrence, Coy; Cullather, Richard; Draper, Clara; Gelaro, Ronald; Kovach, Robin; Liu, Qing; Molod, Andrea;

Applicability of AgMERRA Forcing Dataset to Fill Gaps in Historical in-situ Meteorological Data

NASA Astrophysics Data System (ADS)

Bannayan, M.; Lashkari, A.; Zare, H.; Asadi, S.; Salehnia, N.

2015-12-01

Integrated assessment studies of food production systems use crop models to simulate the effects of climate and socio-economic changes on food security. Climate forcing data is one of those key inputs of crop models. This study evaluated the performance of AgMERRA climate forcing dataset to fill gaps in historical in-situ meteorological data for different climatic regions of Iran. AgMERRA dataset intercompared with in- situ observational dataset for daily maximum and minimum temperature and precipitation during 1980-2010 periods via Root Mean Square error (RMSE), Mean Absolute Error (MAE) and Mean Bias Error (MBE) for 17 stations in four climatic regions included humid and moderate, cold, dry and arid, hot and humid. Moreover, probability distribution function and cumulative distribution function compared between model and observed data. The results of measures of agreement between AgMERRA data and observed data demonstrated that there are small errors in model data for all stations. Except for stations which are located in cold regions, model data in the other stations illustrated under-prediction for daily maximum temperature and precipitation. However, it was not significant. In addition, probability distribution function and cumulative distribution function showed the same trend for all stations between model and observed data. Therefore, the reliability of AgMERRA dataset is high to fill gaps in historical observations in different climatic regions of Iran as well as it could be applied as a basis for future climate scenarios.

Characterization of Wildfire-Induced Aerosol Emissions From the Maritime Continent Peatland and Central African Dry Savannah with MISR and CALIPSO Aerosol Products

NASA Astrophysics Data System (ADS)

Lee, Huikyo; Jeong, Su-Jong; Kalashnikova, Olga; Tosca, Mika; Kim, Sang-Woo; Kug, Jong-Seong

2018-03-01

Aerosol plumes from wildfires affect the Earth's climate system through regulation of the radiative budget and clouds. However, optical properties of aerosols from individual wildfire smoke plumes and their resultant impact on regional climate are highly variable. Therefore, there is a critical need for observations that can constrain the partitioning between different types of aerosols. Here we present the apparent influence of regional ecosystem types on optical properties of wildfire-induced aerosols based on remote sensing observations from two satellite instruments and three ground stations. The independent observations commonly show that the ratio of the absorbing aerosols is significantly lower in smoke plumes from the Maritime Continent than those from Central Africa, so that their impacts on regional climate are different. The observed light-absorbing properties of wildfire-induced aerosols are explained by dominant ecosystem types such as wet peatlands for the Maritime Continent and dry savannah for Central Africa, respectively. These results suggest that the wildfire-aerosol-climate feedback processes largely depend on the terrestrial environments from which the fires originate. These feedbacks also interact with climate under greenhouse warming. Our analysis shows that aerosol optical properties retrieved based on satellite observations are critical in assessing wildfire-induced aerosols forcing in climate models. The optical properties of carbonaceous aerosol mixtures used by state-of-the-art chemistry climate models may overestimate emissions for absorbing aerosols from wildfires over the Maritime Continent.

Skilful seasonal forecasts of streamflow over Europe?

NASA Astrophysics Data System (ADS)

Arnal, Louise; Cloke, Hannah L.; Stephens, Elisabeth; Wetterhall, Fredrik; Prudhomme, Christel; Neumann, Jessica; Krzeminski, Blazej; Pappenberger, Florian

2018-04-01

This paper considers whether there is any added value in using seasonal climate forecasts instead of historical meteorological observations for forecasting streamflow on seasonal timescales over Europe. A Europe-wide analysis of the skill of the newly operational EFAS (European Flood Awareness System) seasonal streamflow forecasts (produced by forcing the Lisflood model with the ECMWF System 4 seasonal climate forecasts), benchmarked against the ensemble streamflow prediction (ESP) forecasting approach (produced by forcing the Lisflood model with historical meteorological observations), is undertaken. The results suggest that, on average, the System 4 seasonal climate forecasts improve the streamflow predictability over historical meteorological observations for the first month of lead time only (in terms of hindcast accuracy, sharpness and overall performance). However, the predictability varies in space and time and is greater in winter and autumn. Parts of Europe additionally exhibit a longer predictability, up to 7 months of lead time, for certain months within a season. In terms of hindcast reliability, the EFAS seasonal streamflow hindcasts are on average less skilful than the ESP for all lead times. The results also highlight the potential usefulness of the EFAS seasonal streamflow forecasts for decision-making (measured in terms of the hindcast discrimination for the lower and upper terciles of the simulated streamflow). Although the ESP is the most potentially useful forecasting approach in Europe, the EFAS seasonal streamflow forecasts appear more potentially useful than the ESP in some regions and for certain seasons, especially in winter for almost 40 % of Europe. Patterns in the EFAS seasonal streamflow hindcast skill are however not mirrored in the System 4 seasonal climate hindcasts, hinting at the need for a better understanding of the link between hydrological and meteorological variables on seasonal timescales, with the aim of improving climate-model-based seasonal streamflow forecasting.

CALIPSO at Four: Results and Progress

NASA Technical Reports Server (NTRS)

Winker, Dave; Hu, Yong; Pitts, Mike; Tackett, Jason; Kittaka, Chieko; Liu, Zhaoyan; Vaughan, Mark

2010-01-01

Aerosols and clouds play important roles in Earth?s climate system, but limitations in our ability to observe them globally limit our understanding of the climate system and our ability to model it. The CALIPSO satellite was developed to provide new capabilities to observe aerosol and cloud from space. CALIPSO carries the first polarization-sensitive lidar to fly in space, which has now provided a four-year record of global aerosol and cloud profiles. This paper briefly summarizes the status of the CALIPSO mission, describes some of the results from CALIPSO, and presents highlights of recent improvements in data products.

Precipitation Measurements From Space: Workshop report. An element of the climate observing system study

NASA Technical Reports Server (NTRS)

Atlas, D. (Editor); Thiele, O. W. (Editor)

1981-01-01

Global climate, agricultural uses for precipitation information, hydrological uses for precipitation, severe thunderstorms and local weather, global weather are addressed. Ground truth measurement, visible and infrared techniques, microwave radiometry and hybrid precipitation measurements, and spaceborne radar are discussed.

The Pathfinder Mission for Climate Absolute Radiance and Refractivity Observatory

NASA Technical Reports Server (NTRS)

Baize, R. R.; Boyer, C.; Cageao, R.; Currey, C.; Fleming, G. A.; Jackson, T.; Johnson, D. G.; Leckey, J.; Liu, X.; Lukashin, C.;

Pan-Arctic observations in GRENE Arctic Climate Change Research Project and its successor

NASA Astrophysics Data System (ADS)

Yamanouchi, Takashi

2016-04-01

We started a Japanese initiative - "Arctic Climate Change Research Project" - within the framework of the Green Network of Excellence (GRENE) Program, funded by the Ministry of Education, Culture, Sports, Science and Technology, Japan (MEXT), in 2011. This Project targeted understanding and forecasting "Rapid Change of the Arctic Climate System and its Global Influences." Four strategic research targets are set by the Ministry: 1. Understanding the mechanism of warming amplification in the Arctic; 2. Understanding the Arctic climate system for global climate and future change; 3. Evaluation of the impacts of Arctic change on the weather and climate in Japan, marine ecosystems and fisheries; 4. Projection of sea ice distribution and Arctic sea routes. Through a network of universities and institutions in Japan, this 5-year Project involves more than 300 scientists from 39 institutions and universities. The National Institute of Polar Research (NIPR) works as the core institute and The Japan Agency for Marine- Earth Science and Technology (JAMSTEC) joins as the supporting institute. There are 7 bottom up research themes approved: the atmosphere, terrestrial ecosystems, cryosphere, greenhouse gases, marine ecology and fisheries, sea ice and Arctic sea routes and climate modeling, among 22 applications. The Project will realize multi-disciplinal study of the Arctic region and connect to the projection of future Arctic and global climatic change by modeling. The project has been running since the beginning of 2011 and in those 5 years pan-Arctic observations have been carried out in many locations, such as Svalbard, Russian Siberia, Alaska, Canada, Greenland and the Arctic Ocean. In particular, 95 GHz cloud profiling radar in high precision was established at Ny-Ålesund, Svalbard, and intensive atmospheric observations were carried out in 2014 and 2015. In addition, the Arctic Ocean cruises by R/V "Mirai" (belonging to JAMSTEC) and other icebreakers belonging to other countries were conducted and mooring buoy observations were also carried out. The data retrieved during these observations was accumulated in the "Arctic Data archive System (ADS)" (https://ads.nipr.ac.jp/) and served with interfaces for analysis. In addition, modeling studies have been promoted from fundamental process model to general circulation model. The successor of the project, ArCS (Arctic Challenge for Sustainability), which lays delivering emphasis 
on robust scientific information to stakeholders for decision making and solving problems, was started in FY2015. Within this project, a cooperative observation of black carbon are planned to be started at Cape Baranova Station (AARI, Rusia), Severnaya Zemlya, and new activities including emphasizing aerological observations are also planned to be started for contributing to "Year of Polar Prediction (YOPP)" of Polar Prediction Project (PPP/ WMO). It will be desirable to have a future collaboration with IASOA.

Climate Change Education in Earth System Science

NASA Astrophysics Data System (ADS)

Hänsel, Stephanie; Matschullat, Jörg

2013-04-01

The course "Atmospheric Research - Climate Change" is offered to master Earth System Science students within the specialisation "Climate and Environment" at the Technical University Bergakademie Freiberg. This module takes a comprehensive approach to climate sciences, reaching from the natural sciences background of climate change via the social components of the issue to the statistical analysis of changes in climate parameters. The course aims at qualifying the students to structure the physical and chemical basics of the climate system including relevant feedbacks. The students can evaluate relevant drivers of climate variability and change on various temporal and spatial scales and can transform knowledge from climate history to the present and the future. Special focus is given to the assessment of uncertainties related to climate observations and projections as well as the specific challenges of extreme weather and climate events. At the end of the course the students are able to critically reflect and evaluate climate change related results of scientific studies and related issues in media. The course is divided into two parts - "Climate Change" and "Climate Data Analysis" and encompasses two lectures, one seminar and one exercise. The weekly "Climate change" lecture transmits the physical and chemical background for climate variation and change. (Pre)historical, observed and projected climate changes and their effects on various sectors are being introduced and discussed regarding their implications for society, economics, ecology and politics. The related seminar presents and discusses the multiple reasons for controversy in climate change issues, based on various texts. Students train the presentation of scientific content and the discussion of climate change aspects. The biweekly lecture on "Climate data analysis" introduces the most relevant statistical tools and methods in climate science. Starting with checking data quality via tools of exploratory data analysis the approaches on climate time series, trend analysis and extreme events analysis are explained. Tools to describe relations within the data sets and significance tests further corroborate this. Within the weekly exercises that have to be prepared at home, the students work with self-selected climate data sets and apply the learned methods. The presentation and discussion of intermediate results by the students is as much part of the exercises as the illustration of possible methodological procedures by the teacher using exemplary data sets. The total time expenditure of the course is 270 hours with 90 attendance hours. The remainder consists of individual studies, e.g., preparation of discussions and presentations, statistical data analysis, and scientific writing. Different forms of examination are applied including written or oral examination, scientific report, presentation and portfolio work.

Long-term climate change and the geochemical cycle of carbon

NASA Technical Reports Server (NTRS)

Marshall, Hal G.; Walker, James C. G.; Kuhn, William R.

1988-01-01

The response of the coupled climate-geochemical system to changes in paleography is examined in terms of the biogeochemical carbon cycle. The simple, zonally averaged energy balance climate model combined with a geochemical carbon cycle model, which was developed to study climate changes, is described. The effects of latitudinal distributions of the continents on the carbon cycle are investigated, and the global silicate weathering rate as a function of latitude is measured. It is observed that a concentration of land area at high altitudes results in a high CO2 partial pressure and a high global average temperature, and for land at low latitudes a cold globe and ice are detected. It is noted that the CO2 greenhouse feedback effect is potentially strong and has a stabilizing effect on the climate system.

CLARREO shortwave observing system simulation experiments of the twenty-first century: Simulator design and implementation

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

Feldman, D.R.; Algieri, C.A.; Ong, J.R.

2011-04-01

Projected changes in the Earth system will likely be manifested in changes in reflected solar radiation. This paper introduces an operational Observational System Simulation Experiment (OSSE) to calculate the signals of future climate forcings and feedbacks in top-of-atmosphere reflectance spectra. The OSSE combines simulations from the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report for the NCAR Community Climate System Model (CCSM) with the MODTRAN radiative transfer code to calculate reflectance spectra for simulations of current and future climatic conditions over the 21st century. The OSSE produces narrowband reflectances and broadband fluxes, the latter of which have been extensivelymore » validated against archived CCSM results. The shortwave reflectance spectra contain atmospheric features including signals from water vapor, liquid and ice clouds, and aerosols. The spectra are also strongly influenced by the surface bidirectional reflectance properties of predicted snow and sea ice and the climatological seasonal cycles of vegetation. By comparing and contrasting simulated reflectance spectra based on emissions scenarios with increasing projected and fixed present-day greenhouse gas and aerosol concentrations, we find that prescribed forcings from increases in anthropogenic sulfate and carbonaceous aerosols are detectable and are spatially confined to lower latitudes. Also, changes in the intertropical convergence zone and poleward shifts in the subsidence zones and the storm tracks are all detectable along with large changes in snow cover and sea ice fraction. These findings suggest that the proposed NASA Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission to measure shortwave reflectance spectra may help elucidate climate forcings, responses, and feedbacks.« less

Improving Constraints on Climate System Properties withAdditional Data and New Statistical and Sampling Methods

NASA Astrophysics Data System (ADS)

Forest, C. E.; Libardoni, A. G.; Sokolov, A. P.; Monier, E.

2017-12-01

We use the updated MIT Earth System Model (MESM) to derive the joint probability distribution function for Equilibrium Climate sensitivity (S), an effective heat diffusivity (Kv), and the net aerosol forcing (Faer). Using a new 1800-member ensemble of MESM runs, we derive PDFs by comparing model outputs against historical observations of surface temperature and global mean ocean heat content. We focus on how changes in (i) the MESM model, (ii) recent surface temperature and ocean heat content observations, and (iii) estimates of internal climate variability will all contribute to uncertainties. We show that estimates of S increase and Faer is less negative. These shifts result partly from new model forcing inputs but also from including recent temperature records that lead to higher values of S and Kv. We show that the parameter distributions are sensitive to the internal variability in the climate system. When considering these factors, we derive our best estimate for the joint probability distribution for the climate system properties. We estimate the 90-percent confidence intervals for climate sensitivity as 2.7-5.4 oC with a mode of 3.5 oC, for Kv as 1.9-23.0 cm2 s-1 with a mode of 4.41 cm2 s-1, and for Faer as -0.4 - -0.04 Wm-2 with a mode of -0.25 Wm-2. Lastly, we estimate TCR to be between 1.4 and 2.1 oC with a mode of 1.8 oC.

A Sustainable Early Warning System for Climate Change Impacts on Water Quality Management

NASA Astrophysics Data System (ADS)

Lee, T.; Tung, C.; Chung, N.

2007-12-01

In this era of rapid social and technological change leading to interesting life complexity and environmental displacement, both positive and negative effects among ecosystems call for a balance in which there are impacts by climate changes. Early warning systems for climate change impacts are necessary in order to allow society as a whole to properly and usefully assimilate the masses of new information and knowledge. Therefore, our research addresses to build up a sustainable early warning mechanism. The main goal is to mitigate the cumulative impacts on the environment of climate change and enhance adaptive capacities. An effective early warning system has been proven for protection. However, there is a problem that estimate future climate changes would be faced with high uncertainty. In general, take estimations for climate change impacts would use the data from General Circulation Models and take the analysis as the Intergovernmental Panel on Climate Change declared. We follow the course of the method for analyzing climate change impacts and attempt to accomplish the sustainable early warning system for water quality management. Climate changes impact not only on individual situation but on short-term variation and long-term gradually changes. This kind characteristic should adopt the suitable warning system for long-term formulation and short- term operation. To continue the on-going research of the long-term early warning system for climate change impacts on water quality management, the short-term early warning system is established by using local observation data for reappraising the warning issue. The combination of long-term and short-term system can provide more circumstantial details. In Taiwan, a number of studies have revealed that climate change impacts on water quality, especially in arid period, the concentration of biological oxygen demand may turn into worse. Rapid population growth would also inflict injury on its assimilative capacity to degenerate. To concern about those items, the sustainable early warning system is established and the initiative fall into the following categories: considering the implications for policies, applying adaptive strategies and informing the new climate changes. By setting up the framework of early warning system expectantly can defend stream area from impacts damaging and in sure the sustainable development.

Characterization of cocoa production, income diversification and shade tree management along a climate gradient in Ghana.

PubMed

Abdulai, Issaka; Jassogne, Laurence; Graefe, Sophie; Asare, Richard; Van Asten, Piet; Läderach, Peter; Vaast, Philippe

2018-01-01

Reduced climatic suitability due to climate change in cocoa growing regions of Ghana is expected in the coming decades. This threatens farmers' livelihood and the cocoa sector. Climate change adaptation requires an improved understanding of existing cocoa production systems and farmers' coping strategies. This study characterized current cocoa production, income diversification and shade tree management along a climate gradient within the cocoa belt of Ghana. The objectives were to 1) compare existing production and income diversification between dry, mid and wet climatic regions, and 2) identify shade trees in cocoa agroforestry systems and their distribution along the climatic gradient. Our results showed that current mean cocoa yield level of 288kg ha-1yr-1 in the dry region was significantly lower than in the mid and wet regions with mean yields of 712 and 849 kg ha-1 yr-1, respectively. In the dry region, farmers diversified their income sources with non-cocoa crops and off-farm activities while farmers at the mid and wet regions mainly depended on cocoa (over 80% of annual income). Two shade systems classified as medium and low shade cocoa agroforestry systems were identified across the studied regions. The medium shade system was more abundant in the dry region and associated to adaptation to marginal climatic conditions. The low shade system showed significantly higher yield in the wet region but no difference was observed between the mid and dry regions. This study highlights the need for optimum shade level recommendation to be climatic region specific.

Characterization of cocoa production, income diversification and shade tree management along a climate gradient in Ghana

PubMed Central

Jassogne, Laurence; Graefe, Sophie; Asare, Richard; Van Asten, Piet; Läderach, Peter; Vaast, Philippe

2018-01-01

Reduced climatic suitability due to climate change in cocoa growing regions of Ghana is expected in the coming decades. This threatens farmers’ livelihood and the cocoa sector. Climate change adaptation requires an improved understanding of existing cocoa production systems and farmers’ coping strategies. This study characterized current cocoa production, income diversification and shade tree management along a climate gradient within the cocoa belt of Ghana. The objectives were to 1) compare existing production and income diversification between dry, mid and wet climatic regions, and 2) identify shade trees in cocoa agroforestry systems and their distribution along the climatic gradient. Our results showed that current mean cocoa yield level of 288kg ha-1yr-1 in the dry region was significantly lower than in the mid and wet regions with mean yields of 712 and 849 kg ha-1 yr-1, respectively. In the dry region, farmers diversified their income sources with non-cocoa crops and off-farm activities while farmers at the mid and wet regions mainly depended on cocoa (over 80% of annual income). Two shade systems classified as medium and low shade cocoa agroforestry systems were identified across the studied regions. The medium shade system was more abundant in the dry region and associated to adaptation to marginal climatic conditions. The low shade system showed significantly higher yield in the wet region but no difference was observed between the mid and dry regions. This study highlights the need for optimum shade level recommendation to be climatic region specific. PMID:29659629

The Roadmap of Marine Observation Development Fostering the Understanding of Weather-Climate Characteristics in the Indonesian Maritime Continent

NASA Astrophysics Data System (ADS)

Sakya, A. E.; Ramdhani, A.; Florida, N.; Nurhayati, N.

2016-12-01

Indonesian Maritime Continent (MC) territory has a unique characteristics of weather-climate variation, due to its geographical position. MC accommodates complex atmosphere-ocean interaction phenomena with huge impacts not only on inter-seasonal, but also on global weather and short-term climate variation like Monsoons, Madden-Julian Oscillation (MJO), El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole Mode (IOD). These phenomena give major contribution to the dynamics of rainfall patterns and climate variability in Indonesian MC. The above complexities are more predictable because observations in the Central and Eastern Pacific (TAO/TRITON) and Indian Ocean (RAMA) are available. Moreover, global remote-sensing observations through satellites have also been developed and its data is easily accessed. At present, maritime weather observation in Indonesia relies on global cooperation, observations carried out using remote sensing equipment, and in-situ observations made by the National Ministries/Institution. However, availability of marine observation data in the MC is very limited, especially inside Indonesian waters. It thus serves a challenge to BMKG to become more active in participating national and international partnership programs to encourage continuous in-situ marine observations. BMKG and National Oceanic and Atmospheric Administration America (NOAA) has a joint cooperation to maintain RAMA array as part of the Global Ocean Observing System (GOOS) and to deliver in-situ oceanic and atmospheric data trhough so-called Indonesian Program Initiative on Maritime Observations and Analysis (Indonesia PRIMA). Within next 5 years, BMKG will focus to foster in-situ marine observation on surface as well as underwater through various observation methods. The development of which is framed within the relevant international programs such as - among others - Year of Maritime Continent (YMC) 2017, JCOMM 5 session 2017, and Tropical Pacific Observation System 2020. These activities are also aligned with Indonesian government program envisions global maritime axis through reinforcement of weather and climate services in sea and pushes connectivity between islands, water transportation safety, natural resources marine exploration activities and other maritime activities.

The impacts of climatologically-driven megadrought, past and future, on semi-arid watersheds and the water resource system they support in central Arizona, USA.

NASA Astrophysics Data System (ADS)

Murphy, K. W.; Ellis, A. W.

2017-12-01

The sustainability of water resource systems in the western United States has previously been brought into question by drought concerns and how it will be influenced by future climate change. Although decadal droughts are observed in instrumental records, the data are typically too short and the droughts too few to render the range of hydroclimatic variability that might impact modern water resource systems in the future. Natural modes of variability are not well represented in climate models, which limits the applicability of their downscaled projections in a region of interest since drought risk would be understated. Paleoclimate data have provided evidence of megadroughts from centuries ago whose hydrologic manifestations of climate variability could readily reoccur again in the future. These can be applied to research into watershed hydrologic response and resource system resilience - past, present, and future. A 645-year tree ring reconstruction of stream flow for the Salt and Verde River watersheds in central Arizona has revealed several drought periods, some more severe than seen in the 129-year instrumental record, including a late 16th century megadrought which affected large portions of the United States. This research study translated the tree ring record into net basin water supply which drives a reservoir operations simulation model to assess how the resource system performs under such severe drought. Regional climate change scenarios were developed from the observation that watershed climate sensitivity has been twice the global warming response. These were applied to the watersheds' temperature sensitivities and precipitation elasticities (reported at AGU2014) to obtain detailed renditions of hydrologic response should megadrought reoccur in a future climate. This provided one of the first rigorous projections of surface water supply under future climate change that amplifies the impact of megadrought arising from modes of climate variability often seen in the western United States. The implications to a large reservoir system serving 40% of water demand in the metropolitan Phoenix, Arizona area is reported which enables decision making for future adaptation planning.

Ocean Data Assimilation in Support of Climate Applications: Status and Perspectives.

PubMed

Stammer, D; Balmaseda, M; Heimbach, P; Köhl, A; Weaver, A

2016-01-01

Ocean data assimilation brings together observations with known dynamics encapsulated in a circulation model to describe the time-varying ocean circulation. Its applications are manifold, ranging from marine and ecosystem forecasting to climate prediction and studies of the carbon cycle. Here, we address only climate applications, which range from improving our understanding of ocean circulation to estimating initial or boundary conditions and model parameters for ocean and climate forecasts. Because of differences in underlying methodologies, data assimilation products must be used judiciously and selected according to the specific purpose, as not all related inferences would be equally reliable. Further advances are expected from improved models and methods for estimating and representing error information in data assimilation systems. Ultimately, data assimilation into coupled climate system components is needed to support ocean and climate services. However, maintaining the infrastructure and expertise for sustained data assimilation remains challenging.

Clime: analyzing and producing climate data in GIS environment

NASA Astrophysics Data System (ADS)

Cattaneo, Luigi; Rillo, Valeria; Mercogliano, Paola

2014-05-01

In the last years, Impacts on Soil and Coasts Division (ISC) of CMCC (Euro-Mediterranean Center on Climate Change) had several collaboration experiences with impact communities, including IS-ENES (FP7-INF) and SafeLand (FP7-ENV) projects, which involved a study of landslide risk in Europe, and is currently active in GEMINA (FIRB) and ORIENTGATE (SEE Transnational Cooperation Programme) research projects. As a result, it has brought research activities about different impact of climate changes as flood and landslide hazards, based on climate simulation obtained from the high resolution regional climate models COSMO CLM, developed at CMCC as member of the consortium CLM Assembly. ISC-Capua also collaborates with local institutions interested in atmospherical climate change and also of their impacts on the soil, such as river basin authorities in the Campania region, ARPA Emilia Romagna and ARPA Calabria. Impact models (e.g. hydraulic or stability models) are usually developed in a GIS environment, since they need an accurate territory description, so Clime has been designed to bridge the usually existing gap between climate data - both observed and simulated - gathered from different sources, and impact communities. The main goal of Clime, special purpose Geographic Information System (GIS) software integrated in ESRI ArcGIS Desktop 10, is to easily evaluate multiple climate features and study climate changes over specific geographical domains with their related effects on environment, including impacts on soil. Developed as an add-in tool, this software has been conceived for research activities of ISC Division in order to provide a substantial contribution during post-processing and validation phase. Therefore, it is possible to analyze and compare multiple datasets (observations, climate simulations, etc.) through processes involving statistical functions, percentiles, trends test and evaluation of extreme events with a flexible system of temporal and spatial filtering, and to represent results as maps, temporal and statistic plots (time series, seasonal cycles, PDFs, scatter plots, Taylor diagrams) or Excel tables; in addition, it features bias correction techniques for climate model results. Summarizing, Clime is able to provide users a simple and fast way to retrieve analysis over simulated climate data and observations within any geographical site of interest (provinces, regions, countries, etc.).

A common fallacy in climate model evaluation

NASA Astrophysics Data System (ADS)

Annan, J. D.; Hargreaves, J. C.; Tachiiri, K.

2012-04-01

We discuss the assessment of model ensembles such as that arising from the CMIP3 coordinated multi-model experiments. An important aspect of this is not merely the closeness of the models to observations in absolute terms but also the reliability of the ensemble spread as an indication of uncertainty. In this context, it has been widely argued that the multi-model ensemble of opportunity is insufficiently broad to adequately represent uncertainties regarding future climate change. For example, the IPCC AR4 summarises the consensus with the sentence: "Those studies also suggest that the current AOGCMs may not cover the full range of uncertainty for climate sensitivity." Similar claims have been made in the literature for other properties of the climate system, including the transient climate response and efficiency of ocean heat uptake. Comparison of model outputs with observations of the climate system forms an essential component of model assessment and is crucial for building our confidence in model predictions. However, methods for undertaking this comparison are not always clearly justified and understood. Here we show that the popular approach which forms the basis for the above claims, of comparing the ensemble spread to a so-called "observationally-constrained pdf", can be highly misleading. Such a comparison will almost certainly result in disagreement, but in reality tells us little about the performance of the ensemble. We present an alternative approach based on an assessment of the predictive performance of the ensemble, and show how it may lead to very different, and rather more encouraging, conclusions. We additionally outline some necessary conditions for an ensemble (or more generally, a probabilistic prediction) to be challenged by an observation.

Characterizing and Addressing the Need for Statistical Adjustment of Global Climate Model Data

NASA Astrophysics Data System (ADS)

White, K. D.; Baker, B.; Mueller, C.; Villarini, G.; Foley, P.; Friedman, D.

2017-12-01

As part of its mission to research and measure the effects of the changing climate, the U. S. Army Corps of Engineers (USACE) regularly uses the World Climate Research Programme's Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-model dataset. However, these data are generated at a global level and are not fine-tuned for specific watersheds. This often causes CMIP5 output to vary from locally observed patterns in the climate. Several downscaling methods have been developed to increase the resolution of the CMIP5 data and decrease systemic differences to support decision-makers as they evaluate results at the watershed scale. Evaluating preliminary comparisons of observed and projected flow frequency curves over the US revealed a simple framework for water resources decision makers to plan and design water resources management measures under changing conditions using standard tools. Using this framework as a basis, USACE has begun to explore to use of statistical adjustment to alter global climate model data to better match the locally observed patterns while preserving the general structure and behavior of the model data. When paired with careful measurement and hypothesis testing, statistical adjustment can be particularly effective at navigating the compromise between the locally observed patterns and the global climate model structures for decision makers.

Climate Change Observation Accuracy: Requirements and Economic Value

NASA Technical Reports Server (NTRS)

Wielicki, Bruce; Cooke, Roger; Golub, Alexander; Baize, Rosemary; Mlynczak, Martin; Lukashin, Constantin; Thome, Kurt; Shea, Yolanda; Kopp, Greg; Pilewskie, Peter;

Measuring progress of the global sea level observing system

NASA Astrophysics Data System (ADS)

Woodworth, Philip L.; Aarup, Thorkild; Merrifield, Mark; Mitchum, Gary T.; Le Provost, Christian

Sea level is such a fundamental parameter in the sciences of oceanography geophysics, and climate change, that in the mid-1980s, the Intergovernmental Oceanographic Commission (IOC) established the Global Sea Level Observing System (GLOSS). GLOSS was to improve the quantity and quality of data provided to the Permanent Service for Mean Sea Level (PSMSL), and thereby, data for input to studies of long-term sea level change by the Intergovernmental Panel on Climate Change (IPCC). It would also provide the key data needed for international programs, such as the World Ocean Circulation Experiment (WOCE) and later, the Climate Variability and Predictability Programme (CLIVAR).GLOSS is now one of the main observation components of the Joint Technical Commission for Oceanography and Marine Meteorology (JCOMM) of IOC and the World Meteorological Organization (WMO). Progress and deficiencies in GLOSS were presented in July to the 22nd IOC Assembly at UNESCO in Paris and are contained in the GLOSS Assessment Report (GAR) [IOC, 2003a].

Sensitivity of the regional climate in the Middle East and North Africa to volcanic perturbations

NASA Astrophysics Data System (ADS)

Dogar, Muhammad Mubashar; Stenchikov, Georgiy; Osipov, Sergey; Wyman, Bruce; Zhao, Ming

2017-08-01

The Middle East and North Africa (MENA) regional climate appears to be extremely sensitive to volcanic eruptions. Winter cooling after the 1991 Pinatubo eruption far exceeded the mean hemispheric temperature anomaly, even causing snowfall in Israel. To better understand MENA climate variability, the climate responses to the El Chichón and Pinatubo volcanic eruptions are analyzed using observations, NOAA/National Centers for Environmental Prediction Climate Forecast System Reanalysis, and output from the Geophysical Fluid Dynamics Laboratory's High-Resolution Atmospheric Model. A multiple regression analysis both for the observations and the model output is performed on seasonal summer and winter composites to separate out the contributions from climate trends, El Niño-Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), Indian summer monsoon, and volcanic aerosols. Strong regional temperature and precipitation responses over the MENA region are found in both winter and summer. The model and the observations both show that a positive NAO amplifies the MENA volcanic winter cooling. In boreal summer, the patterns of changing temperature and precipitation suggest a weakening and southward shift of the Intertropical Convergence Zone, caused by volcanic surface cooling and weakening of the Indian and West African monsoons. The model captures the main features of the climate response; however, it underestimates the total cooling, especially in winter, and exhibits a different spatial pattern of the NAO climate response in MENA compared to the observations. The conducted analysis sheds light on the internal mechanisms of MENA climate variability and helps to selectively diagnose the model deficiencies.

CWRF performance at downscaling China climate characteristics

NASA Astrophysics Data System (ADS)

Liang, Xin-Zhong; Sun, Chao; Zheng, Xiaohui; Dai, Yongjiu; Xu, Min; Choi, Hyun I.; Ling, Tiejun; Qiao, Fengxue; Kong, Xianghui; Bi, Xunqiang; Song, Lianchun; Wang, Fang

2018-05-01

The performance of the regional Climate-Weather Research and Forecasting model (CWRF) for downscaling China climate characteristics is evaluated using a 1980-2015 simulation at 30 km grid spacing driven by the ECMWF Interim reanalysis (ERI). It is shown that CWRF outperforms the popular Regional Climate Modeling system (RegCM4.6) in key features including monsoon rain bands, diurnal temperature ranges, surface winds, interannual precipitation and temperature anomalies, humidity couplings, and 95th percentile daily precipitation. Even compared with ERI, which assimilates surface observations, CWRF better represents the geographic distributions of seasonal mean climate and extreme precipitation. These results indicate that CWRF may significantly enhance China climate modeling capabilities.

Achieving Climate Change Absolute Accuracy in Orbit

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A.; Young, D. F.; Mlynczak, M. G.; Thome, K. J; Leroy, S.; Corliss, J.; Anderson, J. G.; Ao, C. O.; Bantges, R.; Best, F.;

Evaluation of the multi-model CORDEX-Africa hindcast using RCMES

NASA Astrophysics Data System (ADS)

Kim, J.; Waliser, D. E.; Lean, P.; Mattmann, C. A.; Goodale, C. E.; Hart, A.; Zimdars, P.; Hewitson, B.; Jones, C.

2011-12-01

Recent global climate change studies have concluded with a high confidence level that the observed increasing trend in the global-mean surface air temperatures since mid-20th century is triggered by the emission of anthropogenic greenhouse gases (GHGs). The increase in the global-mean temperature due to anthropogenic emissions is nearly monotonic and may alter the climatological norms resulting in a new climate normal. In the presence of anthropogenic climate change, assessing regional impacts of the altered climate state and developing the plans for mitigating any adverse impacts are an important concern. Assessing future climate state and its impact remains a difficult task largely because of the uncertainties in future emissions and model errors. Uncertainties in climate projections propagates into impact assessment models and result in uncertainties in the impact assessments. In order to facilitate the evaluation of model data, a fundamental step for assessing model errors, the JPL Regional Climate Model Evaluation System (RCMES: Lean et al. 2010; Hart et al. 2011) has been developed through a joint effort of the investigators from UCLA and JPL. RCMES is also a regional climate component of a larger worldwide ExArch project. We will present the evaluation of the surface temperatures and precipitation from multiple RCMs participating in the African component of the Coordinated Regional Climate Downscaling Experiment (CORDEX) that has organized a suite of regional climate projection experiments in which multiple RCMs and GCMs are incorporated. As a part of the project, CORDEX organized a 20-year regional climate hindcast study in order to quantify and understand the uncertainties originating from model errors. Investigators from JPL, UCLA, and the CORDEX-Africa team collaborate to analyze the RCM hindcast data using RCMES. The analysis is focused on measuring the closeness between individual regional climate model outputs as well as their ensembles and observed data. The model evaluation is quantified in terms of widely used metrics. Details on the conceptual outline and architecture of RCMES is presented in two companion papers "The Regional climate model Evaluation System (RCMES) based on contemporary satellite and other observations for assessing regional climate model fidelity" and "A Reusable Framework for Regional Climate Model Evaluation" in GC07 and IN30, respectively.

Collaborative Observation and Research (CORE) Watersheds: new strategies for tracking the regional effects of climate change on complex systems

NASA Astrophysics Data System (ADS)

Murdoch, P. S.

2007-12-01

The past 30 years of environmental research have shown that our world is not made up of discrete components acting independently, but rather of a mosaic of complex relations among air, land, water, living resources, and human activities. Recent warming of the climate is having a significant effect on the functioning of those systems. A national imperative is developing to quickly establish local, regional, and national systems for anticipating environmental degradation from a changing climate and developing cost-effective adaptation or mitigation strategies. In these circumstances, the debate over research versus monitoring becomes moot--there is a clear need for the integrated application of both across a range of temporal and spatial scales. A national framework that effectively addresses the multiple scales and complex multi-disciplinary processes of climate change is being assembled largely from existing programs through collaboration among Federal, State, local, and NGO organizations. The result will be an observation and research network capable of interpreting complex environmental changes at a range of spatial and temporal scales, but at less cost than if the network were funded as an independent initiative. A pilot implementation of the collaborative framework in the Delaware River Basin yielded multi-scale assessments of carbon storage and flux, and the effects of forest fragmentation and soil calcium depletion on ecosystem function. A prototype of a national climate-effects observation and research network linking research watersheds, regional surveys, remote sensing, and ecosystem modeling is being initiated in the Yukon River Basin where carbon flux associated with permafrost thaw could accelerate global warming.

Development of a database system for near-future climate change projections under the Japanese National Project SI-CAT

NASA Astrophysics Data System (ADS)

Nakagawa, Y.; Kawahara, S.; Araki, F.; Matsuoka, D.; Ishikawa, Y.; Fujita, M.; Sugimoto, S.; Okada, Y.; Kawazoe, S.; Watanabe, S.; Ishii, M.; Mizuta, R.; Murata, A.; Kawase, H.

2017-12-01

Analyses of large ensemble data are quite useful in order to produce probabilistic effect projection of climate change. Ensemble data of "+2K future climate simulations" are currently produced by Japanese national project "Social Implementation Program on Climate Change Adaptation Technology (SI-CAT)" as a part of a database for Policy Decision making for Future climate change (d4PDF; Mizuta et al. 2016) produced by Program for Risk Information on Climate Change. Those data consist of global warming simulations and regional downscaling simulations. Considering that those data volumes are too large (a few petabyte) to download to a local computer of users, a user-friendly system is required to search and download data which satisfy requests of the users. We develop "a database system for near-future climate change projections" for providing functions to find necessary data for the users under SI-CAT. The database system for near-future climate change projections mainly consists of a relational database, a data download function and user interface. The relational database using PostgreSQL is a key function among them. Temporally and spatially compressed data are registered on the relational database. As a first step, we develop the relational database for precipitation, temperature and track data of typhoon according to requests by SI-CAT members. The data download function using Open-source Project for a Network Data Access Protocol (OPeNDAP) provides a function to download temporally and spatially extracted data based on search results obtained by the relational database. We also develop the web-based user interface for using the relational database and the data download function. A prototype of the database system for near-future climate change projections are currently in operational test on our local server. The database system for near-future climate change projections will be released on Data Integration and Analysis System Program (DIAS) in fiscal year 2017. Techniques of the database system for near-future climate change projections might be quite useful for simulation and observational data in other research fields. We report current status of development and some case studies of the database system for near-future climate change projections.

Indigenous Food Systems and Climate Change: Impacts of Climatic Shifts on the Production and Processing of Native and Traditional Crops in the Bolivian Andes.

PubMed

Keleman Saxena, Alder; Cadima Fuentes, Ximena; Gonzales Herbas, Rhimer; Humphries, Debbie L

2016-01-01

Inhabitants of the high-mountain Andes have already begun to experience changes in the timing, severity, and patterning of annual weather cycles. These changes have important implications for agriculture, for human health, and for the conservation of biodiversity in the region. This paper examines the implications of climate-driven changes for native and traditional crops in the municipality of Colomi, Cochabamba, Bolivia. Data were collected between 2012 and 2014 via mixed methods, qualitative fieldwork, including participatory workshops with female farmers and food preparers, semi-structured interviews with local agronomists, and participant observation. Drawing from this data, the paper describes (a) the observed impacts of changing weather patterns on agricultural production in the municipality of Colomi, Bolivia and (b) the role of local environmental resources and conditions, including clean running water, temperature, and humidity, in the household processing techniques used to conserve and sometimes detoxify native crop and animal species, including potato (Solanum sp.), oca (Oxalis tuberosa), tarwi (Lupinus mutabilis), papalisa (Ullucus tuberosus), and charke (llama or sheep jerky). Analysis suggests that the effects of climatic changes on agriculture go beyond reductions in yield, also influencing how farmers make choices about the timing of planting, soil management, and the use and spatial distribution of particular crop varieties. Furthermore, household processing techniques to preserve and detoxify native foods rely on key environmental and climatic resources, which may be vulnerable to climatic shifts. Although these findings are drawn from a single case study, we suggest that Colomi agriculture characterizes larger patterns in what might be termed, "indigenous food systems." Such systems are underrepresented in aggregate models of the impacts of climate change on world agriculture and may be under different, more direct, and more immediate threat from climate change. As such, the health of the food production and processing environments in such systems merits immediate attention in research and practice.

Indigenous Food Systems and Climate Change: Impacts of Climatic Shifts on the Production and Processing of Native and Traditional Crops in the Bolivian Andes

PubMed Central

Keleman Saxena, Alder; Cadima Fuentes, Ximena; Gonzales Herbas, Rhimer; Humphries, Debbie L.

2016-01-01

Inhabitants of the high-mountain Andes have already begun to experience changes in the timing, severity, and patterning of annual weather cycles. These changes have important implications for agriculture, for human health, and for the conservation of biodiversity in the region. This paper examines the implications of climate-driven changes for native and traditional crops in the municipality of Colomi, Cochabamba, Bolivia. Data were collected between 2012 and 2014 via mixed methods, qualitative fieldwork, including participatory workshops with female farmers and food preparers, semi-structured interviews with local agronomists, and participant observation. Drawing from this data, the paper describes (a) the observed impacts of changing weather patterns on agricultural production in the municipality of Colomi, Bolivia and (b) the role of local environmental resources and conditions, including clean running water, temperature, and humidity, in the household processing techniques used to conserve and sometimes detoxify native crop and animal species, including potato (Solanum sp.), oca (Oxalis tuberosa), tarwi (Lupinus mutabilis), papalisa (Ullucus tuberosus), and charke (llama or sheep jerky). Analysis suggests that the effects of climatic changes on agriculture go beyond reductions in yield, also influencing how farmers make choices about the timing of planting, soil management, and the use and spatial distribution of particular crop varieties. Furthermore, household processing techniques to preserve and detoxify native foods rely on key environmental and climatic resources, which may be vulnerable to climatic shifts. Although these findings are drawn from a single case study, we suggest that Colomi agriculture characterizes larger patterns in what might be termed, “indigenous food systems.” Such systems are underrepresented in aggregate models of the impacts of climate change on world agriculture and may be under different, more direct, and more immediate threat from climate change. As such, the health of the food production and processing environments in such systems merits immediate attention in research and practice. PMID:26973824

Data gathering and simulation of climate change impacts in mountainous areas

NASA Astrophysics Data System (ADS)

Bachelet, D.; Baker, B.; Hicke, J.; Conklin, D.; McKelvey, K.

2007-12-01

High mountains include species most at risk in a warming environment and are a critical link in the water supply chain for both human and natural systems. Scientists are monitoring and simulating these systems as snowpack depth changes, snowmelt timing changes, frozen soils melt and destabilize, and low elevation populations migrate upslope. Natural climate cycles and human activities interact with climate change trends and complicate the interpretation of the signal we observe. For ex. over the past 4 years in Yunnan (China), we documented that herbaceous alpine meadows are contracting as forest tree line advances and alpine shrub biomass increases. This is a result of interactions between human land use alteration and observed shifts in climate. In North America as snowpack decreases, wolverines and lynx denning conditions are jeopardized as human pressure reduces their extent. Coarse scale vegetation shift models using downscaled future climate scenarios fail to capture complex terrain features and microclimatic conditions that can either ensure critical habitat for the in-situ survival of threatened species or make things worse (ex. rockfalls) for climate migrants. Recent simulation efforts focus on high resolution models that address aspect, slope, soil types, and microclimate variations that affect local and migrating plants, their associated pollinators and insect herbivores, modifying habitat availability for birds and mammals

Assessment of the climate change impacts on fecal coliform contamination in a tidal estuarine system.

PubMed

Liu, Wen-Cheng; Chan, Wen-Ting

2015-12-01

Climate change is one of the key factors affecting the future microbiological water quality in rivers and tidal estuaries. A coupled 3D hydrodynamic and fecal coliform transport model was developed and applied to the Danshuei River estuarine system for predicting the influences of climate change on microbiological water quality. The hydrodynamic and fecal coliform model was validated using observational salinity and fecal coliform distributions. According to the analyses of the statistical error, predictions of the salinity and the fecal coliform concentration from the model simulation quantitatively agreed with the observed data. The validated model was then applied to predict the fecal coliform contamination as a result of climate change, including the change of freshwater discharge and the sea level rise. We found that the reduction of freshwater discharge under climate change scenarios resulted in an increase in the fecal coliform concentration. The sea level rise would decrease fecal coliform distributions because both the water level and the water volume increased. A reduction in freshwater discharge has a negative impact on the fecal coliform concentration, whereas a rising sea level has a positive influence on the fecal coliform contamination. An appropriate strategy for the effective microbiological management in tidal estuaries is required to reveal the persistent trends of climate in the future.

Volcanic effects on climate

NASA Technical Reports Server (NTRS)

Robock, Alan

1991-01-01

Volcanic eruptions which inject large amounts of sulfur-rich gas into the stratosphere produce dust veils which last years and cool the earth's surface. At the same time, these dust veils absorb enough solar radiation to warm the stratosphere. Since these temperature changes at the earth's surface and in the stratosphere are both in the opposite direction of hypothesized effects from greenhouse gases, they act to delay and mask the detection of greenhouse effects on the climate system. Tantalizing recent research results have suggested regional effects of volcanic eruptions, including effects on El Nino/Southern Oscillation (ENSO). In addition, a large portion of the global climate change of the past 100 years may be due to the effects of volcanoes, but a definite answer is not yet clear. While effects of several years were demonstrated with both data studies and numerical models, long-term effects, while found in climate model calculations, await confirmation with more realistic models. Extremely large explosive prehistoric eruptions may have produced severe weather and climate effects, sometimes called a 'volcanic winter'. Complete understanding of the above effects of volcanoes is hampered by inadequacies of data sets on volcanic dust veils and on climate change. Space observations can play an increasingly important role in an observing program in the future. The effects of volcanoes are not adequately separated from ENSO events, and climate modeling of the effects of volcanoes is in its infancy. Specific suggestions are made for future work to improve the knowledge of this important component of the climate system.

Benchmark Comparison of Dual- and Quad-Core Processor Linux Clusters with Two Global Climate Modeling Workloads

NASA Technical Reports Server (NTRS)

McGalliard, James

2008-01-01

This viewgraph presentation details the science and systems environments that NASA High End computing program serves. Included is a discussion of the workload that is involved in the processing for the Global Climate Modeling. The Goddard Earth Observing System Model, Version 5 (GEOS-5) is a system of models integrated using the Earth System Modeling Framework (ESMF). The GEOS-5 system was used for the Benchmark tests, and the results of the tests are shown and discussed. Tests were also run for the Cubed Sphere system, results for these test are also shown.

Development of an Experimental African Drought Monitoring and Seasonal Forecasting System: A First Step towards a Global Drought Information System

NASA Astrophysics Data System (ADS)

Wood, E. F.; Chaney, N.; Sheffield, J.; Yuan, X.

2012-12-01

Extreme hydrologic events in the form of droughts are a significant source of social and economic damage. Internationally, organizations such as UNESCO, the Group on Earth Observations (GEO), and the World Climate Research Programme (WCRP) have recognized the need for drought monitoring, especially for the developing world where drought has had devastating impacts on local populations through food insecurity and famine. Having the capacity to monitor droughts in real-time, and to provide drought forecasts with sufficient warning will help developing countries and international programs move from the management of drought crises to the management of drought risk. While observation-based assessments, such as those produced by the US Drought Monitor, are effective for monitoring in countries with extensive observation networks (of precipitation in particular), their utility is lessened in areas (e.g., Africa) where observing networks are sparse. For countries with sparse networks and weak reporting systems, remote sensing observations can provide the real-time data for the monitoring of drought. More importantly, these datasets are now available for at least a decade, which allows for the construction of a climatology against which current conditions can be compared. In this presentation we discuss the development of our multi-lingual experimental African Drought Monitor (ADM) (see http://hydrology.princeton.edu/~nchaney/ADM_ML). At the request of UNESCO, the ADM system has been installed at AGRHYMET, a regional climate and agricultural center in Niamey, Niger and at the ICPAC climate center in Nairobi, Kenya. The ADM system leverages off our U.S. drought monitoring and forecasting system (http://hydrology.princeton.edu/forecasting) that uses the NLDAS data to force the VIC land surface model (LSM) at 1/8th degree spatial resolution for the estimation of our soil moisture drought index (Sheffield et al., 2004). For the seasonal forecast of drought, CFSv2 climate forecasts are bias corrected, downscaled and used as inputs to the VIC LSM as well as forecasts based on ESP and CPC official seasonal outlook. For Africa, data from a combination of remote sensing (TMPA-based precipitation, land cover characteristics) and GFS analysis fields (temperature and wind) are used to monitor drought using our soil moisture drought index as well as 1, 3 and and 6-month SPI. River discharge is also estimated at over 900 locations. Seasonal forecasts have been developed using CFSv2 climate forecasts following the approaches used over CONUS. We will discuss the performance of the system to evaluate the depiction of drought over various scales, from regional to the African continent, and over a number of years to capture multiple drought events. Furthermore, the hindcasts from the seasonal drought forecast system are analyzed to assess the ability of seasonal climate models to detect drought on-set and its recovery. Finally, we will discuss whether our ADM provides a pathway to a Global Drought Information System, a goal of the WCRP Drought Task Force.

Response of the pelagic system of the Pacific Ocean off Baja California Peninsula to the projected effects of climate change: insights from a numerical model.

NASA Astrophysics Data System (ADS)

Arellano, B.; Rivas, D.

2015-12-01

The response of the physical and biological dynamics of the Pacific Ocean off Baja California to the projected effects of climate change are studied using numerical simulations. This region is part of the California Current System, which is a highly productive ecosystem due to the seasonal upwelling, supporting all the trophic levels and important fisheries. The response of the ecosystem to the effects of climate change is uncertain and the information generated by models could be useful to predict future conditions. A three-dimensional hydrodinamical model is coupled to a Nitrate-Phytoplankton-Zooplankton-Detritus (NPZD) trophic model, and it is forced by the GFDL 3.0 model outputs. Monthly climatologies of variables such as temperature, nutrients, wind, and ocean circulation patterns during the historical period 1985-2005 are compared to the available observed data in order to assess the model's ability to reproduce the observed patterns. The system's response to a high-emission scenario proposed by the Intergovernmental Panel of Climate Change (IPCC) is also studied. The experiments are carried out using data correspondig to the RCP 6.0 scenario during the period 2006-2050.

The Use of Remote Sensing Data for Advancing America's Energy Policy

NASA Technical Reports Server (NTRS)

Valinia, Azita; Seery, Bernard D.

2010-01-01

After briefly reviewing America's Energy Policy laid out by the Obama Administration, we outline how a Global Carbon Observing System designed to monitor Carbon from space can provide the necessary data and tools to equip decision makers with the knowledge necessary to formulate effective energy use and practices policy. To stabilize greenhouse gas emissions in the atmosphere in a manner that it does not interfere with the Earth's climate system (which is one of the goals of United Nations Framework for Convention on Climate Change) requires vastly improved prediction of the atmospheric carbon dioxide (CO2) concentrations. This in torn requires a robust understanding of the carbon exchange mechanisms between atmosphere, land, and oceans and a clear understanding of the sources and sinks (i.e. uptake and storage) of CO2. We discuss how the Carbon Observing System from space aids in better understanding of the connection between the carbon cycle and climate change and provides more accurate predictions of atmospheric CO2 concentration. It also enables implementation of greenhouse gas (GHG) mitigation policies such as cap and trade programs, international climate treaties, as well as formulation of effective energy use policies.

The next generation of scenarios for climate change research and assessment.

PubMed

Moss, Richard H; Edmonds, Jae A; Hibbard, Kathy A; Manning, Martin R; Rose, Steven K; van Vuuren, Detlef P; Carter, Timothy R; Emori, Seita; Kainuma, Mikiko; Kram, Tom; Meehl, Gerald A; Mitchell, John F B; Nakicenovic, Nebojsa; Riahi, Keywan; Smith, Steven J; Stouffer, Ronald J; Thomson, Allison M; Weyant, John P; Wilbanks, Thomas J

2010-02-11

Advances in the science and observation of climate change are providing a clearer understanding of the inherent variability of Earth's climate system and its likely response to human and natural influences. The implications of climate change for the environment and society will depend not only on the response of the Earth system to changes in radiative forcings, but also on how humankind responds through changes in technology, economies, lifestyle and policy. Extensive uncertainties exist in future forcings of and responses to climate change, necessitating the use of scenarios of the future to explore the potential consequences of different response options. To date, such scenarios have not adequately examined crucial possibilities, such as climate change mitigation and adaptation, and have relied on research processes that slowed the exchange of information among physical, biological and social scientists. Here we describe a new process for creating plausible scenarios to investigate some of the most challenging and important questions about climate change confronting the global community.

The Impact of ENSO on Trace Gas Composition in the Upper Troposphere to Lower Stratosphere

NASA Technical Reports Server (NTRS)

Oman, Luke; Douglass, Anne; Ziemke, Jerry; Waugh, Darryn Warwick

2016-01-01

The El Nino-Southern Oscillation (ENSO) is the dominant mode of interannual variability in the tropical troposphere and its effects extend well into the stratosphere. Its impact on atmospheric dynamics and chemistry cause important changes to trace gas constituent distributions. A comprehensive suite of satellite observations, reanalyses, and chemistry climate model simulations are illuminating our understanding of processes like ENSO. Analyses of more than a decade of observations from NASAs Aura and Aqua satellites, combined with simulations from the Goddard Earth Observing System Chemistry-Climate Model (GEOSCCM) and other Chemistry Climate Modeling Initiative (CCMI) models, and the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) reanalysis have provided key insights into the response of atmospheric composition to ENSO. While we will primarily focus on ozone and water vapor responses in the upper troposphere to lower stratosphere, the effects of ENSO ripple through many important trace gas species throughout the atmosphere. The very large 2015-2016 El Nino event provides an opportunity to closely examine these impacts with unprecedented observational breadth. An improved quantification of natural climate variations, like those from ENSO, is needed to detect and quantify anthropogenic climate changes.

Nevada Infrastructure for Climate Change Science, Education, and Outreach

NASA Astrophysics Data System (ADS)

Dana, G. L.; Lancaster, N.; Mensing, S. A.; Piechota, T.

2008-12-01

The Great Basin is characterized by complex basin and range topography, arid to semiarid climate, and a history of sensitivity to climate change. Mountain areas comprise about 10% of the landscape, yet are the areas of highest precipitation and generate 85% of groundwater recharge and most surface runoff. These characteristics provide an ideal natural laboratory to study the effects of climate change. The Nevada system of Higher Education, including the University of Nevada, Las Vegas, the University of Nevada, Reno, the Desert Research Institute, and Nevada State College have begun a five year research and infrastructure building program, funded by the National Science Foundation Experimental Program to Stimulate Competitive Research (NSF EPSCoR) with the vision "to create a statewide interdisciplinary program and virtual climate change center that will stimulate transformative research, education, and outreach on the effects of regional climate change on ecosystem resources (especially water) and support use of this knowledge by policy makers and stakeholders." Six major strategies are proposed to develop infrastructure needs and attain our vision: 1) Develop a capability to model climate change at a regional and sub-regional scale(Climate Modeling Component) 2) Analyze effects on ecosystems and disturbance regimes (Ecological Change Component) 3) Quantify and model changes in water balance and resources under climate change (Water Resources Component) 4) Assess effects on human systems and enhance policy making and outreach to communities and stakeholders (Policy, Decision-Making, and Outreach Component) 5) Develop a data portal and software to support interdisciplinary research via integration of data from observational networks and modeling (Cyberinfrastructure Component) and 6) Train teachers and students at all levels and provide public outreach in climate change issues (Education Component). Two new climate observational transects will be established across Great Basin Ranges, one anticipated on a mountain range in southern Nevada and the second to be located in north-central Nevada. Climatic, hydrologic and ecological data from these transects will be downloaded into high capacity data storage units and made available to researchers through creation of the Nevada climate change portal. Our research will aim to answer two interdisciplinary science questions key to understanding the effects of future climate change on Great Basin mountain ecosystems and the potential management strategies for responding to these changes: 1) How will climate change affect water resources and linked ecosystem resources and human systems? And 2) How will climate change affect disturbance regimes (e.g., wildland fires, invasive species, insect outbreaks, droughts) and linked systems? Infrastructure developed through this project will provide new interdisciplinary capability to detect, analyze, and model effects of regional climate change in mountainous regions of the west and provide a major contribution to existing climate change research and monitoring networks.

Objective spatiotemporal proxy-model comparisons of the Asian monsoon for the last millennium

NASA Astrophysics Data System (ADS)

Anchukaitis, K. J.; Cook, E. R.; Ammann, C. M.; Buckley, B. M.; D'Arrigo, R. D.; Jacoby, G.; Wright, W. E.; Davi, N.; Li, J.

2008-12-01

The Asian monsoon system can be studied using a complementary proxy/simulation approach which evaluates climate models using estimates of past precipitation and temperature, and which subsequently applies the best understanding of the physics of the climate system as captured in general circulation models to evaluate the broad-scale dynamics behind regional paleoclimate reconstructions. Here, we use a millennial-length climate field reconstruction of monsoon season summer (JJA) drought, developed from tree- ring proxies, with coupled climate simulations from NCAR CSM1.4 and CCSM3 to evaluate the cause of large- scale persistent droughts over the last one thousand years. Direct comparisons are made between the external forced response within the climate model and the spatiotemporal field reconstruction. In order to identify patterns of drought associated with internal variability in the climate system, we use a model/proxy analog technique which objectively selects epochs in the model that most closely reproduce those observed in the reconstructions. The concomitant ocean-atmosphere dynamics are then interpreted in order to identify and understand the internal climate system forcing of low frequency monsoon variability. We examine specific periods of extensive or intensive regional drought in the 15th, 17th, and 18th centuries, many of which are coincident with major cultural changes in the region.

Research Review, 1983

NASA Technical Reports Server (NTRS)

1984-01-01

The Global Modeling and Simulation Branch (GMSB) of the Laboratory for Atmospheric Sciences (GLAS) is engaged in general circulation modeling studies related to global atmospheric and oceanographic research. The research activities discussed are organized into two disciplines: Global Weather/Observing Systems and Climate/Ocean-Air Interactions. The Global Weather activities are grouped in four areas: (1) Analysis and Forecast Studies, (2) Satellite Observing Systems, (3) Analysis and Model Development, (4) Atmospheric Dynamics and Diagnostic Studies. The GLAS Analysis/Forecast/Retrieval System was applied to both FGGE and post FGGE periods. The resulting analyses have already been used in a large number of theoretical studies of atmospheric dynamics, forecast impact studies and development of new or improved algorithms for the utilization of satellite data. Ocean studies have focused on the analysis of long-term global sea surface temperature data, for use in the study of the response of the atmosphere to sea surface temperature anomalies. Climate research has concentrated on the simulation of global cloudiness, and on the sensitivities of the climate to sea surface temperature and ground wetness anomalies.

Check-Up of Planet Earth at the Turn of the Millennium: Contribution of EOS-Terra to a New Phase in Earth Sciences

NASA Technical Reports Server (NTRS)

Kaufman, Yoram

1999-01-01

Langley's remarkable solar and lunar spectra collected from Mt. Whitney inspired Arrhenius to develop the first quantitative climate model in 1896. In 1999, NASA's Earth Observing AM Satellite (EOS-Terra) will repeat Langley's experiment, but for the entire planet, thus pioneering a wide array of calibrated spectral observations from space of the Earth System. Conceived in response to real environmental problems, EOS-Terra, in conjunction with other international satellite efforts, will fill a major gap in current efforts by providing quantitative global data sets with a resolution of few kilometers on the physical, chemical and biological elements of the earth system. Thus, like Langley's data, EOS-Terra can revolutionize climate research by inspiring a new generation of climate system models and enable us to assess the human impact on the environment. In the talk I shall review the historical developments that brought to the Terra mission, its objectives and example of application to biomass burning.

Global situational awareness and early warning of high-consequence climate change.

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

Backus, George A.; Carr, Martin J.; Boslough, Mark Bruce Elrick

2009-08-01

Global monitoring systems that have high spatial and temporal resolution, with long observational baselines, are needed to provide situational awareness of the Earth's climate system. Continuous monitoring is required for early warning of high-consequence climate change and to help anticipate and minimize the threat. Global climate has changed abruptly in the past and will almost certainly do so again, even in the absence of anthropogenic interference. It is possible that the Earth's climate could change dramatically and suddenly within a few years. An unexpected loss of climate stability would be equivalent to the failure of an engineered system on amore » grand scale, and would affect billions of people by causing agricultural, economic, and environmental collapses that would cascade throughout the world. The probability of such an abrupt change happening in the near future may be small, but it is nonzero. Because the consequences would be catastrophic, we argue that the problem should be treated with science-informed engineering conservatism, which focuses on various ways a system can fail and emphasizes inspection and early detection. Such an approach will require high-fidelity continuous global monitoring, informed by scientific modeling.« less

CAN-DOO: The Climate Action Network through Direct Observations and Outreach

NASA Astrophysics Data System (ADS)

Taubman, B.; Sherman, J. P.; Perry, L. B.; Markham, J.; Kelly, G.

2011-12-01

The urgency of climate change demands a greater understanding of our climate system, not only by the leaders of today, but by the scientists, policy makers, and citizens of tomorrow. Unfortunately, a large segment of the population currently possesses inadequate knowledge of climate science. In direct response to a need for greater scientific literacy with respect to climate science, researchers from Appalachian State University's Appalachian Atmospheric Interdisciplinary Research (AppalAIR) group, with support from NASA, have developed CAN-DOO: the Climate Action Network through Direct Observations and Outreach. CAN-DOO addresses climate science literacy by 1) Developing the infrastructure for sustaining and expanding public outreach through long-term climate measurements capable of complementing existing NASA measurements, 2) Enhancing public awareness of climate science and NASA's role in advancing our understanding of the Earth System, and 3) Introducing Science, Technology, Engineering, and Mathematics principles to homeschooled, public school, and Appalachian State University students through applied climate science activities. Project partners include the Grandfather Mountain Stewardship Foundation, Pisgah Astronomical Research Institute, and local elementary schools. In partnership with Grandfather Mountain, climate science awareness is promoted through citizen science activities, interactive public displays, and staff training. CAN-DOO engages students by involving them in the entire scientific investigative process as applied to climate science. We introduce local elementary and middle school students, homeschooled students throughout North Carolina, and undergraduate students in a new Global Climate Change course and select other courses at Appalachian State University to instrument assembly, measurement techniques, data collection, hypothesis testing, and drawing conclusions. Results are placed in the proper context via comparisons with other student data products, local research-grade measurements, and NASA measurements. Several educational modules have been developed that address specific topics in climate science. The modules are scalable and have been successfully implemented at levels ranging from 2nd grade through first-year graduate as well as with citizen science groups. They also can be applied in user-desired segments to a variety of Earth Science units. In this paper, we will introduce the project activities and present results from the first year of observations and outreach, with a special emphasis on two of the developed modules, the surface energy balance and aerosol optical depth module.

GCOS reference upper air network (GRUAN): Steps towards assuring future climate records

NASA Astrophysics Data System (ADS)

Thorne, P. W.; Vömel, H.; Bodeker, G.; Sommer, M.; Apituley, A.; Berger, F.; Bojinski, S.; Braathen, G.; Calpini, B.; Demoz, B.; Diamond, H. J.; Dykema, J.; Fassò, A.; Fujiwara, M.; Gardiner, T.; Hurst, D.; Leblanc, T.; Madonna, F.; Merlone, A.; Mikalsen, A.; Miller, C. D.; Reale, T.; Rannat, K.; Richter, C.; Seidel, D. J.; Shiotani, M.; Sisterson, D.; Tan, D. G. H.; Vose, R. S.; Voyles, J.; Wang, J.; Whiteman, D. N.; Williams, S.

2013-09-01

The observational climate record is a cornerstone of our scientific understanding of climate changes and their potential causes. Existing observing networks have been designed largely in support of operational weather forecasting and continue to be run in this mode. Coverage and timeliness are often higher priorities than absolute traceability and accuracy. Changes in instrumentation used in the observing system, as well as in operating procedures, are frequent, rarely adequately documented and their impacts poorly quantified. For monitoring changes in upper-air climate, which is achieved through in-situ soundings and more recently satellites and ground-based remote sensing, the net result has been trend uncertainties as large as, or larger than, the expected emergent signals of climate change. This is more than simply academic with the tropospheric temperature trends issue having been the subject of intense debate, two international assessment reports and several US congressional hearings. For more than a decade the international climate science community has been calling for the instigation of a network of reference quality measurements to reduce uncertainty in our climate monitoring capabilities. This paper provides a brief history of GRUAN developments to date and outlines future plans. Such reference networks can only be achieved and maintained with strong continuing input from the global metrological community.

Uncertainties in Decadal Model Evaluation due to the Choice of Different Reanalysis Products

NASA Astrophysics Data System (ADS)

Illing, Sebastian; Kadow, Christopher; Kunst, Oliver; Cubasch, Ulrich

2014-05-01

In recent years decadal predictions have become very popular in the climate science community. A major task is the evaluation and validation of a decadal prediction system. Therefore hindcast experiments are performed and evaluated against observation based or reanalysis data-sets. That is, various metrics and skill scores like the anomaly correlation or the mean squared error skill score (MSSS) are calculated to estimate potential prediction skill of the model system. Our results will mostly feature the Baseline 1 hindcast experiments from the MiKlip decadal prediction system. MiKlip (www.fona-miklip.de) is a project for medium-term climate prediction funded by the Federal Ministry of Education and Research in Germany (BMBF) and has the aim to create a model system that can provide reliable decadal forecasts on climate and weather. There are various reanalysis and observation based products covering at least the last forty years which can be used for model evaluation, for instance the 20th Century Reanalysis from NOAA-CIRES, the Climate Forecast System Reanalysis from NCEP or the Interim Reanalysis from ECMWF. Each of them is based on different climate models and observations. We will show that the choice of the reanalysis product has a huge impact on the value of various skill metrics. In some cases this may actually lead to a change in the interpretation of the results, e.g. when one tries to compare two model versions and the anomaly correlation difference changes its sign for two different reanalysis products. We will also show first results of our studies investigating the influence and effect of this source of uncertainty for decadal model evaluation. Furthermore we point out regions which are most affected by this uncertainty and where one has to cautious interpreting skill scores. In addition we introduce some strategies to overcome or at least reduce this source of uncertainty.

New Observationally-Based Metrics for the Analysis of Coupled Climate Model and Earth System Model Simulations of the Southern Ocean

NASA Astrophysics Data System (ADS)

Russell, J. L.

2014-12-01

The exchange of heat and carbon dioxide between the atmosphere and ocean are major controls on Earth's climate under conditions of anthropogenic forcing. The Southern Ocean south of 30°S, occupying just over ¼ of the surface ocean area, accounts for a disproportionate share of the vertical exchange of properties between the deep and surface waters of the ocean and between the surface ocean and the atmosphere; thus this region can be disproportionately influential on the climate system. Despite the crucial role of the Southern Ocean in the climate system, understanding of the particular mechanisms involved remains inadequate, and the model studies underlying many of these results are highly controversial. As part of the overall goal of working toward reducing uncertainties in climate projections, we present an analysis using new data/model metrics based on a unified framework of theory, quantitative datasets, and numerical modeling. These new metrics quantify the mechanisms, processes, and tendencies relevant to the role of the Southern Ocean in climate.

Modelling Climate/Global Change and Assessing Environmental Risks for Siberia

NASA Astrophysics Data System (ADS)

Lykosov, V. N.; Kabanov, M. V.; Heimann, M.; Gordov, E. P.

2009-04-01

The state-of-the-art climate models are based on a combined atmosphere-ocean general circulation model. A central direction of their development is associated with an increasingly accurate description of all physical processes participating in climate formation. In modeling global climate, it is necessary to reconstruct seasonal and monthly mean values, seasonal variability (monsoon cycle, parameters of storm-tracks, etc.), climatic variability (its dominating modes, such as El Niño or Arctic Oscillation), etc. At the same time, it is quite urgent now to use modern mathematical models in studying regional climate and ecological peculiarities, in particular, that of Northern Eurasia. It is related with the fact that, according to modern ideas, natural environment in mid- and high latitudes of the Northern hemisphere is most sensitive to the observed global climate changes. One should consider such tasks of modeling regional climate as detailed reconstruction of its characteristics, investigation of the peculiarities of hydrological cycle, estimation of the possibility of extreme phenomena to occur, and investigation of the consequences of the regional climate changes for the environment and socio-economic relations as its basic tasks. Changes in nature and climate in Siberia are of special interest in view of the global change in the Earth system. The vast continental territory of Siberia is undoubtedly a ponderable natural territorial region of Eurasian continent, which is characterized by the various combinations of climate-forming factors. Forests, water, and wetland areas are situated on a significant part of Siberia. They play planetary important regulating role due to the processes of emission and accumulation of the main greenhouse gases (carbon dioxide, methane, etc.). Evidence of the enhanced rates of the warming observed in the region and the consequences of such warming for natural environment are undoubtedly important reason for integrated regional investigations in this region of the planet. Reported is an overview of some risk consequences of Climate/Global Change for Siberia environment as follows from results of current scientific activity in climate monitoring and modelling. At present, the challenge facing the weather and climate scientists is to improve the prediction of interactions between weather/climate and Earth system. Taking into account significantly increased computing capacity, a special attention in the report is paid to perspectives of the Earth system modelling.

A Reusable Framework for Regional Climate Model Evaluation

NASA Astrophysics Data System (ADS)

Hart, A. F.; Goodale, C. E.; Mattmann, C. A.; Lean, P.; Kim, J.; Zimdars, P.; Waliser, D. E.; Crichton, D. J.

2011-12-01

Climate observations are currently obtained through a diverse network of sensors and platforms that include space-based observatories, airborne and seaborne platforms, and distributed, networked, ground-based instruments. These global observational measurements are critical inputs to the efforts of the climate modeling community and can provide a corpus of data for use in analysis and validation of climate models. The Regional Climate Model Evaluation System (RCMES) is an effort currently being undertaken to address the challenges of integrating this vast array of observational climate data into a coherent resource suitable for performing model analysis at the regional level. Developed through a collaboration between the NASA Jet Propulsion Laboratory (JPL) and the UCLA Joint Institute for Regional Earth System Science and Engineering (JIFRESSE), the RCMES uses existing open source technologies (MySQL, Apache Hadoop, and Apache OODT), to construct a scalable, parametric, geospatial data store that incorporates decades of observational data from a variety of NASA Earth science missions, as well as other sources into a consistently annotated, highly available scientific resource. By eliminating arbitrary partitions in the data (individual file boundaries, differing file formats, etc), and instead treating each individual observational measurement as a unique, geospatially referenced data point, the RCMES is capable of transforming large, heterogeneous collections of disparate observational data into a unified resource suitable for comparison to climate model output. This facility is further enhanced by the availability of a model evaluation toolkit which consists of a set of Python libraries, a RESTful web service layer, and a browser-based graphical user interface that allows for orchestration of model-to-data comparisons by composing them visually through web forms. This combination of tools and interfaces dramatically simplifies the process of interacting with and utilizing large volumes of observational data for model evaluation research. We feel that the RCMES is particularly appealing in that it represents a principled, reusable architectural approach rather than a one-off technological implementation. In fact, early RCMES prototypes have already utilized a variety of implementation technologies in an effort to address different performance and scalability concerns. This has been greatly facilitated by the fact that, at the architectural level, the RCMES is fundamentally domain agnostic. Strictly separating the data model from the implementation has enabled us to create a reusable architecture that we believe can be modified and configured to suit the demands of researchers in other domains.

The Climate Variability & Predictability (CVP) Program at NOAA - Observing and Understanding Processes Affecting the Propagation of Intraseasonal Oscillations in the Maritime Continent Region

NASA Astrophysics Data System (ADS)

Lucas, S. E.

2017-12-01

The Climate Variability & Predictability (CVP) Program supports research aimed at providing process-level understanding of the climate system through observation, modeling, analysis, and field studies. This vital knowledge is needed to improve climate models and predictions so that scientists can better anticipate the impacts of future climate variability and change. To achieve its mission, the CVP Program supports research carried out at NOAA and other federal laboratories, NOAA Cooperative Institutes, and academic institutions. The Program also coordinates its sponsored projects with major national and international scientific bodies including the World Climate Research Programme (WCRP), the International and U.S. Climate Variability and Predictability (CLIVAR/US CLIVAR) Program, and the U.S. Global Change Research Program (USGCRP). The CVP program sits within NOAA's Climate Program Office (http://cpo.noaa.gov/CVP). In 2017, the CVP Program had a call for proposals focused on observing and understanding processes affecting the propagation of intraseasonal oscillations in the Maritime Continent region. This poster will present the recently funded CVP projects, the expected scientific outcomes, the geographic areas of their work in the Maritime Continent region, and the collaborations with the Office of Naval Research, Indonesian Agency for Meteorology, Climatology and Geophysics (BMKG), Japan Agency for Marine-Earth Science and Technology (JAMSTEC) and other partners.

Testing Earth System Models with Earth System Data: using C isotopes in atmospheric CO2 to probe stomatal response to future climate change

NASA Astrophysics Data System (ADS)

Ballantyne, A. P.; Miller, J. B.; Bowling, D. R.; Tans, P. P.; Baker, I. T.

2013-12-01

The global cycles of water and carbon are inextricably linked through photosynthesis. This link is largely governed by stomatal conductance that regulates water loss to the atmosphere and carbon gain to the biosphere. Although extensive research has focused on the response of stomatal conductance to increased atmospheric CO2, much less research has focused on the response of stomatal conductance to concomitant climate change. Here we make use of intensive and extensive measurements of C isotopes in source CO2 to the atmosphere (del-bio) to make inferences about stomatal response to climatic factors at a single forest site and across a network of global observation sites. Based on intensive observations at the Niwot Ridge Ameriflux site we discover that del-bio is an excellent physical proxy of stomatal response during the growing season and this response is highly sensitive to atmospheric water vapor pressure deficit (VPD). We use these intensive single forest site observations to inform our analysis of the global observation network, focusing in on the growing season across an array of terrestrial sites. We find that stomatal response across most of these terrestrial sites is also highly sensitive to VPD. Lastly, we simulate the response of future climate change on stomatal response and discover that future increases in VPD may limit the biosphere's capacity to assimilate future CO2 emissions. These results have direct implications for the benchmarking of Earth System Models as stomatal conductance in many of these models does not vary as a function of VPD.

Quantitative Comparison of the Variability in Observed and Simulated Shortwave Reflectance

NASA Technical Reports Server (NTRS)

Roberts, Yolanda, L.; Pilewskie, P.; Kindel, B. C.; Feldman, D. R.; Collins, W. D.

2013-01-01

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) is a climate observation system that has been designed to monitor the Earth's climate with unprecedented absolute radiometric accuracy and SI traceability. Climate Observation System Simulation Experiments (OSSEs) have been generated to simulate CLARREO hyperspectral shortwave imager measurements to help define the measurement characteristics needed for CLARREO to achieve its objectives. To evaluate how well the OSSE-simulated reflectance spectra reproduce the Earth s climate variability at the beginning of the 21st century, we compared the variability of the OSSE reflectance spectra to that of the reflectance spectra measured by the Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY). Principal component analysis (PCA) is a multivariate decomposition technique used to represent and study the variability of hyperspectral radiation measurements. Using PCA, between 99.7%and 99.9%of the total variance the OSSE and SCIAMACHY data sets can be explained by subspaces defined by six principal components (PCs). To quantify how much information is shared between the simulated and observed data sets, we spectrally decomposed the intersection of the two data set subspaces. The results from four cases in 2004 showed that the two data sets share eight (January and October) and seven (April and July) dimensions, which correspond to about 99.9% of the total SCIAMACHY variance for each month. The spectral nature of these shared spaces, understood by examining the transformed eigenvectors calculated from the subspace intersections, exhibit similar physical characteristics to the original PCs calculated from each data set, such as water vapor absorption, vegetation reflectance, and cloud reflectance.

Global vegetation productivity response to climatic oscillations during the satellite era.

PubMed

Gonsamo, Alemu; Chen, Jing M; Lombardozzi, Danica

2016-10-01

Climate control on global vegetation productivity patterns has intensified in response to recent global warming. Yet, the contributions of the leading internal climatic variations to global vegetation productivity are poorly understood. Here, we use 30 years of global satellite observations to study climatic variations controls on continental and global vegetation productivity patterns. El Niño-Southern Oscillation (ENSO) phases (La Niña, neutral, and El Niño years) appear to be a weaker control on global-scale vegetation productivity than previously thought, although continental-scale responses are substantial. There is also clear evidence that other non-ENSO climatic variations have a strong control on spatial patterns of vegetation productivity mainly through their influence on temperature. Among the eight leading internal climatic variations, the East Atlantic/West Russia Pattern extensively controls the ensuing year vegetation productivity of the most productive tropical and temperate forest ecosystems of the Earth's vegetated surface through directionally consistent influence on vegetation greenness. The Community Climate System Model (CCSM4) simulations do not capture the observed patterns of vegetation productivity responses to internal climatic variations. Our analyses show the ubiquitous control of climatic variations on vegetation productivity and can further guide CCSM and other Earth system models developments to represent vegetation response patterns to unforced variability. Several winter time internal climatic variation indices show strong potentials on predicting growing season vegetation productivity two to six seasons ahead which enables national governments and farmers forecast crop yield to ensure supplies of affordable food, famine early warning, and plan management options to minimize yield losses ahead of time. © 2016 John Wiley & Sons Ltd.

Incorporating Parallel Computing into the Goddard Earth Observing System Data Assimilation System (GEOS DAS)

NASA Technical Reports Server (NTRS)

Larson, Jay W.

1998-01-01

Atmospheric data assimilation is a method of combining actual observations with model forecasts to produce a more accurate description of the earth system than the observations or forecast alone can provide. The output of data assimilation, sometimes called the analysis, are regular, gridded datasets of observed and unobserved variables. Analysis plays a key role in numerical weather prediction and is becoming increasingly important for climate research. These applications, and the need for timely validation of scientific enhancements to the data assimilation system pose computational demands that are best met by distributed parallel software. The mission of the NASA Data Assimilation Office (DAO) is to provide datasets for climate research and to support NASA satellite and aircraft missions. The system used to create these datasets is the Goddard Earth Observing System Data Assimilation System (GEOS DAS). The core components of the the GEOS DAS are: the GEOS General Circulation Model (GCM), the Physical-space Statistical Analysis System (PSAS), the Observer, the on-line Quality Control (QC) system, the Coupler (which feeds analysis increments back to the GCM), and an I/O package for processing the large amounts of data the system produces (which will be described in another presentation in this session). The discussion will center on the following issues: the computational complexity for the whole GEOS DAS, assessment of the performance of the individual elements of GEOS DAS, and parallelization strategy for some of the components of the system.

Aerosol-Radiation-Cloud Interactions in the South-East Atlantic: Model-Relevant Observations and the Beneficiary Modeling Efforts in the Realm of the EVS-2 Project ORACLES

NASA Technical Reports Server (NTRS)

Redemann, Jens

2018-01-01

Globally, aerosols remain a major contributor to uncertainties in assessments of anthropogenically-induced changes to the Earth climate system, despite concerted efforts using satellite and suborbital observations and increasingly sophisticated models. The quantification of direct and indirect aerosol radiative effects, as well as cloud adjustments thereto, even at regional scales, continues to elude our capabilities. Some of our limitations are due to insufficient sampling and accuracy of the relevant observables, under an appropriate range of conditions to provide useful constraints for modeling efforts at various climate scales. In this talk, I will describe (1) the efforts of our group at NASA Ames to develop new airborne instrumentation to address some of the data insufficiencies mentioned above; (2) the efforts by the EVS-2 ORACLES project to address aerosol-cloud-climate interactions in the SE Atlantic and (3) time permitting, recent results from a synergistic use of A-Train aerosol data to test climate model simulations of present-day direct radiative effects in some of the AEROCOM phase II global climate models.

Linking plant and ecosystem functional biogeography.

PubMed

Reichstein, Markus; Bahn, Michael; Mahecha, Miguel D; Kattge, Jens; Baldocchi, Dennis D

2014-09-23

Classical biogeographical observations suggest that ecosystems are strongly shaped by climatic constraints in terms of their structure and function. On the other hand, vegetation function feeds back on the climate system via biosphere-atmosphere exchange of matter and energy. Ecosystem-level observations of this exchange reveal very large functional biogeographical variation of climate-relevant ecosystem functional properties related to carbon and water cycles. This variation is explained insufficiently by climate control and a classical plant functional type classification approach. For example, correlations between seasonal carbon-use efficiency and climate or environmental variables remain below 0.6, leaving almost 70% of variance unexplained. We suggest that a substantial part of this unexplained variation of ecosystem functional properties is related to variations in plant and microbial traits. Therefore, to progress with global functional biogeography, we should seek to understand the link between organismic traits and flux-derived ecosystem properties at ecosystem observation sites and the spatial variation of vegetation traits given geoecological covariates. This understanding can be fostered by synergistic use of both data-driven and theory-driven ecological as well as biophysical approaches.

Linking plant and ecosystem functional biogeography

PubMed Central

Reichstein, Markus; Bahn, Michael; Mahecha, Miguel D.; Kattge, Jens; Baldocchi, Dennis D.

2014-01-01

Classical biogeographical observations suggest that ecosystems are strongly shaped by climatic constraints in terms of their structure and function. On the other hand, vegetation function feeds back on the climate system via biosphere–atmosphere exchange of matter and energy. Ecosystem-level observations of this exchange reveal very large functional biogeographical variation of climate-relevant ecosystem functional properties related to carbon and water cycles. This variation is explained insufficiently by climate control and a classical plant functional type classification approach. For example, correlations between seasonal carbon-use efficiency and climate or environmental variables remain below 0.6, leaving almost 70% of variance unexplained. We suggest that a substantial part of this unexplained variation of ecosystem functional properties is related to variations in plant and microbial traits. Therefore, to progress with global functional biogeography, we should seek to understand the link between organismic traits and flux-derived ecosystem properties at ecosystem observation sites and the spatial variation of vegetation traits given geoecological covariates. This understanding can be fostered by synergistic use of both data-driven and theory-driven ecological as well as biophysical approaches. PMID:25225392

a Study of the Impact of Doubling Carbon Dioxide and Solar Radiation Variations on the Climate System.

NASA Astrophysics Data System (ADS)

Chu, Shaoping

The exchange of moisture and heat between the atmosphere and the Earth's surface fundamentally affect the dynamics and thermodynamics of the climate system. In order to trace moisture flow through the climate system and examine its impact on climate, a hydrologic cycle and a land energy balance have been developed and incorporated into a coupled climate-thermodynamic sea ice (CCSI) model. The expanded CCSI model has been tested by comparing computed climate parameters with available observations and GCM modeling results. In general, the expanded model does a good job in simulating the large scale features of the atmospheric circulation and precipitation in both space and time. The expanded model has been used to examine the possibility that increased levels of CO_2 in the atmosphere may induce the growth of Northern Hemisphere ice sheets. Results of the study indicate that if summer ice albedo is high enough, and there is some mechanism for initially maintaining ice through the summer season, then it may be possible to have ice sheet growth under the conditions CO_2 induced warming, mainly the result of decreased summer ice melt in response to the higher land ice albedo, and not an increase in precipitation. The expanded model has also been used to examine the impact of Milankovitch solar radiation variations on the climate system, to study the mechanisms that produce glacial-interglacial cycles, especially with respect to the initiation of ice sheets. The results show the Milankovitch solar radiation variations affect the climate system most in the polar regions with the mean annual surface air temperature varying directly in response to changes in the annually averaged incoming solar radiation. However, the seasonal variations in the surface air temperatures are much more complex with large magnitude variations for brief times during the year. The study indicates that ice sheets may start to grow under the conditions of low insolation that occurred at 25, 70, and 115 kyr BP and a land ice minimum albedo of 0.53, with the largest growth rate at 115 kyr BP, approximately when the current 100 kyr cycle began as observed in the geological record.

Eastern Boundary Upwelling Ecosystems: Review and Observing Needs

NASA Astrophysics Data System (ADS)

Chavez, F.; Garçon, V. C.; Dewitte, B.; Montes, I.

2015-12-01

Eastern Boundary Upwelling Systems (EBUS) cover less than 3% of the world ocean surface but play a significant role in the climate system, and contribute disproportionately to ocean biological productivity with up to 40% of the reported global fish catch. Coupled with the vast coastal human populations, these regions play key socio-economic roles. Human pressure on these productive ecosystems and their services is increasing, requiring new and evolving scientific approaches to collect information and use it in management. Here we review and compare the physical, chemical and biological characteristics of the four major EBUS: Benguela, California, Northwest Africa and Peru/Chile. Long-term trends and climate variability are emphasized. Technologies and systems for observing and understanding the changing marine ecosystems of EBUS are discussed.

Scientific Overview of Temporal Experiment for Storms and Tropical Systems (TEMPEST) Program

NASA Astrophysics Data System (ADS)

Chandra, C. V.; Reising, S. C.; Kummerow, C. D.; van den Heever, S. C.; Todd, G.; Padmanabhan, S.; Brown, S. T.; Lim, B.; Haddad, Z. S.; Koch, T.; Berg, G.; L'Ecuyer, T.; Munchak, S. J.; Luo, Z. J.; Boukabara, S. A.; Ruf, C. S.

2014-12-01

Over the past decade and a half, we have gained a better understanding of the role of clouds and precipitation on Earth's water cycle, energy budget and climate, from focused Earth science observational satellite missions. However, these missions provide only a snapshot at one point in time of the cloud's development. Processes that govern cloud system development occur primarily on time scales of the order of 5-30 minutes that are generally not observable from low Earth orbiting satellites. Geostationary satellites, in contrast, have higher temporal resolution but at present are limited to visible and infrared wavelengths that observe only the tops of clouds. This observing gap was noted by the National Research Council's Earth Science Decadal Survey in 2007. Uncertainties in global climate models are significantly affected by processes that govern the formation and dissipation of clouds that largely control the global water and energy budgets. Current uncertainties in cloud parameterization within climate models lead to drastically different climate outcomes. With all evidence suggesting that the precipitation onset may be governed by factors such atmospheric stability, it becomes critical to have at least first-order observations globally in diverse climate regimes. Similar arguments are valid for ice processes where more efficient ice formation and precipitation have a tendency to leave fewer ice clouds behind that have different but equally important impacts on the Earth's energy budget and resulting temperature trends. TEMPEST is a unique program that will provide a small constellation of inexpensive CubeSats with millimeter-wave radiometers to address key science needs related to cloud and precipitation processes. Because these processes are most critical in the development of climate models that will soon run at scales that explicitly resolve clouds, the TEMPEST program will directly focus on examining, validating and improving the parameterizations currently used in cloud scale models. The time evolution of cloud and precipitation microphysics is dependent upon parameterized process rates. The outcome of TEMPEST will provide a first-order understanding of how individual assumptions in current cloud model parameterizations behave in diverse climate regimes.

Climate Impact of Solar Variability

NASA Technical Reports Server (NTRS)

Schatten, Kenneth H. (Editor); Arking, Albert (Editor)

1990-01-01

The conference on The Climate Impact of Solar Variability, was held at Goddard Space Flight Center from April 24 to 27, 1990. In recent years they developed a renewed interest in the potential effects of increasing greenhouse gases on climate. Carbon dioxide, methane, nitrous oxide, and the chlorofluorocarbons have been increasing at rates that could significantly change climate. There is considerable uncertainty over the magnitude of this anthropogenic change. The climate system is very complex, with feedback processes that are not fully understood. Moreover, there are two sources of natural climate variability (volcanic aerosols and solar variability) added to the anthropogenic changes which may confuse our interpretation of the observed temperature record. Thus, if we could understand the climatic impact of the natural variability, it would aid our interpretation and understanding of man-made climate changes.

Ground Water and Climate Change

NASA Technical Reports Server (NTRS)

Taylor, Richard G.; Scanlon, Bridget; Doell, Petra; Rodell, Matt; van Beek, Rens; Wada, Yoshihide; Longuevergne, Laurent; Leblanc, Marc; Famiglietti, James S.; Edmunds, Mike;

Ground water and climate change

USGS Publications Warehouse

Taylor, Richard G.; Scanlon, Bridget R.; Döll, Petra; Rodell, Matt; van Beek, Rens; Wada, Yoshihide; Longuevergne, Laurent; Leblanc, Marc; Famiglietti, James S.; Edmunds, Mike; Konikow, Leonard F.; Green, Timothy R.; Chen, Jianyao; Taniguchi, Makoto; Bierkens, Marc F.P.; MacDonald, Alan; Fan, Ying; Maxwell, Reed M.; Yechieli, Yossi; Gurdak, Jason J.; Allen, Diana M.; Shamsudduha, Mohammad; Hiscock, Kevin; Yeh, Pat J.-F.; Holman, Ian; Treidel, Holger

2012-01-01

As the world's largest distributed store of fresh water, ground water plays a central part in sustaining ecosystems and enabling human adaptation to climate variability and change. The strategic importance of ground water for global water and food security will probably intensify under climate change as more frequent and intense climate extremes (droughts and floods) increase variability in precipitation, soil moisture and surface water. Here we critically review recent research assessing the impacts of climate on ground water through natural and human-induced processes as well as through groundwater-driven feedbacks on the climate system. Furthermore, we examine the possible opportunities and challenges of using and sustaining groundwater resources in climate adaptation strategies, and highlight the lack of groundwater observations, which, at present, limits our understanding of the dynamic relationship between ground water and climate.

The prediction of surface temperature in the new seasonal prediction system based on the MPI-ESM coupled climate model

NASA Astrophysics Data System (ADS)

Baehr, J.; Fröhlich, K.; Botzet, M.; Domeisen, D. I. V.; Kornblueh, L.; Notz, D.; Piontek, R.; Pohlmann, H.; Tietsche, S.; Müller, W. A.

2015-05-01

A seasonal forecast system is presented, based on the global coupled climate model MPI-ESM as used for CMIP5 simulations. We describe the initialisation of the system and analyse its predictive skill for surface temperature. The presented system is initialised in the atmospheric, oceanic, and sea ice component of the model from reanalysis/observations with full field nudging in all three components. For the initialisation of the ensemble, bred vectors with a vertically varying norm are implemented in the ocean component to generate initial perturbations. In a set of ensemble hindcast simulations, starting each May and November between 1982 and 2010, we analyse the predictive skill. Bias-corrected ensemble forecasts for each start date reproduce the observed surface temperature anomalies at 2-4 months lead time, particularly in the tropics. Niño3.4 sea surface temperature anomalies show a small root-mean-square error and predictive skill up to 6 months. Away from the tropics, predictive skill is mostly limited to the ocean, and to regions which are strongly influenced by ENSO teleconnections. In summary, the presented seasonal prediction system based on a coupled climate model shows predictive skill for surface temperature at seasonal time scales comparable to other seasonal prediction systems using different underlying models and initialisation strategies. As the same model underlying our seasonal prediction system—with a different initialisation—is presently also used for decadal predictions, this is an important step towards seamless seasonal-to-decadal climate predictions.

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

NASA Technical Reports Server (NTRS)

Thome, Kurtis; McCorkel, Joel; McAndrew, Brendan

2016-01-01

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.

GLOBE Observer and the Association of Science & Technology Centers: Leveraging Citizen Science and Partnerships for an International Science Experiment to Build Climate Literacy

NASA Astrophysics Data System (ADS)

Riebeek Kohl, H.; Chambers, L. H.; Murphy, T.

2016-12-01

For more that 20 years, the Global Learning and Observations to Benefit the Environment (GLOBE) Program has sought to increase environment literacy in students by involving them in the process of data collection and scientific research. In 2016, the program expanded to accept observations from citizen scientists of all ages through a relatively simple app. Called GLOBE Observer, the new program aims to help participants feel connected to a global community focused on advancing the scientific understanding of Earth system science while building climate literacy among participants and increasing valuable environmental data points to expand both student and scientific research. In October 2016, GLOBE Observer partnered with the Association of Science & Technology Centers (ASTC) in an international science experiment in which museums and patrons around the world collected cloud observations through GLOBE Observer to create a global cloud map in support of NASA satellite science. The experiment was an element of the International Science Center and Science Museum Day, an event planned in partnership with UNESCO and ASTC. Museums and science centers provided the climate context for the observations, while GLOBE Observer offered a uniform experience and a digital platform to build a connected global community. This talk will introduce GLOBE Observer and will present the results of the experiment, including evaluation feedback on gains in climate literacy through the event.

Sources and Impacts of Modeled and Observed Low-Frequency Climate Variability

NASA Astrophysics Data System (ADS)

Parsons, Luke Alexander

Here we analyze climate variability using instrumental, paleoclimate (proxy), and the latest climate model data to understand more about the sources and impacts of low-frequency climate variability. Understanding the drivers of climate variability at interannual to century timescales is important for studies of climate change, including analyses of detection and attribution of climate change impacts. Additionally, correctly modeling the sources and impacts of variability is key to the simulation of abrupt change (Alley et al., 2003) and extended drought (Seager et al., 2005; Pelletier and Turcotte, 1997; Ault et al., 2014). In Appendix A, we employ an Earth system model (GFDL-ESM2M) simulation to study the impacts of a weakening of the Atlantic meridional overturning circulation (AMOC) on the climate of the American Tropics. The AMOC drives some degree of local and global internal low-frequency climate variability (Manabe and Stouffer, 1995; Thornalley et al., 2009) and helps control the position of the tropical rainfall belt (Zhang and Delworth, 2005). We find that a major weakening of the AMOC can cause large-scale temperature, precipitation, and carbon storage changes in Central and South America. Our results suggest that possible future changes in AMOC strength alone will not be sufficient to drive a large-scale dieback of the Amazonian forest, but this key natural ecosystem is sensitive to dry-season length and timing of rainfall (Parsons et al., 2014). In Appendix B, we compare a paleoclimate record of precipitation variability in the Peruvian Amazon to climate model precipitation variability. The paleoclimate (Lake Limon) record indicates that precipitation variability in western Amazonia is 'red' (i.e., increasing variability with timescale). By contrast, most state-of-the-art climate models indicate precipitation variability in this region is nearly 'white' (i.e., equally variability across timescales). This paleo-model disagreement in the overall structure of the variance spectrum has important consequences for the probability of multi-year drought. Our lake record suggests there is a significant background threat of multi-year, and even decade-length, drought in western Amazonia, whereas climate model simulations indicate most droughts likely last no longer than one to three years. These findings suggest climate models may underestimate the future risk of extended drought in this important region. In Appendix C, we expand our analysis of climate variability beyond South America. We use observations, well-constrained tropical paleoclimate, and Earth system model data to examine the overall shape of the climate spectrum across interannual to century frequencies. We find a general agreement among observations and models that temperature variability increases with timescale across most of the globe outside the tropics. However, as compared to paleoclimate records, climate models generate too little low-frequency variability in the tropics (e.g., Laepple and Huybers, 2014). When we compare the shape of the simulated climate spectrum to the spectrum of a simple autoregressive process, we find much of the modeled surface temperature variability in the tropics could be explained by ocean smoothing of weather noise. Importantly, modeled precipitation tends to be similar to white noise across much of the globe. By contrast, paleoclimate records of various types from around the globe indicate that both temperature and precipitation variability should experience much more low-frequency variability than a simple autoregressive or white-noise process. In summary, state-of-the-art climate models generate some degree of dynamically driven low-frequency climate variability, especially at high latitudes. However, the latest climate models, observations, and paleoclimate data provide us with drastically different pictures of the background climate system and its associated risks. This research has important consequences for improving how we simulate climate extremes as we enter a warmer (and often drier) world in the coming centuries; if climate models underestimate low-frequency variability, we will underestimate the risk of future abrupt change and extreme events, such as megadroughts.

Ecological Assimilation of Land and Climate Observations - the EALCO model

NASA Astrophysics Data System (ADS)

Wang, S.; Zhang, Y.; Trishchenko, A.

2004-05-01

Ecosystems are intrinsically dynamic and interact with climate at a highly integrated level. Climate variables are the main driving factors in controlling the ecosystem physical, physiological, and biogeochemical processes including energy balance, water balance, photosynthesis, respiration, and nutrient cycling. On the other hand, ecosystems function as an integrity and feedback on the climate system through their control on surface radiation balance, energy partitioning, and greenhouse gases exchange. To improve our capability in climate change impact assessment, a comprehensive ecosystem model is required to address the many interactions between climate change and ecosystems. In addition, different ecosystems can have very different responses to the climate change and its variation. To provide more scientific support for ecosystem impact assessment at national scale, it is imperative that ecosystem models have the capability of assimilating the large scale geospatial information including satellite observations, GIS datasets, and climate model outputs or reanalysis. The EALCO model (Ecological Assimilation of Land and Climate Observations) is developed for such purposes. EALCO includes the comprehensive interactions among ecosystem processes and climate, and assimilates a variety of remote sensing products and GIS database. It provides both national and local scale model outputs for ecosystem responses to climate change including radiation and energy balances, water conditions and hydrological cycles, carbon sequestration and greenhouse gas exchange, and nutrient (N) cycling. These results form the foundation for the assessment of climate change impact on ecosystems, their services, and adaptation options. In this poster, the main algorithms for the radiation, energy, water, carbon, and nitrogen simulations were diagrammed. Sample input data layers at Canada national scale were illustrated. Model outputs including the Canada wide spatial distributions of net radiation, evapotranspiration, gross primary production, net primary production, and net ecosystem production were discussed.

Improved Analysis of Earth System Models and Observations using Simple Climate Models

NASA Astrophysics Data System (ADS)

Nadiga, B. T.; Urban, N. M.

2016-12-01

Earth system models (ESM) are the most comprehensive tools we have to study climate change and develop climate projections. However, the computational infrastructure required and the cost incurred in running such ESMs precludes direct use of such models in conjunction with a wide variety of tools that can further our understanding of climate. Here we are referring to tools that range from dynamical systems tools that give insight into underlying flow structure and topology to tools that come from various applied mathematical and statistical techniques and are central to quantifying stability, sensitivity, uncertainty and predictability to machine learning tools that are now being rapidly developed or improved. Our approach to facilitate the use of such models is to analyze output of ESM experiments (cf. CMIP) using a range of simpler models that consider integral balances of important quantities such as mass and/or energy in a Bayesian framework.We highlight the use of this approach in the context of the uptake of heat by the world oceans in the ongoing global warming. Indeed, since in excess of 90% of the anomalous radiative forcing due greenhouse gas emissions is sequestered in the world oceans, the nature of ocean heat uptake crucially determines the surface warming that is realized (cf. climate sensitivity). Nevertheless, ESMs themselves are never run long enough to directly assess climate sensitivity. So, we consider a range of models based on integral balances--balances that have to be realized in all first-principles based models of the climate system including the most detailed state-of-the art climate simulations. The models range from simple models of energy balance to those that consider dynamically important ocean processes such as the conveyor-belt circulation (Meridional Overturning Circulation, MOC), North Atlantic Deep Water (NADW) formation, Antarctic Circumpolar Current (ACC) and eddy mixing. Results from Bayesian analysis of such models using both ESM experiments and actual observations are presented. One such result points to the importance of direct sequestration of heat below 700 m, a process that is not allowed for in the simple models that have been traditionally used to deduce climate sensitivity.

Noachian Climate of Mars: Insights from Noachian Stratigraphy and Valley Networks System Formation Times

NASA Astrophysics Data System (ADS)

Head, J. W., III

2017-12-01

Noachian climate models have been proposed in order to account for 1) observed fluvial and lacustrine activity, 2) weathering processes producing phyllosilicates, and 3) an unusual impact record including three major impact basins and unusual degradation processes. We adopt a stratigraphic approach in order place these observations in a temporal context. Formation of the major impact basins Hellas, Isidis and Argyre in earlier Noachian profoundly influenced the uplands geology and appears to have occurred concurrently with major phyllosilicate and related surface occurrences/deposits; the immediate aftermath of these basins appears to have created a temporary hot and wet surface environment with significant effect on surface morphology and alteration processes. Formation of Late Noachian-Early Hesperian valley network systems (VNS) signaled the presence of warm/wet conditions generating several hypotheses for climates permissive of these conditions. We examined estimates for the time required to carve channels/deltas and total duration implied by plausible intermittencies. Synthesis of required timescales show that the total time to carve the VN does not exceed 106 years, < 0.25% of the total Noachian. What climate models can account for the VNS? 1) Warm and wet/semiarid/arid climate: Sustained background MAT >273 K, hydrological system vertically integrated, and rainfall occurs to recharge the aquifer. 2) Cold and Icy climate warmed by greenhouse gases or episodic stochastic events: Climate is sustained cold/icy, but greenhouse gases of unspecified nature/amount/duration elevate MAT by several tens of Kelvins, bringing the annual temperature range into the realm where peak seasonal temperatures (PST) exceed 273 K. In this climate environment, analogous to the Antarctic Dry Valleys, seasonal summer temperatures above 273 K are sufficient to melt snow/ice and form fluvial and lacustrine features, but MAT is well below 273 K (253 K); punctuated warming alternatives include impacts or volcanic eruptions. We conclude that a cold and icy background climate with modest greenhouse warming or punctuated warming and melting events for the VNs origin is consistent with: 1) the estimated durations of continuous VN formation (<105 years) and 2) VN system estimated recurrence rates (106-107 years).

Near real time observational data collection for SPRUCE experiment- PakBus protocol for slow satellite connections

NASA Astrophysics Data System (ADS)

Krassovski, Misha; Hanson, Paul; Riggs, Jeff

2017-04-01

Climate change studies are one of the most important aspects of modern science and related experiments are getting bigger and more complex. One such experiment is the Spruce and Peatland Responses Under Climatic and Environmental Change experiment (SPRUCE, http://mnspruce.ornl.gov) conducted in in northern Minnesota, 40 km north of Grand Rapids, in the USDA Forest Service Marcell Experimental Forest (MEF). The SPRUCE experimental mission is to assess ecosystem-level biological responses of vulnerable, high carbon terrestrial ecosystems to a range of climate warming manipulations and an elevated CO2 atmosphere. This manipulation experiment generates a lot of observational data and requires a reliable onsite data collection system, dependable methods to transfer data to a robust scientific facility, and real-time monitoring capabilities. This publication shares our experience of establishing near real time data collection and monitoring system via a satellite link using PakBus protocol.

Satellite Observations of the Effect of Natural and Anthropogenic Aerosols on Clouds

NASA Technical Reports Server (NTRS)

Kaufman, Yoram J.

2006-01-01

Our knowledge of atmospheric aerosols (smoke, pollution, dust or sea salt particles, small enough to be suspended in the air), their evolution, composition, variability in space and time and interaction with clouds and precipitation is still lacking despite decades of research. Understanding the global aerosol system is critical to quantifying anthropogenic climate change, to determine climate sensitivity from observations and to understand the hydrological cycle. While a single instrument was used to demonstrate 50 years ago that the global CO2 levels are rising, posing threat of global warming, we need an array of satellites and field measurements coupled with chemical transport models to understand the global aerosol system. This complexity of the aerosol problem results from their short lifetime (1 week) and variable chemical composition. A new generation of satellites provides exciting opportunities to measure the global distribution of aerosols, distinguishing natural from anthropogenic aerosol and measuring their interaction with clouds and climate.

Nevada Infrastructure for Climate Change Science, Education, and Outreach

NASA Astrophysics Data System (ADS)

Dana, G. L.; Piechota, T. C.; Lancaster, N.; Mensing, S. A.

2009-12-01

The Nevada system of Higher Education, including the University of Nevada, Las Vegas, the University of Nevada, Reno, the Desert Research Institute, and Nevada State College have begun a five year research and infrastructure building program, funded by the National Science Foundation Experimental Program to Stimulate Competitive Research (NSF EPSCoR) with the vision “to create a statewide interdisciplinary program and virtual climate change center that will stimulate transformative research, education, and outreach on the effects of regional climate change on ecosystem resources (especially water) and support use of this knowledge by policy makers and stakeholders.” Six major strategies are proposed: 1) Develop a capability to model climate change and its effects at a regional and sub-regional scales to evaluate different future scenarios and strategies (Climate Modeling Component) 2) Develop data collection, modeling, and visualization infrastructure to determine and analyze effects on ecosystems and disturbance regimes (Ecological Change Component) 3) Develop data collection, modeling, and visualization infrastructure to better quantify and model changes in water balance and resources under climate change (Water Resources Component) 4) Develop data collection and modeling infrastructure to assess effects on human systems, responses to institutional and societal aspects, and enhance policy making and outreach to communities and stakeholders (Policy, Decision-Making, and Outreach Component) 5) Develop a data portal and software to support interdisciplinary research via integration of data from observational networks and modeling (Cyberinfrastructure Component) and 6) Develop educational infrastructure to train students at all levels and provide public outreach in climate change issues (Education Component). As part of the new infrastructure, two observational transects will be established across Great Basin Ranges, one in southern Nevada in the Spring Mountains, and the second to be located in the Snake Range of eastern Nevada which will reach bristlecone pine stands. Climatic, hydrologic and ecological data from these transects will be downloaded into high capacity data storage units and made available to researchers through creation of the Nevada climate change portal. Our research will aim to answer two interdisciplinary science questions: 1) How will climate change affect water resources and linked ecosystem resources and human systems? And 2) How will climate change affect disturbance regimes (e.g., wildland fires, invasive species, insect outbreaks, droughts) and linked systems?

FUPSOL: Modelling the Future and Past Solar Influence on Earth Climate

NASA Astrophysics Data System (ADS)

Anet, J. G.; Rozanov, E.; Peter, T.

2012-04-01

Global warming is becoming one of the main threats to mankind. There is growing evidence that anthropogenic greenhouse gases have become the dominant factor since about 1970. At the same time natural factors of climate change such as solar and volcanic forcings cannot be neglected on longer time scales. Despite growing scientific efforts over the last decades in both, observations and simulations, the uncertainty of the solar contribution to the past climate change remained unacceptably high (IPCC, 2007), the reasons being on one hand missing observations of solar irradiance prior to the satellite era, and on the other hand a majority of models so far not including all processes relevant for solar-climate interactions. This project aims at elucidating the processes governing the effects of solar activity variations on Earth's climate. We use the state-of-the-art coupled atmosphere-ocean-chemistry-climate model (AOCCM) SOCOL (Schraner et al, 2008) developed in Switzerland by coupling the community Earth System Model (ESM) COSMOS distributed by MPI for Meteorology (Hamburg, Germany) with a comprehensive atmospheric chemistry module. The model solves an extensive set of equations describing the dynamics of the atmosphere and ocean, radiative transfer, transport of species, their chemical transformations, cloud formation and the hydrological cycle. The intention is to show how past solar variations affected climate and how the decrease in solar forcing expected for the next decades will affect climate on global and regional scales. We will simulate the global climate system behavior during Dalton minimum (1790 and 1830) and first half of 21st century with a series of multiyear ensemble experiments and perform these experiments using all known anthropogenic and natural climate forcing taken in different combinations to understand the effects of solar irradiance in different spectral regions and particle precipitation variability. Further on, we will quantify the solar influence on global climate in the future by evaluating the simulations and using information from past analogs such as the Dalton minimum. In the end, the project aims at reducing the uncertainty of the solar contribution to past and future climate change, which so far remained high despite many years of analyses of observational records and theoretical investigations with climate models of different complexity.

An effective drift correction for dynamical downscaling of decadal global climate predictions

NASA Astrophysics Data System (ADS)

Paeth, Heiko; Li, Jingmin; Pollinger, Felix; Müller, Wolfgang A.; Pohlmann, Holger; Feldmann, Hendrik; Panitz, Hans-Jürgen

2018-04-01

Initialized decadal climate predictions with coupled climate models are often marked by substantial climate drifts that emanate from a mismatch between the climatology of the coupled model system and the data set used for initialization. While such drifts may be easily removed from the prediction system when analyzing individual variables, a major problem prevails for multivariate issues and, especially, when the output of the global prediction system shall be used for dynamical downscaling. In this study, we present a statistical approach to remove climate drifts in a multivariate context and demonstrate the effect of this drift correction on regional climate model simulations over the Euro-Atlantic sector. The statistical approach is based on an empirical orthogonal function (EOF) analysis adapted to a very large data matrix. The climate drift emerges as a dramatic cooling trend in North Atlantic sea surface temperatures (SSTs) and is captured by the leading EOF of the multivariate output from the global prediction system, accounting for 7.7% of total variability. The SST cooling pattern also imposes drifts in various atmospheric variables and levels. The removal of the first EOF effectuates the drift correction while retaining other components of intra-annual, inter-annual and decadal variability. In the regional climate model, the multivariate drift correction of the input data removes the cooling trends in most western European land regions and systematically reduces the discrepancy between the output of the regional climate model and observational data. In contrast, removing the drift only in the SST field from the global model has hardly any positive effect on the regional climate model.

Climate-change impacts on sandy-beach biota: crossing a line in the sand.

PubMed

Schoeman, David S; Schlacher, Thomas A; Defeo, Omar

2014-08-01

Sandy ocean beaches are iconic assets that provide irreplaceable ecosystem services to society. Despite their great socioeconomic importance, beaches as ecosystems are severely under-represented in the literature on climate-change ecology. Here, we redress this imbalance by examining whether beach biota have been observed to respond to recent climate change in ways that are consistent with expectations under climate change. We base our assessments on evidence coming from case studies on beach invertebrates in South America and on sea turtles globally. Surprisingly, we find that observational evidence for climate-change responses in beach biota is more convincing for invertebrates than for highly charismatic turtles. This asymmetry is paradoxical given the better theoretical understanding of the mechanisms by which turtles are likely to respond to changes in climate. Regardless of this disparity, knowledge of the unique attributes of beach systems can complement our detection of climate-change impacts on sandy-shore invertebrates to add rigor to studies of climate-change ecology for sandy beaches. To this end, we combine theory from beach ecology and climate-change ecology to put forward a suite of predictive hypotheses regarding climate impacts on beaches and to suggest ways that these can be tested. Addressing these hypotheses could significantly advance both beach and climate-change ecology, thereby progressing understanding of how future climate change will impact coastal ecosystems more generally.

Fewer clouds in the Mediterranean: consistency of observations and climate simulations

PubMed Central

Sanchez-Lorenzo, Arturo; Enriquez-Alonso, Aaron; Calbó, Josep; González, Josep-Abel; Wild, Martin; Folini, Doris; Norris, Joel R.; Vicente-Serrano, Sergio M.

2017-01-01

Clouds play a major role in the climate system, but large uncertainties remain about their decadal variations. Here we report a widespread decrease in cloud cover since the 1970 s over the Mediterranean region, in particular during the 1970 s–1980 s, especially in the central and eastern areas and during springtime. Confidence in these findings is high due to the good agreement between the interannual variations of cloud cover provided by surface observations and several satellite-derived and reanalysis products, although some discrepancies exist in their trends. Climate model simulations of the historical experiment from the Coupled Model Intercomparison Project Phase 5 (CMIP5) also exhibit a decrease in cloud cover over the Mediterranean since the 1970 s, in agreement with surface observations, although the rate of decrease is slightly lower. The observed northward expansion of the Hadley cell is discussed as a possible cause of detected trends. PMID:28148960

Assimilation of temperature and salinity profile data in the Norwegian Climate Prediction Model

NASA Astrophysics Data System (ADS)

Wang, Yiguo; Counillon, Francois; Bertino, Laurent; Bethke, Ingo; Keenlyside, Noel

2016-04-01

Assimilating temperature and salinity profile data is promising to constrain the ocean component of Earth system models for the purpose of seasonal-to-dedacal climate predictions. However, assimilating temperature and salinity profiles that are measured in standard depth coordinate (z-coordinate) into isopycnic coordinate ocean models that are discretised by water densities is challenging. Prior studies (Thacker and Esenkov, 2002; Xie and Zhu, 2010) suggested that converting observations to the model coordinate (i.e. innovations in isopycnic coordinate) performs better than interpolating model state to observation coordinate (i.e. innovations in z-coordinate). This problem is revisited here with the Norwegian Climate Prediction Model, which applies the ensemble Kalman filter (EnKF) into the ocean isopycnic model (MICOM) of the Norwegian Earth System Model. We perform Observing System Simulation Experiments (OSSEs) to compare two schemes (the EnKF-z and EnKF-ρ). In OSSEs, the truth is set to the EN4 objective analyses and observations are perturbations of the truth with white noises. Unlike in previous studies, it is found that EnKF-z outperforms EnKF-ρ for different observed vertical resolution, inhomogeneous sampling (e.g. upper 1000 meter observations only), or lack of salinity measurements. That is mostly because the operator converting observations into isopycnic coordinate is strongly non-linear. We also study the horizontal localisation radius at certain arbitrary grid points. Finally, we perform the EnKF-z with the chosen localisation radius in a realistic framework with NorCPM over a 5-year analysis period. The analysis is validated by different independent datasets.

Atmospheric Research at BNL

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

Peter Daum

2008-10-06

Brookhaven researcher Peter Daum discusses an international field experiment designed to make observations of critical components of the climate system of the southeastern Pacific. Because elements of this system are poorly understood and poorly represent

Atmospheric Research at BNL

ScienceCinema

Peter Daum

2017-12-09

Brookhaven researcher Peter Daum discusses an international field experiment designed to make observations of critical components of the climate system of the southeastern Pacific. Because elements of this system are poorly understood and poorly represent

A Review of Recent Changes in Southern Ocean Sea Ice, Their Drivers and Forcings

NASA Technical Reports Server (NTRS)

Hobbs, William R.; Massom, Rob; Stammerjohn, Sharon; Reid, Phillip; Williams, Guy; Meier, Walter

2016-01-01

Over the past 37years, satellite records show an increase in Antarctic sea ice cover that is most pronounced in the period of sea ice growth. This trend is dominated by increased sea ice coverage in the western Ross Sea, and is mitigated by a strong decrease in the Bellingshausen and Amundsen seas. The trends in sea ice areal coverage are accompanied by related trends in yearly duration. These changes have implications for ecosystems, as well as global and regional climate. In this review, we summarize the researchto date on observing these trends, identifying their drivers, and assessing the role of anthropogenic climate change. Whilst the atmosphere is thought to be the primary driver, the ocean is also essential in explaining the seasonality of the trend patterns. Detecting an anthropogenic signal in Antarctic sea ice is particularly challenging for a number of reasons: the expected response is small compared to the very high natural variability of the system; the observational record is relatively short; and the ability of global coupled climate models to faithfully represent the complex Antarctic climate system is in doubt.

A Mixed Phase Tale: New Ways of using in-situ cloud observations to reduce climate model biases in Southern Ocean

NASA Astrophysics Data System (ADS)

Gettelman, A.; Stith, J. L.

2014-12-01

Southern ocean clouds are a critical part of the earth's energy budget, and significant biases in the climatology of these clouds exist in models used to predict climate change. We compare in situ measurements of cloud microphysical properties of ice and liquid over the S. Ocean with constrained output from the atmospheric component of an Earth System Model. Observations taken during the HIAPER (the NSF/NCAR G-V aircraft) Pole-to-Pole Observations (HIPPO) multi-year field campaign are compared with simulations from the atmospheric component of the Community Earth System Model (CESM). Remarkably, CESM is able to accurately simulate the locations of cloud formation, and even cloud microphysical properties are comparable between the model and observations. Significantly, the simulations do not predict sufficient supercooled liquid. Altering the model cloud and aerosol processes to better reproduce the observations of supercooled liquid acts to reduce long-standing biases in S. Ocean clouds in CESM, which are typical of other models. Furthermore, sensitivity tests show where better observational constraints on aerosols and cloud microphysics can reduce uncertainty and biases in global models. These results are intended to show how we can connect large scale simulations with field observations in the S. Ocean to better understand Southern Ocean cloud processes and reduce biases in global climate simulations.

Regional Climate and Streamflow Projections in North America Under IPCC CMIP5 Scenarios

NASA Astrophysics Data System (ADS)

Chang, H. I.; Castro, C. L.; Troch, P. A. A.; Mukherjee, R.

2014-12-01

The Colorado River system is the predominant source of water supply for the Southwest U.S. and is already fully allocated, making the region's environmental and economic health particularly sensitive to annual and multi-year streamflow variability. Observed streamflow declines in the Colorado Basin in recent years are likely due to synergistic combination of anthropogenic global warming and natural climate variability, which are creating an overall warmer and more extreme climate. IPCC assessment reports have projected warmer and drier conditions in arid to semi-arid regions (e.g. Solomon et al. 2007). The NAM-related precipitation contributes to substantial Colorado streamflows. Recent climate change studies for the Southwest U.S. region project a dire future, with chronic drought, and substantially reduced Colorado River flows. These regional effects reflect the general observation that climate is being more extreme globally, with areas climatologically favored to be wet getting wetter and areas favored to be dry getting drier (Wang et al. 2012). Multi-scale downscaling modeling experiments are designed using recent IPCC AR5 global climate projections, which incorporate regional climate and hydrologic modeling components. The Weather Research and Forecasting model (WRF) has been selected as the main regional modeling tool; the Variable Infiltration Capacity model (VIC) will be used to generate streamflow projections for the Colorado River Basin. The WRF domain is set up to follow the CORDEX-North America guideline with 25km grid spacing, and VIC model is individually calibrated for upper and lower Colorado River basins in 1/8° resolution. The multi-scale climate and hydrology study aims to characterize how the combination of climate change and natural climate variability is changing cool and warm season precipitation. Further, to preserve the downscaled RCM sensitivity and maintain a reasonable climatology mean based on observed record, a new bias correction technique is applied when using the RCM climatology to the streamflow model. Of specific interest is how major droughts associated with La Niña-like conditions may worsen in the future, as these are the times when the Colorado River system is most critically stressed and would define the "worst case" scenario for water resource planning.

The Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC)

NASA Astrophysics Data System (ADS)

Rex, M.; Shupe, M.; Dethloff, K.

2017-12-01

MOSAiC is an international initiative under the umbrella of the International Arctic Science Committee (IASC) designed by an international consortium of leading polar research institutes. Rapid changes in the Arctic lead to an urgent need for reliable information about the state and evolution of the Arctic climate system. This requires more observations and improved modelling over various spatial and temporal scales, and across a wide variety of disciplines. Observations of many critical parameters were never made in the central Arctic for a full annual cycle. MOSAiC will be the first year-around expedition into the central Arctic exploring the coupled climate system. The research vessel Polarstern will drift with the sea ice across the central Arctic during the years 2019 to 2020. The drift starts in the Siberian sector of the Arctic in late summer. A distributed regional network of observational sites will be established on the sea ice in an area of up to 50 km distance from Polarstern, representing a grid cell of climate models. The ship and the surrounding network will drift with the natural sea ice drift across the polar cap towards the Atlantic. The focus of MOSAiC lies on in-situ observations of the climate processes that couple atmosphere, ocean, sea ice, biogeochemistry and ecosystem. These measurements will be supported by weather and sea ice predictions and remote sensing operations to make the expedition successful. The expedition includes aircraft operations and cruises by icebreakers from MOSAiC partners. All these observations will be used for the main scientific goals of MOSAiC, enhancing the understanding of the regional and global consequences of Arctic climate change and sea ice loss and improve weather and climate prediction. More precisely, the results are needed to advance the data assimilation for numerical weather prediction models, sea ice forecasts and climate models and ground truth for satellite remote sensing. Additionally, the understanding of energy budget and fluxes through interfaces, sources, sinks and cycles of chemical species, boundary layer processes, and primary productivity will be investigated during the expedition. MOSAiC will support safer maritime and offshore operations, contribute to an improved scientific future fishery and traffic along the northern sea routes.

Investigating the variation of terrestrial water storage under changing climate and land cover

NASA Astrophysics Data System (ADS)

Fang, Y.; Niu, G. Y.; Zhang, X.; Troch, P. A. A.

2015-12-01

Terrestrial water storage (TWS) consists of groundwater, soil moisture, snow and ice, lakes and rivers and water contained in biomass. The water storage, especially the subsurface storage, is an essential property of the catchment, which controls climate, hydrological and biogeochemical processes at different scales. During the past decades, climate and land cover change has been proved to exert significant influences on hydrological processes which in turn alters the TWS variation. In order to better understand the interaction and feedback mechanism between TWS and earth system, it is necessary to quantify the effects of climate and land cover change on TWS variation. Direct estimation of total TWS has been made possible by the Gravity Recovery And Climate Experiment (GRACE) satellites that measures the earth gravity field. At present, few efforts were made to explicitly investigate the TWS variation under changing climate and land cover. GRACE data has its own limitations. One is its temporal coverage is short, it's only available since 2002, which is not sufficient to reflect the trend due to climate and land cover change. The other reason is that it cannot distinguish different components contributing to TWS. The limitation of TWS observation data can be overcame by numerical models developed to reproduce or to predict different earth system processes. After calibration and validation, with limited observations, these models can be trusted to extend our knowledge to where observations are not available both in time and space. In this study, based on Noah-MP LSM and satellite and ground data, we aim to: (1) Investigate the variation of total TWS as well as its components over Upper Colorado River Basin from 1990 to 2014. (2) Identify the major factors that control the TWS variation. (3) Quantify how the changing climate and land cover affect TWS variation in the same period.

Statistical structure of intrinsic climate variability under global warming

NASA Astrophysics Data System (ADS)

Zhu, Xiuhua; Bye, John; Fraedrich, Klaus

2017-04-01

Climate variability is often studied in terms of fluctuations with respect to the mean state, whereas the dependence between the mean and variability is rarely discussed. We propose a new climate metric to measure the relationship between means and standard deviations of annual surface temperature computed over non-overlapping 100-year segments. This metric is analyzed based on equilibrium simulations of the Max Planck Institute-Earth System Model (MPI-ESM): the last millennium climate (800-1799), the future climate projection following the A1B scenario (2100-2199), and the 3100-year unforced control simulation. A linear relationship is globally observed in the control simulation and thus termed intrinsic climate variability, which is most pronounced in the tropical region with negative regression slopes over the Pacific warm pool and positive slopes in the eastern tropical Pacific. It relates to asymmetric changes in temperature extremes and associates fluctuating climate means with increase or decrease in intensity and occurrence of both El Niño and La Niña events. In the future scenario period, the linear regression slopes largely retain their spatial structure with appreciable changes in intensity and geographical locations. Since intrinsic climate variability describes the internal rhythm of the climate system, it may serve as guidance for interpreting climate variability and climate change signals in the past and the future.

A global food demand model for the assessment of complex human-earth systems

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

EDMONDS, JAMES A.; LINK, ROBERT; WALDHOFF, STEPHANIE T.

Demand for agricultural products is an important problem in climate change economics. Food consumption will shape and shaped by climate change and emissions mitigation policies through interactions with bioenergy and afforestation, two critical issues in meeting international climate goals such as two-degrees. We develop a model of food demand for staple and nonstaple commodities that evolves with changing incomes and prices. The model addresses a long-standing issue in estimating food demands, the evolution of demand relationships across large changes in income and prices. We discuss the model, some of its properties and limitations. We estimate parameter values using pooled cross-sectional-time-seriesmore » observations and the Metropolis Monte Carlo method and cross-validate the model by estimating parameters using a subset of the observations and test its ability to project into the unused observations. Finally, we apply bias correction techniques borrowed from the climate-modeling community and report results.« less

Interoperable Access to Near Real Time Ocean Observations with the Observing System Monitoring Center

NASA Astrophysics Data System (ADS)

O'Brien, K.; Hankin, S.; Mendelssohn, R.; Simons, R.; Smith, B.; Kern, K. J.

2013-12-01

The Observing System Monitoring Center (OSMC), a project funded by the National Oceanic and Atmospheric Administration's Climate Observations Division (COD), exists to join the discrete 'networks' of In Situ ocean observing platforms -- ships, surface floats, profiling floats, tide gauges, etc. - into a single, integrated system. The OSMC is addressing this goal through capabilities in three areas focusing on the needs of specific user groups: 1) it provides real time monitoring of the integrated observing system assets to assist management in optimizing the cost-effectiveness of the system for the assessment of climate variables; 2) it makes the stream of real time data coming from the observing system available to scientific end users into an easy-to-use form; and 3) in the future, it will unify the delayed-mode data from platform-focused data assembly centers into a standards- based distributed system that is readily accessible to interested users from the science and education communities. In this presentation, we will be focusing on the efforts of the OSMC to provide interoperable access to the near real time data stream that is available via the Global Telecommunications System (GTS). This is a very rich data source, and includes data from nearly all of the oceanographic platforms that are actively observing. We will discuss how the data is being served out using a number of widely used 'web services' (including OPeNDAP and SOS) and downloadable file formats (KML, csv, xls, netCDF), so that it can be accessed in web browsers and popular desktop analysis tools. We will also be discussing our use of the Environmental Research Division's Data Access Program (ERDDAP), available from NOAA/NMFS, which has allowed us to achieve our goals of serving the near real time data. From an interoperability perspective, it's important to note that access to the this stream of data is not just for humans, but also for machine-to-machine requests. We'll also delve into how we configured access to the near real time ocean observations in accordance with the Climate and Forecast (CF) metadata conventions describing the various 'feature types' associated with particular in situ observation types, or discrete sampling geometries (DSG). Wrapping up, we'll discuss some of the ways this data source is already being used.

Earth Observing System: Science Objectives and Challenges

NASA Technical Reports Server (NTRS)

King, Michael D.

1999-01-01

The Earth Observing System (EOS) is a space-based observing system comprised of a series of satellite sensors by which scientists can monitor the Earth, a Data and Information System (EOSDIS) enabling researchers worldwide to access the satellite data, and an interdisciplinary science research program to interpret the satellite data. In this presentation we review the key areas of scientific uncertainty in understanding climate and global change, and follow that with a description of the EOS goals, objectives, and scientific research elements that comprise the program (instrument science teams and interdisciplinary investigations). Finally, I will describe how scientists and policy makers intend to use EOS data improve our understanding of key global change uncertainties, such as: (i) clouds and radiation, including fossil fuel and natural emissions of sulfate aerosol and its potential impact on cloud feedback, (ii) man's impact on ozone depletion, with examples of ClO and O3 obtained from the UARS satellite during the Austral Spring, and (iii) volcanic eruptions and their impact on climate, with examples from the eruption of Mt. Pinatubo.

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

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

Steps towards a consistent Climate Forecast System Reanalysis wave hindcast (1979-2016)

NASA Astrophysics Data System (ADS)

Stopa, Justin E.; Ardhuin, Fabrice; Huchet, Marion; Accensi, Mickael

2017-04-01

Surface gravity waves are being increasingly recognized as playing an important role within the climate system. Wave hindcasts and reanalysis products of long time series (>30 years) have been instrumental in understanding and describing the wave climate for the past several decades and have allowed a better understanding of extreme waves and inter-annual variability. Wave hindcasts have the advantage of covering the oceans in higher space-time resolution than possible with conventional observations from satellites and buoys. Wave reanalysis systems like ECWMF's ERA-Interim directly included a wave model that is coupled to the ocean and atmosphere, otherwise reanalysis wind fields are used to drive a wave model to reproduce the wave field in long time series. The ERA Interim dataset is consistent in time, but cannot adequately resolve extreme waves. On the other hand, the NCEP Climate Forecast System (CFSR) wind field better resolves the extreme wind speeds, but suffers from discontinuous features in time which are due to the quantity and quality of the remote sensing data incorporated into the product. Therefore, a consistent hindcast that resolves the extreme waves still alludes us limiting our understanding of the wave climate. In this study, we systematically correct the CFSR wind field to reproduce a homogeneous wave field in time. To verify the homogeneity of our hindcast we compute error metrics on a monthly basis using the observations from a merged altimeter wave database which has been calibrated and quality controlled from 1985-2016. Before 1985 only few wave observations exist and are limited to a select number of wave buoys mostly in the North Hemisphere. Therefore we supplement our wave observations with seismic data which responds to nonlinear wave interactions created by opposing waves with nearly equal wavenumbers. Within the CFSR wave hindcast, we find both spatial and temporal discontinuities in the error metrics. The Southern Hemisphere often has wind speed biases larger than the Northern Hemisphere and we propose a simple correction to reduce these features by applying a taper shaped by a half-Hanning window. The discontinuous features in time are corrected by scaling the entire wind field by percentages ranging typically ranging from 1-3%. Our analysis is performed on monthly time series and we expect the monthly statistics to be more adequate for climate studies.

Observations and High-Resolution Numerical Simulations of a Non-Developing Tropical Disturbance in the Western North Pacific

DTIC Science & Technology

2013-09-01

potential energy CFSR Climate Forecast System Reanalysis COAMPS Coupled Ocean / Atmosphere Mesoscale Prediction System DA data assimilation DART Data...developing (TCS025) tropical disturbance using the adjoint and tangent linear models for the Coupled Ocean – Atmosphere Mesoscale Prediction System (COAMPS...for Medium-range Weather Forecasts ELDORA ELectra DOppler RAdar EOL Earth Observing Laboratory GPS global positioning system GTS Global

Parametric decadal climate forecast recalibration (DeFoReSt 1.0)

NASA Astrophysics Data System (ADS)

Pasternack, Alexander; Bhend, Jonas; Liniger, Mark A.; Rust, Henning W.; Müller, Wolfgang A.; Ulbrich, Uwe

2018-01-01

Near-term climate predictions such as decadal climate forecasts are increasingly being used to guide adaptation measures. For near-term probabilistic predictions to be useful, systematic errors of the forecasting systems have to be corrected. While methods for the calibration of probabilistic forecasts are readily available, these have to be adapted to the specifics of decadal climate forecasts including the long time horizon of decadal climate forecasts, lead-time-dependent systematic errors (drift) and the errors in the representation of long-term changes and variability. These features are compounded by small ensemble sizes to describe forecast uncertainty and a relatively short period for which typically pairs of reforecasts and observations are available to estimate calibration parameters. We introduce the Decadal Climate Forecast Recalibration Strategy (DeFoReSt), a parametric approach to recalibrate decadal ensemble forecasts that takes the above specifics into account. DeFoReSt optimizes forecast quality as measured by the continuous ranked probability score (CRPS). Using a toy model to generate synthetic forecast observation pairs, we demonstrate the positive effect on forecast quality in situations with pronounced and limited predictability. Finally, we apply DeFoReSt to decadal surface temperature forecasts from the MiKlip prototype system and find consistent, and sometimes considerable, improvements in forecast quality compared with a simple calibration of the lead-time-dependent systematic errors.

Possible climates on terrestrial exoplanets.

PubMed

Forget, F; Leconte, J

2014-04-28

What kind of environment may exist on terrestrial planets around other stars? In spite of the lack of direct observations, it may not be premature to speculate on exoplanetary climates, for instance, to optimize future telescopic observations or to assess the probability of habitable worlds. To begin with, climate primarily depends on (i) the atmospheric composition and the volatile inventory; (ii) the incident stellar flux; and (iii) the tidal evolution of the planetary spin, which can notably lock a planet with a permanent night side. The atmospheric composition and mass depends on complex processes, which are difficult to model: origins of volatiles, atmospheric escape, geochemistry, photochemistry, etc. We discuss physical constraints, which can help us to speculate on the possible type of atmosphere, depending on the planet size, its final distance for its star and the star type. Assuming that the atmosphere is known, the possible climates can be explored using global climate models analogous to the ones developed to simulate the Earth as well as the other telluric atmospheres in the solar system. Our experience with Mars, Titan and Venus suggests that realistic climate simulators can be developed by combining components, such as a 'dynamical core', a radiative transfer solver, a parametrization of subgrid-scale turbulence and convection, a thermal ground model and a volatile phase change code. On this basis, we can aspire to build reliable climate predictors for exoplanets. However, whatever the accuracy of the models, predicting the actual climate regime on a specific planet will remain challenging because climate systems are affected by strong positive feedbacks. They can drive planets with very similar forcing and volatile inventory to completely different states. For instance, the coupling among temperature, volatile phase changes and radiative properties results in instabilities, such as runaway glaciations and runaway greenhouse effect.

Multistability and tipping: From mathematics and physics to climate and brain-Minireview and preface to the focus issue.

PubMed

Feudel, Ulrike; Pisarchik, Alexander N; Showalter, Kenneth

2018-03-01

Multistability refers to the coexistence of different stable states in nonlinear dynamical systems. This phenomenon has been observed in laboratory experiments and in nature. In this introduction, we briefly introduce the classes of dynamical systems in which this phenomenon has been found and discuss the extension to new system classes. Furthermore, we introduce the concept of critical transitions and discuss approaches to distinguish them according to their characteristics. Finally, we present some specific applications in physics, neuroscience, biology, ecology, and climate science.

Multistability and tipping: From mathematics and physics to climate and brain—Minireview and preface to the focus issue

NASA Astrophysics Data System (ADS)

Feudel, Ulrike; Pisarchik, Alexander N.; Showalter, Kenneth

2018-03-01

Multistability refers to the coexistence of different stable states in nonlinear dynamical systems. This phenomenon has been observed in laboratory experiments and in nature. In this introduction, we briefly introduce the classes of dynamical systems in which this phenomenon has been found and discuss the extension to new system classes. Furthermore, we introduce the concept of critical transitions and discuss approaches to distinguish them according to their characteristics. Finally, we present some specific applications in physics, neuroscience, biology, ecology, and climate science.

Developing quantitative criteria to evaluate AOGCMs for application to regional climate assessments

NASA Astrophysics Data System (ADS)

Hayhoe, K.; Wake, C.; Bradbury, J.; Degaetano, A.; Hertel, A.

2006-12-01

Climate projections are the foundation for regional assessments of potential climate impacts. However, the soundness of regional assessments depends on the ability of global climate models to reproduce key processes responsible for regional climate trends. Here, we develop a systematic method to compare observed climate with historical atmosphere-ocean general circulation model (AOGCM) simulations, to assess the degree to which AOGCMs are able to reproduce regional circulation patterns. Applying this methodology to the U.S. Northeast (NE), we find that nearly all AOGCMs simulate a reasonable winter NAO pattern and seasonal positions of the Jet Stream and the East Coast Trough. However, not all models capture observed correlations between these circulation patterns and seasonal climate anomalies in the NE. Using only those AOGCMs that meet the criteria in each of these areas, we then develop projections of future climate change in the NE. The primary changes projected to occur over the next century - slightly greater temperature increases in summer than winter, and increases in winter precipitation - are consistent with projected trends in regional climate processes and are relatively independent of model or scale. These suggest confidence in the direction and potential range of the most notable regional climate trends, with the absolute magnitude of change depending on both the sensitivity of the climate system to human forcing as well as on human emissions over coming decades.

New climatic classification of Nepal

NASA Astrophysics Data System (ADS)

Karki, Ramchandra; Talchabhadel, Rocky; Aalto, Juha; Baidya, Saraju Kumar

2016-08-01

Although it is evident that Nepal has an extremely wide range of climates within a short latitudinal distance, there is a lack of comprehensive research in this field. The climatic zoning in a topographically complex country like Nepal has important implications for the selection of scientific station network design and climate model verification, as well as for studies examining the effects of climate change in terms of shifting climatic boundaries and vegetation in highly sensitive environments. This study presents a new high-resolution climate map of Nepal on the basis of long-term (1981-2010) monthly precipitation data for 240 stations and mean air temperature data for 74 stations, using original and modified Köppen-Geiger climate classification systems. Climatic variables used in Köppen-Geiger system were calculated (i) at each station and (ii) interpolated to 1-km spatial resolution using kriging which accounted for latitude, longitude, and elevation. The original Köppen-Geiger scheme could not identify all five types of climate (including tropical) observed in Nepal. Hence, the original scheme was slightly modified by changing the boundary of coldest month mean air temperature value from 18 °C to 14.5 °C in order to delineate the realistic climatic condition of Nepal. With this modification, all five types of climate (including tropical) were identified. The most common dominant type of climate for Nepal is temperate with dry winter and hot summer (Cwa).

The origins of computer weather prediction and climate modeling

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

Lynch, Peter

2008-03-20

Numerical simulation of an ever-increasing range of geophysical phenomena is adding enormously to our understanding of complex processes in the Earth system. The consequences for mankind of ongoing climate change will be far-reaching. Earth System Models are capable of replicating climate regimes of past millennia and are the best means we have of predicting the future of our climate. The basic ideas of numerical forecasting and climate modeling were developed about a century ago, long before the first electronic computer was constructed. There were several major practical obstacles to be overcome before numerical prediction could be put into practice. Amore » fuller understanding of atmospheric dynamics allowed the development of simplified systems of equations; regular radiosonde observations of the free atmosphere and, later, satellite data, provided the initial conditions; stable finite difference schemes were developed; and powerful electronic computers provided a practical means of carrying out the prodigious calculations required to predict the changes in the weather. Progress in weather forecasting and in climate modeling over the past 50 years has been dramatic. In this presentation, we will trace the history of computer forecasting through the ENIAC integrations to the present day. The useful range of deterministic prediction is increasing by about one day each decade, and our understanding of climate change is growing rapidly as Earth System Models of ever-increasing sophistication are developed.« less

The origins of computer weather prediction and climate modeling

NASA Astrophysics Data System (ADS)

Lynch, Peter

2008-03-01

Numerical simulation of an ever-increasing range of geophysical phenomena is adding enormously to our understanding of complex processes in the Earth system. The consequences for mankind of ongoing climate change will be far-reaching. Earth System Models are capable of replicating climate regimes of past millennia and are the best means we have of predicting the future of our climate. The basic ideas of numerical forecasting and climate modeling were developed about a century ago, long before the first electronic computer was constructed. There were several major practical obstacles to be overcome before numerical prediction could be put into practice. A fuller understanding of atmospheric dynamics allowed the development of simplified systems of equations; regular radiosonde observations of the free atmosphere and, later, satellite data, provided the initial conditions; stable finite difference schemes were developed; and powerful electronic computers provided a practical means of carrying out the prodigious calculations required to predict the changes in the weather. Progress in weather forecasting and in climate modeling over the past 50 years has been dramatic. In this presentation, we will trace the history of computer forecasting through the ENIAC integrations to the present day. The useful range of deterministic prediction is increasing by about one day each decade, and our understanding of climate change is growing rapidly as Earth System Models of ever-increasing sophistication are developed.

Evaluating synoptic systems in the CMIP5 climate models over the Australian region

NASA Astrophysics Data System (ADS)

Gibson, Peter B.; Uotila, Petteri; Perkins-Kirkpatrick, Sarah E.; Alexander, Lisa V.; Pitman, Andrew J.

2016-10-01

Climate models are our principal tool for generating the projections used to inform climate change policy. Our confidence in projections depends, in part, on how realistically they simulate present day climate and associated variability over a range of time scales. Traditionally, climate models are less commonly assessed at time scales relevant to daily weather systems. Here we explore the utility of a self-organizing maps (SOMs) procedure for evaluating the frequency, persistence and transitions of daily synoptic systems in the Australian region simulated by state-of-the-art global climate models. In terms of skill in simulating the climatological frequency of synoptic systems, large spread was observed between models. A positive association between all metrics was found, implying that relative skill in simulating the persistence and transitions of systems is related to skill in simulating the climatological frequency. Considering all models and metrics collectively, model performance was found to be related to model horizontal resolution but unrelated to vertical resolution or representation of the stratosphere. In terms of the SOM procedure, the timespan over which evaluation was performed had some influence on model performance skill measures, as did the number of circulation types examined. These findings have implications for selecting models most useful for future projections over the Australian region, particularly for projections related to synoptic scale processes and phenomena. More broadly, this study has demonstrated the utility of the SOMs procedure in providing a process-based evaluation of climate models.

Temporal Variability of Observed and Simulated Hyperspectral Earth Reflectance

NASA Technical Reports Server (NTRS)

Roberts, Yolanda; Pilewskie, Peter; Kindel, Bruce; Feldman, Daniel; Collins, William D.

2012-01-01

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) is a climate observation system designed to study Earth's climate variability with unprecedented absolute radiometric accuracy and SI traceability. Observation System Simulation Experiments (OSSEs) were developed using GCM output and MODTRAN to simulate CLARREO reflectance measurements during the 21st century as a design tool for the CLARREO hyperspectral shortwave imager. With OSSE simulations of hyperspectral reflectance, Feldman et al. [2011a,b] found that shortwave reflectance is able to detect changes in climate variables during the 21st century and improve time-to-detection compared to broadband measurements. The OSSE has been a powerful tool in the design of the CLARREO imager and for understanding the effect of climate change on the spectral variability of reflectance, but it is important to evaluate how well the OSSE simulates the Earth's present-day spectral variability. For this evaluation we have used hyperspectral reflectance measurements from the Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY), a shortwave spectrometer that was operational between March 2002 and April 2012. To study the spectral variability of SCIAMACHY-measured and OSSE-simulated reflectance, we used principal component analysis (PCA), a spectral decomposition technique that identifies dominant modes of variability in a multivariate data set. Using quantitative comparisons of the OSSE and SCIAMACHY PCs, we have quantified how well the OSSE captures the spectral variability of Earth?s climate system at the beginning of the 21st century relative to SCIAMACHY measurements. These results showed that the OSSE and SCIAMACHY data sets share over 99% of their total variance in 2004. Using the PCs and the temporally distributed reflectance spectra projected onto the PCs (PC scores), we can study the temporal variability of the observed and simulated reflectance spectra. Multivariate time series analysis of the PC scores using techniques such as Singular Spectrum Analysis (SSA) and Multichannel SSA will provide information about the temporal variability of the dominant variables. Quantitative comparison techniques can evaluate how well the OSSE reproduces the temporal variability observed by SCIAMACHY spectral reflectance measurements during the first decade of the 21st century. PCA of OSSE-simulated reflectance can also be used to study how the dominant spectral variables change on centennial scales for forced and unforced climate change scenarios. To have confidence in OSSE predictions of the spectral variability of hyperspectral reflectance, it is first necessary for us to evaluate the degree to which the OSSE simulations are able to reproduce the Earth?s present-day spectral variability.

Global climatology of planetary boundary layer top obtained from multi-satellite GPS RO observations

NASA Astrophysics Data System (ADS)

Basha, Ghouse; Kishore, P.; Ratnam, M. Venkat; Ravindra Babu, S.; Velicogna, Isabella; Jiang, Jonathan H.; Ao, Chi O.

2018-05-01

Accurate estimation of the planetary boundary layer (PBL) top is essential for air quality prediction, weather forecast, and assessment of regional and global climate models. In this article, the long-term climatology of seasonal, global distribution of PBL is presented by using global positioning system radio occultation (GPSRO) based payloads such as Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC), Communication/Navigation Outage Forecast System (C/NOFS), TerraSAR-X, and The Gravity Recovery and Climate Experiment (GRACE) from the year 2006-2015. We used Wavelet Covariance Transform (WCT) technique for precise PBL top identification. The derived PBL top from GPSRO data is rigorously evaluated with GPS radiosonde data over Gadanki. Significant seasonal variation is noticed in both radiosonde and GPSRO observations. Further, we compared the PBL obtained GPS RO with global radiosonde network and observed very good correlation. The number of occultations reaching down to 500 m and retrieval rate of PBL top from WCT method is very high in mid-latitudes compared to tropical latitudes. The global distribution of PBL top shows significant seasonal variation with higher during summer followed by spring, fall, and minimum in winter. In the vicinity of Inter Tropical Convergence Zone (ITCZ), the PBL top is high over eastern Pacific compared to other regions. The ERA-Interim reanalysis data underestimate the PBL top compared to GPS RO observations due to different measurement techniques. The seasonal variation of global averaged PBL top over land and ocean shows contrasting features at different latitude bands.

3rd Annual Earth System Grid Federation and 3rd Annual Earth System Grid Federation and Ultrascale Visualization Climate Data Analysis Tools Face-to-Face Meeting Report December 2013

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

Williams, Dean N.

The climate and weather data science community gathered December 3–5, 2013, at Lawrence Livermore National Laboratory, in Livermore, California, for the third annual Earth System Grid Federation (ESGF) and Ultra-scale Visualization Climate Data Analysis Tools (UV-CDAT) Face-to-Face (F2F) Meeting, which was hosted by the Department of Energy, National Aeronautics and Space Administration, National Oceanic and Atmospheric Administration, the European Infrastructure for the European Network of Earth System Modelling, and the Australian Department of Education. Both ESGF and UV-CDAT are global collaborations designed to develop a new generation of open-source software infrastructure that provides distributed access and analysis to observed andmore » simulated data from the climate and weather communities. The tools and infrastructure developed under these international multi-agency collaborations are critical to understanding extreme weather conditions and long-term climate change, while the F2F meetings help to build a stronger climate and weather data science community and stronger federated software infrastructure. The 2013 F2F meeting determined requirements for existing and impending national and international community projects; enhancements needed for data distribution, analysis, and visualization infrastructure; and standards and resources needed for better collaborations.« less

Comparisons with observational and experimental manipulation data imply needed conceptual changes to ESM land models

NASA Astrophysics Data System (ADS)

Riley, W. J.; Zhu, Q.; Tang, J.

2016-12-01

The land models integrated in Earth System Models (ESMs) are critical components necessary to predict soil carbon dynamics and carbon-climate interactions under a changing climate. Yet, these models have been shown to have poor predictive power when compared with observations and ignore many processes known to the observational communities to influence above and belowground carbon dynamics. Here I will report work to tightly couple observations and perturbation experiment results with development of an ESM land model (ALM), focusing on nutrient constraints of the terrestrial C cycle. Using high-frequency flux tower observations and short-term nitrogen and phosphorus perturbation experiments, we show that conceptualizing plant and soil microbe interactions as a multi-substrate, multi-competitor kinetic network allows for accurate prediction of nutrient acquisition. Next, using multiple-year FACE and fertilization response observations at many forest sites, we show that capturing the observed responses requires representation of dynamic allocation to respond to the resulting stresses. Integrating the mechanisms implied by these observations into ALM leads to much lower observational bias and to very different predictions of long-term soil and aboveground C stocks and dynamics, and therefore C-climate feedbacks. I describe how these types of observational constraints are being integrated into the open-source International Land Model Benchmarking (ILAMB) package, and end with the argument that consolidating as many observations of all sorts for easy use by modelers is an important goal to improve C-climate feedback predictions.

Implications of freshwater flux data from the CMIP5 multimodel output across a set of Northern Hemisphere drainage basins

NASA Astrophysics Data System (ADS)

Bring, Arvid; Asokan, Shilpa M.; Jaramillo, Fernando; Jarsjö, Jerker; Levi, Lea; Pietroń, Jan; Prieto, Carmen; Rogberg, Peter; Destouni, Georgia

2015-06-01

The multimodel ensemble of the Coupled Model Intercomparison Project, Phase 5 (CMIP5) synthesizes the latest research in global climate modeling. The freshwater system on land, particularly runoff, has so far been of relatively low priority in global climate models, despite the societal and ecosystem importance of freshwater changes, and the science and policy needs for such model output on drainage basin scales. Here we investigate the implications of CMIP5 multimodel ensemble output data for the freshwater system across a set of drainage basins in the Northern Hemisphere. Results of individual models vary widely, with even ensemble mean results differing greatly from observations and implying unrealistic long-term systematic changes in water storage and level within entire basins. The CMIP5 projections of basin-scale freshwater fluxes differ considerably more from observations and among models for the warm temperate study basins than for the Arctic and cold temperate study basins. In general, the results call for concerted research efforts and model developments for improving the understanding and modeling of the freshwater system and its change drivers. Specifically, more attention to basin-scale water flux analyses should be a priority for climate model development, and an important focus for relevant model-based advice for adaptation to climate change.

Vulnerabilities of macrophytes distribution due to climate change

NASA Astrophysics Data System (ADS)

Hossain, Kaizar; Yadav, Sarita; Quaik, Shlrene; Pant, Gaurav; Maruthi, A. Y.; Ismail, Norli

2017-08-01

The rise in the earth's surface and water temperature is part of the effect of climatic change that has been observed for the last decade. The rates of climate change are unprecedented, and biological responses to these changes have also been prominent in all levels of species, communities and ecosystems. Aquatic-terrestrial ecotones are vulnerable to climate change, and degradation of the emergent aquatic macrophyte zone would have contributed severe ecological consequences for freshwater, wetland and terrestrial ecosystems. Most researches on climate change effects on biodiversity are contemplating on the terrestrial realm, and considerable changes in terrestrial biodiversity and species' distributions have been detected in response to climate change. This is unfortunate, given the importance of aquatic systems for providing ecosystem goods and services. Thus, if researchers were able to identify early-warning indicators of anthropogenic environmental changes on aquatic species, communities and ecosystems, it would certainly help to manage and conserve these systems in a sustainable way. One of such early-warning indicators concerns the expansion of emergent macrophytes in aquatic-terrestrial ecotones. Hence, this review highlights the impact of climatic changes towards aquatic macrophytes and their possible environmental implications.

Inter-model variability in hydrological extremes projections for Amazonian sub-basins

NASA Astrophysics Data System (ADS)

Andres Rodriguez, Daniel; Garofolo, Lucas; Lázaro de Siqueira Júnior, José; Samprogna Mohor, Guilherme; Tomasella, Javier

2014-05-01

Irreducible uncertainties due to knowledge's limitations, chaotic nature of climate system and human decision-making process drive uncertainties in Climate Change projections. Such uncertainties affect the impact studies, mainly when associated to extreme events, and difficult the decision-making process aimed at mitigation and adaptation. However, these uncertainties allow the possibility to develop exploratory analyses on system's vulnerability to different sceneries. The use of different climate model's projections allows to aboard uncertainties issues allowing the use of multiple runs to explore a wide range of potential impacts and its implications for potential vulnerabilities. Statistical approaches for analyses of extreme values are usually based on stationarity assumptions. However, nonstationarity is relevant at the time scales considered for extreme value analyses and could have great implications in dynamic complex systems, mainly under climate change transformations. Because this, it is required to consider the nonstationarity in the statistical distribution parameters. We carried out a study of the dispersion in hydrological extremes projections using climate change projections from several climate models to feed the Distributed Hydrological Model of the National Institute for Spatial Research, MHD-INPE, applied in Amazonian sub-basins. This model is a large-scale hydrological model that uses a TopModel approach to solve runoff generation processes at the grid-cell scale. MHD-INPE model was calibrated for 1970-1990 using observed meteorological data and comparing observed and simulated discharges by using several performance coeficients. Hydrological Model integrations were performed for present historical time (1970-1990) and for future period (2010-2100). Because climate models simulate the variability of the climate system in statistical terms rather than reproduce the historical behavior of climate variables, the performances of the model's runs during the historical period, when feed with climate model data, were tested using descriptors of the Flow Duration Curves. The analyses of projected extreme values were carried out considering the nonstationarity of the GEV distribution parameters and compared with extremes events in present time. Results show inter-model variability in a broad dispersion on projected extreme's values. Such dispersion implies different degrees of socio-economic impacts associated to extreme hydrological events. Despite the no existence of one optimum result, this variability allows the analyses of adaptation strategies and its potential vulnerabilities.

Comparing the model-simulated global warming signal to observations using empirical estimates of unforced noise.

PubMed

Brown, Patrick T; Li, Wenhong; Cordero, Eugene C; Mauget, Steven A

2015-04-21

The comparison of observed global mean surface air temperature (GMT) change to the mean change simulated by climate models has received much public and scientific attention. For a given global warming signal produced by a climate model ensemble, there exists an envelope of GMT values representing the range of possible unforced states of the climate system (the Envelope of Unforced Noise; EUN). Typically, the EUN is derived from climate models themselves, but climate models might not accurately simulate the correct characteristics of unforced GMT variability. Here, we simulate a new, empirical, EUN that is based on instrumental and reconstructed surface temperature records. We compare the forced GMT signal produced by climate models to observations while noting the range of GMT values provided by the empirical EUN. We find that the empirical EUN is wide enough so that the interdecadal variability in the rate of global warming over the 20(th) century does not necessarily require corresponding variability in the rate-of-increase of the forced signal. The empirical EUN also indicates that the reduced GMT warming over the past decade or so is still consistent with a middle emission scenario's forced signal, but is likely inconsistent with the steepest emission scenario's forced signal.

Comparing the model-simulated global warming signal to observations using empirical estimates of unforced noise

PubMed Central

Brown, Patrick T.; Li, Wenhong; Cordero, Eugene C.; Mauget, Steven A.

2015-01-01

The comparison of observed global mean surface air temperature (GMT) change to the mean change simulated by climate models has received much public and scientific attention. For a given global warming signal produced by a climate model ensemble, there exists an envelope of GMT values representing the range of possible unforced states of the climate system (the Envelope of Unforced Noise; EUN). Typically, the EUN is derived from climate models themselves, but climate models might not accurately simulate the correct characteristics of unforced GMT variability. Here, we simulate a new, empirical, EUN that is based on instrumental and reconstructed surface temperature records. We compare the forced GMT signal produced by climate models to observations while noting the range of GMT values provided by the empirical EUN. We find that the empirical EUN is wide enough so that the interdecadal variability in the rate of global warming over the 20th century does not necessarily require corresponding variability in the rate-of-increase of the forced signal. The empirical EUN also indicates that the reduced GMT warming over the past decade or so is still consistent with a middle emission scenario's forced signal, but is likely inconsistent with the steepest emission scenario's forced signal. PMID:25898351

Infrared calibration for climate: a perspective on present and future high-spectral resolution instruments

NASA Astrophysics Data System (ADS)

Revercomb, Henry E.; Anderson, James G.; Best, Fred A.; Tobin, David C.; Knuteson, Robert O.; LaPorte, Daniel D.; Taylor, Joe K.

2006-12-01

The new era of high spectral resolution infrared instruments for atmospheric sounding offers great opportunities for climate change applications. A major issue with most of our existing IR observations from space is spectral sampling uncertainty and the lack of standardization in spectral sampling. The new ultra resolution observing capabilities from the AIRS grating spectrometer on the NASA Aqua platform and from new operational FTS instruments (IASI on Metop, CrIS for NPP/NPOESS, and the GIFTS for a GOES demonstration) will go a long way toward improving this situation. These new observations offer the following improvements: 1. Absolute accuracy, moving from issues of order 1 K to <0.2-0.4 K brightness temperature, 2. More complete spectral coverage, with Nyquist sampling for scale standardization, and 3. Capabilities for unifying IR calibration among different instruments and platforms. However, more needs to be done to meet the immediate needs for climate and to effectively leverage these new operational weather systems, including 1. Place special emphasis on making new instruments as accurate as they can be to realize the potential of technological investments already made, 2. Maintain a careful validation program for establishing the best possible direct radiance check of long-term accuracy--specifically, continuing to use aircraft-or balloon-borne instruments that are periodically checked directly with NIST, and 3. Commit to a simple, new IR mission that will provide an ongoing backbone for the climate observing system. The new mission would make use of Fourier Transform Spectrometer measurements to fill in spectral and diurnal sampling gaps of the operational systems and provide a benchmark with better than 0.1K 3-sigma accuracy based on standards that are verifiable in-flight.

Recent trends in energy flows through the Arctic climate system

NASA Astrophysics Data System (ADS)

Mayer, Michael; Haimberger, Leo

2016-04-01

While Arctic climate change can be diagnosed in many parameters, a comprehensive assessment of long-term changes and low frequency variability in the coupled Arctic energy budget still remains challenging due to the complex physical processes involved and the lack of observations. Here we draw on strongly improved observational capabilities of the past 15 years and employ observed radiative fluxes from CERES along with state-of-the-art atmospheric as well as coupled ocean-ice reanalyses to explore recent changes in energy flows through the Arctic climate system. Various estimates of ice volume and ocean heat content trends imply that the energy imbalance of the Arctic climate system was >1 Wm-2 during the 2000-2015 period, where most of the extra heat warmed the ocean and a comparatively small fraction was used to melt sea ice. The energy imbalance was partly fed by enhanced oceanic heat transports into the Arctic, especially in the mid 2000s. Seasonal trends of net radiation show a very clear signal of the ice-albedo feedback. Stronger radiative energy input during summer means increased seasonal oceanic heat uptake and accelerated sea ice melt. In return, lower minimum sea ice extent and higher SSTs lead to enhanced heat release from the ocean during fall season. These results are consistent with modeling studies finding an enhancement of the annual cycle of surface energy exchanges in a warming Arctic. Moreover, stronger heat fluxes from the ocean to the atmosphere in fall tend to warm the arctic boundary layer and reduce meridional temperature gradients, thereby reducing atmospheric energy transports into the polar cap. Although the observed results are a robust finding, extended high-quality datasets are needed to reliably separate trends from low frequency variability.

Assessing Extratropical Influence on Tropical Climatology and Variability with Regional Coupled Data Assimilation

NASA Astrophysics Data System (ADS)

Lu, F.; Liu, Z.; Liu, Y.; Zhang, S.; Jacob, R. L.

2017-12-01

The Regional Coupled Data Assimilation (RCDA) method is introduced as a tool to study coupled climate dynamics and teleconnections. The RCDA method is built on an ensemble-based coupled data assimilation (CDA) system in a coupled general circulation model (CGCM). The RCDA method limits the data assimilation to the desired model components (e.g. atmosphere) and regions (e.g. the extratropics), and studies the ensemble-mean model response (e.g. tropical response to "observed" extratropical atmospheric variability). When applied to the extratropical influence on tropical climate, the RCDA method has shown some unique advantages, namely the combination of a fully coupled model, real-world observations and an ensemble approach. Tropical variability (e.g. El Niño-Southern Oscillation or ENSO) and climatology (e.g. asymmetric Inter-Tropical Convergence Zone or ITCZ) were initially thought to be determined mostly by local forcing and ocean-atmosphere interaction in the tropics. Since late 20th century, numerous studies have showed that extratropical forcing could affect, or even largely determine some aspects of the tropical climate. Due to the coupled nature of the climate system, however, the challenge of determining and further quantifying the causality of extratropical forcing on the tropical climate remains. Using the RCDA method, we have demonstrated significant control of extratropical atmospheric forcing on ENSO variability in a CGCM, both with model-generated and real-world observation datasets. The RCDA method has also shown robust extratropical impact on the tropical double-ITCZ bias in a CGCM. The RCDA method has provided the first systematic and quantitative assessment of extratropical influence on tropical climatology and variability by incorporating real world observations in a CGCM.

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

NASA Technical Reports Server (NTRS)

Menzel, W. Paul; Huh, Oscar K.; Walker, Nan

2004-01-01

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.

On the generation of climate model ensembles

NASA Astrophysics Data System (ADS)

Haughton, Ned; Abramowitz, Gab; Pitman, Andy; Phipps, Steven J.

2014-10-01

Climate model ensembles are used to estimate uncertainty in future projections, typically by interpreting the ensemble distribution for a particular variable probabilistically. There are, however, different ways to produce climate model ensembles that yield different results, and therefore different probabilities for a future change in a variable. Perhaps equally importantly, there are different approaches to interpreting the ensemble distribution that lead to different conclusions. Here we use a reduced-resolution climate system model to compare three common ways to generate ensembles: initial conditions perturbation, physical parameter perturbation, and structural changes. Despite these three approaches conceptually representing very different categories of uncertainty within a modelling system, when comparing simulations to observations of surface air temperature they can be very difficult to separate. Using the twentieth century CMIP5 ensemble for comparison, we show that initial conditions ensembles, in theory representing internal variability, significantly underestimate observed variance. Structural ensembles, perhaps less surprisingly, exhibit over-dispersion in simulated variance. We argue that future climate model ensembles may need to include parameter or structural perturbation members in addition to perturbed initial conditions members to ensure that they sample uncertainty due to internal variability more completely. We note that where ensembles are over- or under-dispersive, such as for the CMIP5 ensemble, estimates of uncertainty need to be treated with care.

CIRUN: Climate Information Responding to User Needs

NASA Astrophysics Data System (ADS)

Busalacchi, A. J.

2009-12-01

The Earth System will experience real climate change over the next 50 years, exceeding the scope of natural climate variability. A paramount question facing society is how to adapt to this certainty of climate variability and change. In response, OSTP and NOAA are considering how comprehensive climate services would best inform decisions about adaptation. Similarly, NASA is considering the optimal configuration of the next generation of Earth, environmental, and climate observations to be deployed over the coming 10-20 years. Moreover, much of the added-value information for specific climate-related decisions will be provided by private, academic and non-governmental organizations. In this context, over the past several years the University of Maryland has established the CIRUN (Climate Information: Responding to User Needs) initiative to identify the nature of national needs for climate information and services from a decision support perspective. To date, CIRUN has brought together decisionmakers in a number of sectors to help understand their perspectives on climate with the goal of improving the usefulness of climate information, observations and prediction products to specific user communities. CIRUN began with a major workshop in October 2007 that convened 430 participants in agriculture, parks and recreation, terrestrial ecosystems, insurance/investment, energy, national security, state/local/municipal, water, human health, commerce and manufacturing, transportation, and coastal/marine sectors. Plenary speakers such as Norman Augustine, R. James Woolsey, James Mahoney, and former Senator Joseph Tydings, breakout panel sessions, and participants provided input based on the following: - How would you characterize the exposure or vulnerability to climate variability or change impacting your organization? - Does climate variability and/or change currently factor into your organization's objectives or operations? - Are any of your existing plans being affected by climate or projections of climate change? - Is your organization developing a plan for adapting to climate change? - What are your needs for climate observations, predictions, and services? Please cite one or more specific examples when possible. - Do you currently have access to the climate information your organization needs? - What next steps are needed to assure effective use of climate services in your decision making? As a result, a dialogue with various user communities and a subsequent series of more sector specific workshops has been established regarding how significantly enhanced climate observations, data management, modeling, and predictions can provide valuable decision support for business and policy decisions. In particular, CIRUN has helped - To identify how users, stakeholders, and decision makers are influenced by climate on time scales from seasons to decades - To identify the needs and requirements of users, stakeholders, and decision makers for climate information, observations, predictions, and services from global to local scales - To identify what adaptation measures are being considered in the private and public sectors, and how this might result in new classes of information for decision support - To recommend principal elements of the path forward toward more effective use of climate services in decision making.

Data-mining analysis of the global distribution of soil carbon in observational databases and Earth system models

NASA Astrophysics Data System (ADS)

Hashimoto, Shoji; Nanko, Kazuki; Ťupek, Boris; Lehtonen, Aleksi

2017-03-01

Future climate change will dramatically change the carbon balance in the soil, and this change will affect the terrestrial carbon stock and the climate itself. Earth system models (ESMs) are used to understand the current climate and to project future climate conditions, but the soil organic carbon (SOC) stock simulated by ESMs and those of observational databases are not well correlated when the two are compared at fine grid scales. However, the specific key processes and factors, as well as the relationships among these factors that govern the SOC stock, remain unclear; the inclusion of such missing information would improve the agreement between modeled and observational data. In this study, we sought to identify the influential factors that govern global SOC distribution in observational databases, as well as those simulated by ESMs. We used a data-mining (machine-learning) (boosted regression trees - BRT) scheme to identify the factors affecting the SOC stock. We applied BRT scheme to three observational databases and 15 ESM outputs from the fifth phase of the Coupled Model Intercomparison Project (CMIP5) and examined the effects of 13 variables/factors categorized into five groups (climate, soil property, topography, vegetation, and land-use history). Globally, the contributions of mean annual temperature, clay content, carbon-to-nitrogen (CN) ratio, wetland ratio, and land cover were high in observational databases, whereas the contributions of the mean annual temperature, land cover, and net primary productivity (NPP) were predominant in the SOC distribution in ESMs. A comparison of the influential factors at a global scale revealed that the most distinct differences between the SOCs from the observational databases and ESMs were the low clay content and CN ratio contributions, and the high NPP contribution in the ESMs. The results of this study will aid in identifying the causes of the current mismatches between observational SOC databases and ESM outputs and improve the modeling of terrestrial carbon dynamics in ESMs. This study also reveals how a data-mining algorithm can be used to assess model outputs.

Emergent constraints on climate-carbon cycle feedbacks in the CMIP5 Earth system models

NASA Astrophysics Data System (ADS)

Wenzel, Sabrina; Cox, Peter M.; Eyring, Veronika; Friedlingstein, Pierre

2014-05-01

An emergent linear relationship between the long-term sensitivity of tropical land carbon storage to climate warming (γLT) and the short-term sensitivity of atmospheric carbon dioxide (CO2) to interannual temperature variability (γIAV) has previously been identified by Cox et al. (2013) across an ensemble of Earth system models (ESMs) participating in the Coupled Climate-Carbon Cycle Model Intercomparison Project (C4MIP). Here we examine whether such a constraint also holds for a new set of eight ESMs participating in Phase 5 of the Coupled Model Intercomparison Project. A wide spread in tropical land carbon storage is found for the quadrupling of atmospheric CO2, which is of the order of 252 ± 112 GtC when carbon-climate feedbacks are enabled. Correspondingly, the spread in γLT is wide (-49 ± 40 GtC/K) and thus remains one of the key uncertainties in climate projections. A tight correlation is found between the long-term sensitivity of tropical land carbon and the short-term sensitivity of atmospheric CO2 (γLT versus γIAV), which enables the projections to be constrained with observations. The observed short-term sensitivity of CO2 (-4.4 ± 0.9 GtC/yr/K) sharpens the range of γLT to -44 ± 14 GtC/K, which overlaps with the probability density function derived from the C4MIP models (-53 ± 17 GtC/K) by Cox et al. (2013), even though the lines relating γLT and γIAV differ in the two cases. Emergent constraints of this type provide a means to focus ESM evaluation against observations on the metrics most relevant to projections of future climate change.

PERPHECLIM ACCAF Project - Perennial fruit crops and forest phenology evolution facing climatic changes

NASA Astrophysics Data System (ADS)

Garcia de Cortazar-Atauri, Iñaki; Audergon, Jean Marc; Bertuzzi, Patrick; Anger, Christel; Bonhomme, Marc; Chuine, Isabelle; Davi, Hendrik; Delzon, Sylvain; Duchêne, Eric; Legave, Jean Michel; Raynal, Hélène; Pichot, Christian; Van Leeuwen, Cornelis; Perpheclim Team

2015-04-01

Phenology is a bio-indicator of climate evolutions. Measurements of phenological stages on perennial species provide actually significant illustrations and assessments of the impact of climate change. Phenology is also one of the main key characteristics of the capacity of adaptation of perennial species, generating questions about their consequences on plant growth and development or on fruit quality. Predicting phenology evolution and adaptative capacities of perennial species need to override three main methodological limitations: 1) existing observations and associated databases are scattered and sometimes incomplete, rendering difficult implementation of multi-site study of genotype-environment interaction analyses; 2) there are not common protocols to observe phenological stages; 3) access to generic phenological models platforms is still very limited. In this context, the PERPHECLIM project, which is funded by the Adapting Agriculture and Forestry to Climate Change Meta-Program (ACCAF) from INRA (French National Institute of Agronomic Research), has the objective to develop the necessary infrastructure at INRA level (observatories, information system, modeling tools) to enable partners to study the phenology of various perennial species (grapevine, fruit trees and forest trees). Currently the PERPHECLIM project involves 27 research units in France. The main activities currently developed are: define protocols and observation forms to observe phenology for various species of interest for the project; organizing observation training; develop generic modeling solutions to simulate phenology (Phenological Modelling Platform and modelling platform solutions); support in building research projects at national and international level; develop environment/genotype observation networks for fruit trees species; develop an information system managing data and documentation concerning phenology. Finally, PERPHECLIM project aims to build strong collaborations with public (Observatoire des Saisons) and private sector partners (technical institutes) in order to allow a more direct transfer of knowledge.

Evaluation of mean climate in a chemistry-climate model simulation

NASA Astrophysics Data System (ADS)

Hong, S.; Park, H.; Wie, J.; Park, R.; Lee, S.; Moon, B. K.

2017-12-01

Incorporation of the interactive chemistry is essential for understanding chemistry-climate interactions and feedback processes in climate models. Here we assess a newly developed chemistry-climate model (GRIMs-Chem), which is based on the Global/Regional Integrated Model system (GRIMs) including the aerosol direct effect as well as stratospheric linearized ozone chemistry (LINOZ). We conducted GRIMs-Chem with observed sea surface temperature during the period of 1979-2010, and compared the simulation results with observations and also with CMIP models. To measure the relative performance of our model, we define the quantitative performance metric using the Taylor diagram. This metric allow us to assess overall features in simulating multiple variables. Overall, our model better reproduce the zonal mean spatial pattern of temperature, horizontal wind, vertical motion, and relative humidity relative to other models. However, the model did not produce good simulations at upper troposphere (200 hPa). It is currently unclear which model processes are responsible for this. AcknowledgementsThis research was supported by the Korea Ministry of Environment (MOE) as "Climate Change Correspondence Program."

Climate Model Diagnostic Analyzer

NASA Technical Reports Server (NTRS)

Lee, Seungwon; Pan, Lei; Zhai, Chengxing; Tang, Benyang; Kubar, Terry; Zhang, Zia; Wang, Wei

2015-01-01

The comprehensive and innovative evaluation of climate models with newly available global observations is critically needed for the improvement of climate model current-state representation and future-state predictability. A climate model diagnostic evaluation process requires physics-based multi-variable analyses that typically involve large-volume and heterogeneous datasets, making them both computation- and data-intensive. With an exploratory nature of climate data analyses and an explosive growth of datasets and service tools, scientists are struggling to keep track of their datasets, tools, and execution/study history, let alone sharing them with others. In response, we have developed a cloud-enabled, provenance-supported, web-service system called Climate Model Diagnostic Analyzer (CMDA). CMDA enables the physics-based, multivariable model performance evaluations and diagnoses through the comprehensive and synergistic use of multiple observational data, reanalysis data, and model outputs. At the same time, CMDA provides a crowd-sourcing space where scientists can organize their work efficiently and share their work with others. CMDA is empowered by many current state-of-the-art software packages in web service, provenance, and semantic search.

Partners in Earth System Science: a Field, Laboratory and Classroom Based Professional Development Program for K-12 Teachers Designed to Build Scientific and Pedagogical Understandings of Teaching Climate Change.

NASA Astrophysics Data System (ADS)

Slattery, W.; Lunsford, S.; Diedrick, A.; Crane, C.

2015-12-01

The purpose of the Partners in Earth System Science summer and academic year professional development program for Ohio K-12 teachers is to build their understandings of the scientific observations, methods and resources that scientists use when studying past and present climate change. Participants then use these tools to develop inquiry-based activities to teach their K-12 students how the scientific method and data are used to understand the effects of global climate change. The summer portion of the program takes teachers from throughout Ohio to the Duke University Marine Laboratory in Beaufort, North Carolina. There they engage in a physical and biological exploration of the modern and ancient ocean. For example, they collect samples of sediment and test water samples collected from modern coastal environments and connect their findings with evidence of the fauna living in those environments. Then, using observations from the geological record of the Eocene through Pleistocene sediments exposed in eastern North Carolina and inferences from observations made from the modern ocean they seek to answer scientifically testable questions regarding the physical and biological characteristics of the ocean during Cenozoic climate change events. During the academic year participants connect with each other and project faculty online to support the development of inquiry based science activities for their K-12 students. These activities focus on how evidence and observations such as outcrop extent, sediment type and biological assemblages can be used to infer past climates. The activities are taught in participant's classrooms and discussed with other participants in an online discussion space. Assessment of both teachers and K-12 students document significant positive changes in science knowledge, their confidence in being able to do science and a clearer understanding of how oceans are impacted by global climate change.

Modelling the Climate - Greenland Ice Sheet Interaction in the Coupled Ice-sheet/Climate Model EC-EARTH - PISM

NASA Astrophysics Data System (ADS)

Yang, S.; Madsen, M. S.; Rodehacke, C. B.; Svendsen, S. H.; Adalgeirsdottir, G.

2014-12-01

Recent observations show that the Greenland ice sheet (GrIS) has been losing mass with an increasing speed during the past decades. Predicting the GrIS changes and their climate consequences relies on the understanding of the interaction of the GrIS with the climate system on both global and local scales, and requires climate model systems with an explicit and physically consistent ice sheet module. A fully coupled global climate model with a dynamical ice sheet model for the GrIS has recently been developed. The model system, EC-EARTH - PISM, consists of the EC-EARTH, an atmosphere, ocean and sea ice model system, and the Parallel Ice Sheet Model (PISM). The coupling of PISM includes a modified surface physical parameterization in EC-EARTH adapted to the land ice surface over glaciated regions in Greenland. The PISM ice sheet model is forced with the surface mass balance (SMB) directly computed inside the EC-EARTH atmospheric module and accounting for the precipitation, the surface evaporation, and the melting of snow and ice over land ice. PISM returns the simulated basal melt, ice discharge and ice cover (extent and thickness) as boundary conditions to EC-EARTH. This coupled system is mass and energy conserving without being constrained by any anomaly correction or flux adjustment, and hence is suitable for investigation of ice sheet - climate feedbacks. Three multi-century experiments for warm climate scenarios under (1) the RCP85 climate forcing, (2) an abrupt 4xCO2 and (3) an idealized 1% per year CO2 increase are performed using the coupled model system. The experiments are compared with their counterparts of the standard CMIP5 simulations (without the interactive ice sheet) to evaluate the performance of the coupled system and to quantify the GrIS feedbacks. In particular, the evolution of the Greenland ice sheet under the warm climate and its impacts on the climate system are investigated. Freshwater fluxes from the Greenland ice sheet melt to the Arctic and North Atlantic basin and their influence on the ocean stratification and ocean circulation are analysed. The changes in the surface climate and the atmospheric circulation associated with the impact of the Greenland ice sheet changes are quantified. The interaction between the Greenland ice sheet and Arctic sea ice is also examined.

The Earth Observing System Terra Mission

NASA Technical Reports Server (NTRS)

Kaufman, Yoram J.; Einaudi, Franco (Technical Monitor)

2000-01-01

Langley's remarkable solar and lunar spectra collected from Mt. Whitney inspired Arrhenius to develop the first quantitative climate model in 1896. After the launch in Dec. 16 1999, NASA's Earth Observing AM Satellite (EOS-Terra) will repeat Langley's experiment, but for the entire planet, thus pioneering a wide array of calibrated spectral observations from space of the Earth System. Conceived in response to real environmental problems, EOS-Terra, in conjunction with other international satellite efforts, will fill a major gap in current efforts by providing quantitative global data sets with a resolution better than 1 km on the physical, chemical and biological elements of the earth system. Thus, like Langley's data, EOS-Terra can revolutionize climate research by inspiring a new generation of climate system models and enable us to assess the human impact on the environment. In the talk I shall review the historical perspective of the Terra mission and the key new elements of the mission. We expect to have first images that demonstrate the most innovative capability from EOS Terra 5 instruments: MODIS - 1.37 micron cirrus cloud channel; 250m daily coverage for clouds and vegetation change; 7 solar channels for land and aerosol studies; new fire channels; Chlorophyll fluorescence; MISR - first 9 multi angle views of clouds and vegetation; MOPITT - first global CO maps and C114 maps; ASTER - Thermal channels for geological studies with 15-90 m resolution.

The Earth Observing System Terra Mission

NASA Technical Reports Server (NTRS)

Kaufman, Yoram J.

2000-01-01

Langley's remarkable solar and lunar spectra collected from Mt. Whitney inspired Arrhenius to develop the first quantitative climate model in 1896. After the launch in Dec. 16 1999, NASA's Earth Observing AM Satellite (EOS-Terra) will repeat Langley's experiment, but for the entire planet, thus pioneering a wide array of calibrated spectral observations from space of the Earth System. Conceived in response to real environmental problems, EOS-Terra, in conjunction with other international satellite efforts, will fill a major gap in current efforts by providing quantitative global data sets with a resolution smaller than 1 km on the physical, chemical and biological elements of the earth system. Thus, like Langley's data, EOS-Terra can revolutionize climate research by inspiring a new generation of climate system models and enable us to assess the human impact on the environment. In the talk I shall review the historical perspective of the Terra mission and the key new elements of the mission. We expect to have some first images that demonstrate the most innovative capability from EOS Terra: MODIS - 1.37 microns cirrus channel; 250 m daily cover for clouds and vegetation change; 7 solar channels for land and aerosol; new fire channels; Chlorophyll fluorescence; MISR - 9 multi angle views of clouds and vegetation; MOPITT - Global CO maps and CH4 maps; ASTER - Thermal channels for geological studies with 15-90 m resolution.

Oscar: a portable prototype system for the study of climate variability

NASA Astrophysics Data System (ADS)

Madonna, Fabio; Rosoldi, Marco; Amato, Francesco

2015-04-01

The study of the techniques for the exploitation of solar energy implies the knowledge of nature, ecosystem, biological factors and local climate. Clouds, fog, water vapor, and the presence of large concentrations of dust can significantly affect the way to exploit the solar energy. Therefore, a quantitative characterization of the impact of climate variability at the regional scale is needed to increase the efficiency and sustainability of the energy system. OSCAR (Observation System for Climate Application at Regional scale) project, funded in the frame of the PO FESR 2007-2013, aims at the design of a portable prototype system for the study of correlations among the trends of several Essential Climate Variables (ECVs) and the change in the amount of solar irradiance at the ground level. The final goal of this project is to provide a user-friendly low cost solution for the quantification of the impact of regional climate variability on the efficiency of solar cell and concentrators to improve the exploitation of natural sources. The prototype has been designed on the basis of historical measurements performed at CNR-IMAA Atmospheric Observatory (CIAO). Measurements from satellite and data from models have been also considered as ancillary to the study, above all, to fill in the gaps of existing datasets. In this work, the results outcome from the project activities will be presented. The results include: the design and implementation of the prototype system; the development of a methodology for the estimation of the impact of climate variability, mainly due to aerosol, cloud and water vapor, on the solar irradiance using the integration of the observations potentially provided by prototype; the study of correlation between the surface radiation, precipitation and aerosols transport. In particular, a statistical study will be presented to assess the impact of the atmosphere on the solar irradiance at the ground, quantifying the contribution due to aerosol and clouds and separating their effect on the direct and the diffuse components of the solar radiation. This also aims to provide recommendations to the manufacturer of the devices used to exploit solar radiation.

Near-surface wind speed statistical distribution: comparison between ECMWF System 4 and ERA-Interim

NASA Astrophysics Data System (ADS)

Marcos, Raül; Gonzalez-Reviriego, Nube; Torralba, Verónica; Cortesi, Nicola; Young, Doo; Doblas-Reyes, Francisco J.

2017-04-01

In the framework of seasonal forecast verification, knowing whether the characteristics of the climatological wind speed distribution, simulated by the forecasting systems, are similar to the observed ones is essential to guide the subsequent process of bias adjustment. To bring some light about this topic, this work assesses the properties of the statistical distributions of 10m wind speed from both ERA-Interim reanalysis and seasonal forecasts of ECMWF system 4. The 10m wind speed distribution has been characterized in terms of the four main moments of the probability distribution (mean, standard deviation, skewness and kurtosis) together with the coefficient of variation and goodness of fit Shapiro-Wilks test, allowing the identification of regions with higher wind variability and non-Gaussian behaviour at monthly time-scales. Also, the comparison of the predicted and observed 10m wind speed distributions has been measured considering both inter-annual and intra-seasonal variability. Such a comparison is important in both climate research and climate services communities because it provides useful climate information for decision-making processes and wind industry applications.

Root Systems of Individual Plants, and the Biotic and Abiotic Factors Controlling Their Depth and Distribution: a Synthesis Using a Global Database.

NASA Astrophysics Data System (ADS)

Tumber-Davila, S. J.; Schenk, H. J.; Jackson, R. B.

2017-12-01

This synthesis examines plant rooting distributions globally, by doubling the number of entries in the Root Systems of Individual Plants database (RSIP) created by Schenk and Jackson. Root systems influence many processes, including water and nutrient uptake and soil carbon storage. Root systems also mediate vegetation responses to changing climatic and environmental conditions. Therefore, a collective understanding of the importance of rooting systems to carbon sequestration, soil characteristics, hydrology, and climate, is needed. Current global models are limited by a poor understanding of the mechanisms affecting rooting, carbon stocks, and belowground biomass. This improved database contains an extensive bank of records describing the rooting system of individual plants, as well as detailed information on the climate and environment from which the observations are made. The expanded RSIP database will: 1) increase our understanding of rooting depths, lateral root spreads and above and belowground allometry; 2) improve the representation of plant rooting systems in Earth System Models; 3) enable studies of how climate change will alter and interact with plant species and functional groups in the future. We further focus on how plant rooting behavior responds to variations in climate and the environment, and create a model that can predict rooting behavior given a set of environmental conditions. Preliminary results suggest that high potential evapotranspiration and seasonality of precipitation are indicative of deeper rooting after accounting for plant growth form. When mapping predicted deep rooting by climate, we predict deepest rooting to occur in equatorial South America, Africa, and central India.

Evidence for climate change in the satellite cloud record.

PubMed

Norris, Joel R; Allen, Robert J; Evan, Amato T; Zelinka, Mark D; O'Dell, Christopher W; Klein, Stephen A

2016-08-04

Clouds substantially affect Earth's energy budget by reflecting solar radiation back to space and by restricting emission of thermal radiation to space. They are perhaps the largest uncertainty in our understanding of climate change, owing to disagreement among climate models and observational datasets over what cloud changes have occurred during recent decades and will occur in response to global warming. This is because observational systems originally designed for monitoring weather have lacked sufficient stability to detect cloud changes reliably over decades unless they have been corrected to remove artefacts. Here we show that several independent, empirically corrected satellite records exhibit large-scale patterns of cloud change between the 1980s and the 2000s that are similar to those produced by model simulations of climate with recent historical external radiative forcing. Observed and simulated cloud change patterns are consistent with poleward retreat of mid-latitude storm tracks, expansion of subtropical dry zones, and increasing height of the highest cloud tops at all latitudes. The primary drivers of these cloud changes appear to be increasing greenhouse gas concentrations and a recovery from volcanic radiative cooling. These results indicate that the cloud changes most consistently predicted by global climate models are currently occurring in nature.

Evidence for climate change in the satellite cloud record

NASA Astrophysics Data System (ADS)

Norris, Joel R.; Allen, Robert J.; Evan, Amato T.; Zelinka, Mark D.; O'Dell, Christopher W.; Klein, Stephen A.

2016-08-01

Clouds substantially affect Earth’s energy budget by reflecting solar radiation back to space and by restricting emission of thermal radiation to space. They are perhaps the largest uncertainty in our understanding of climate change, owing to disagreement among climate models and observational datasets over what cloud changes have occurred during recent decades and will occur in response to global warming. This is because observational systems originally designed for monitoring weather have lacked sufficient stability to detect cloud changes reliably over decades unless they have been corrected to remove artefacts. Here we show that several independent, empirically corrected satellite records exhibit large-scale patterns of cloud change between the 1980s and the 2000s that are similar to those produced by model simulations of climate with recent historical external radiative forcing. Observed and simulated cloud change patterns are consistent with poleward retreat of mid-latitude storm tracks, expansion of subtropical dry zones, and increasing height of the highest cloud tops at all latitudes. The primary drivers of these cloud changes appear to be increasing greenhouse gas concentrations and a recovery from volcanic radiative cooling. These results indicate that the cloud changes most consistently predicted by global climate models are currently occurring in nature.

Volcanic Eruptions and Climate

NASA Technical Reports Server (NTRS)

LeGrande, Allegra N.; Anchukaitis, Kevin J.

2015-01-01

Volcanic eruptions represent some of the most climatically important and societally disruptive short-term events in human history. Large eruptions inject ash, dust, sulfurous gases (e.g. SO2, H2S), halogens (e.g. Hcl and Hbr), and water vapor into the Earth's atmosphere. Sulfurous emissions principally interact with the climate by converting into sulfate aerosols that reduce incoming solar radiation, warming the stratosphere and altering ozone creation, reducing global mean surface temperature, and suppressing the hydrological cycle. In this issue, we focus on the history, processes, and consequences of these large eruptions that inject enough material into the stratosphere to significantly affect the climate system. In terms of the changes wrought on the energy balance of the Earth System, these transient events can temporarily have a radiative forcing magnitude larger than the range of solar, greenhouse gas, and land use variability over the last millennium. In simulations as well as modern and paleoclimate observations, volcanic eruptions cause large inter-annual to decadal-scale changes in climate. Active debates persist concerning their role in longer-term (multi-decadal to centennial) modification of the Earth System, however.

Hydrological Excitations of Polar Motion Derived from Different Variables of Fgoals - g2 Climate Model

NASA Astrophysics Data System (ADS)

Winska, M.

2016-12-01

The hydrological contribution to decadal, inter-annual and multi-annual suppress polar motion derived from climate model as well as from GRACE (Gravity Recovery and Climate Experiment) data is discussed here for the period 2002.3-2016.0. The data set used here are Earth Orientation Parameters Combined 04 (EOP C04), Flexible Global Ocean-Atmosphere-Land System Model: Grid-point Version 2 (FGOAL-g2) and Global Land Data Assimilation System (GLDAS) climate models and GRACE CSR RL05 data for polar motion, hydrological and gravimetric excitation, respectively. Several Hydrological Angular Momentum (HAM) functions are calculated here from the selected variables: precipitation, evaporation, runoff, soil moisture, accumulated snow of the FGOALS and GLDAS climate models as well as from the global mass change fields from GRACE data provided by the International Earth Rotation and Reference System Service (IERS) Global Geophysical Fluids Center (GGFC). The contribution of different HAM excitation functions to achieve the full agreement between geodetic observations and geophysical excitation functions of polar motion is studied here.

The Challenges of Developing a Framework for Global Water Cycle Monitoring and Prediction (Alfred Wegener Medal Lecture)

NASA Astrophysics Data System (ADS)

Wood, Eric F.

2014-05-01

The Global Earth Observation System of Systems (GEOSS) Water Strategy ("From Observations to Decisions") recognizes that "water is essential for ensuring food and energy security, for facilitating poverty reduction and health security, and for the maintenance of ecosystems and biodiversity", and that water cycle data and observations are critical for improved water management and water security - especially in less developed regions. The GEOSS Water Strategy has articulated a number of goals for improved water management, including flood and drought preparedness, that include: (i) facilitating the use of Earth Observations for water cycle observations; (ii) facilitating the acquisition, processing, and distribution of data products needed for effective management; (iii) providing expertise, information systems, and datasets to the global, regional, and national water communities. There are several challenges that must be met to advance our capability to provide near real-time water cycle monitoring, early warning of hydrological hazards (floods and droughts) and risk assessment under climate change, regionally and globally. Current approaches to monitoring and predicting hydrological hazards are limited in many parts of the world, and especially in developing countries where national capacity is limited and monitoring networks are inadequate. This presentation describes the developments at Princeton University towards a seamless monitoring and prediction framework at all time scales that allows for consistent assessment of water variability from historic to current conditions, and from seasonal and decadal predictions to climate change projections. At the center of the framework is an experimental, global water cycle monitoring and seasonal forecast system that has evolved out of regional and continental systems for the US and Africa. The system is based on land surface hydrological modeling that is driven by satellite remote sensing precipitation to predict current hydrological conditions, flood potential and the state of drought. Seasonal climate model forecasts are downscaled and bias-corrected to drive the land surface model to provide hydrological forecasts and drought products out 6-9 months. The system relies on historic reconstructions of water variability over the 20th century, which forms the background climatology to which current conditions can be assessed. Future changes in water availability and drought risk are quantified based on bias-corrected and downscaled climate model projections that are used to drive the land surface models. For regions with lack of on-the-ground data we are field-testing low-cost environmental sensors and along with new satellite products for terrestrial hydrology and vegetation, integrating these into the system for improved monitoring and prediction. At every step there are scientific challenges whose solutions are only partially being solved. In addition there are challenges in delivering such systems as "climate services", especially to societies with low technical capacity such as rural agriculturalists in sub-Saharan Africa, but whose needs for such information are great. We provide an overview of the system and some examples of real-world applications to flood and drought events, with a focus on Africa.

Climate Data Guide - Modern Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2)

NASA Technical Reports Server (NTRS)

Cullather, Richard; Bosilovich, Michael

2017-01-01

The Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) is a global atmospheric reanalysis produced by the NASA Global Modeling and Assimilation Office (GMAO). It spans the satellite observing era from 1980 to the present. The goals of MERRA-2 are to provide a regularly-gridded, homogeneous record of the global atmosphere, and to incorporate additional aspects of the climate system including trace gas constituents (stratospheric ozone), and improved land surface representation, and cryospheric processes. MERRA-2 is also the first satellite-era global reanalysis to assimilate space-based observations of aerosols and represent their interactions with other physical processes in the climate system. The inclusion of these additional components are consistent with the overall objectives of an Integrated Earth System Analysis (IESA). MERRA-2 is intended to replace the original MERRA product, and reflects recent advances in atmospheric modeling and data assimilation. Modern hyperspectral radiance and microwave observations, along with GPS-Radio Occultation and NASA ozone datasets are now assimilated in MERRA-2. Much of the structure of the data files remains the same in MERRA-2. While the original MERRA data format was HDF-EOS, the MERRA-2 supplied binary data format is now NetCDF4 (with lossy compression to save space).

Evaluating Options for Improving California's Drought Resilience

NASA Astrophysics Data System (ADS)

Ray, P. A.; Schwarz, A.; Wi, S.; Correa, M.; Brown, C.

2015-12-01

Through a unique collaborative arrangement, the University of Massachusetts (UMass) and the California Department of Water Resources (DWR) have together performed a baseline climate change analysis of the California state (State Water Project) and federal (Central Valley Project) water systems. The first step in the baseline analysis was development of an improved basinwide hydrologic model covering a large area of California including all major tributaries to the state and federal water systems. The CalLite modeling system used by DWR for planning purposes allowed simulation of the system of reservoirs, rivers, control points, and deliveries which are then used to create performance metrics that quantify a wide range of system characteristics including water deliveries, water quality, and environmental/ecological factors. A baseline climate stress test was conducted to identify current vulnerabilities to climate change through the linking of the modeling chain with Decision Scaling concepts through the UMass bottom-up climate stress-testing algorithm. This procedure allowed the first comprehensive climate stress analysis of the California state and federal water systems not constrained by observed historical variability and wet-dry year sequences. A forward-looking drought vulnerability and adaptation assessment of the water systems based on this workflow is ongoing and preliminary results will be presented. Presentation of results will include discussion of the collaborative arrangement between DWR and UMass, which is instrumental to both the success of the research and the education of policy makers.

NASA's Modern Era Retrospective-Analysis for Research and Applications (MERRA): Early Results and Future Directions

NASA Technical Reports Server (NTRS)

Schubert, Siegfried

2008-01-01

This talk will review the status and progress of the NASA/Global Modeling and Assimilation Office (GMAO) atmospheric global reanalysis project called the Modern Era Retrospective-Analysis for Research and Applications (MERRA). An overview of NASA's emerging capabilities for assimilating a variety of other Earth Science observations of the land, ocean, and atmospheric constituents will also be presented. MERRA supports NASA Earth science by synthesizing the current suite of research satellite observations in a climate data context (covering the period 1979-present), and by providing the science and applications communities with of a broad range of weather and climate data with an emphasis on improved estimates of the hydrological cycle. MERRA is based on a major new version of the Goddard Earth Observing System Data Assimilation System (GEOS-5), that includes the Earth System Modeling Framework (ESMF)-based GEOS-5 atmospheric general circulation model and the new NOAA National Centers for Environmental Prediction (NCEP) unified grid-point statistical interpolation (GST) analysis scheme developed as a collaborative effort between NCEP and the GMAO. In addition to MERRA, the GMAO is developing new capabilities in aerosol and constituent assimilation, ocean, ocean biology, and land surface assimilation. This includes the development of an assimilation capability for tropospheric air quality monitoring and prediction, the development of a carbon-cycle modeling and assimilation system, and an ocean data assimilation system for use in coupled short-term climate forecasting.

The critical role of fire in catchment coevolution in South Eastern Australia

NASA Astrophysics Data System (ADS)

Nyman, P.; Inbar, A.; Lane, P. N. J.; Sheridan, G. J.

2016-12-01

Temperate south east Australian forested uplands are characterised by complex spatial patterns in forest types, soils and fire regimes, even within areas with similar geologies and landscape position. Preliminary measurements and experiments suggest that positive and negative feedbacks between the vegetation, fuels, fire frequency and soil erosion may control the coevolution of these observed system states. Here we propose the hypotheses that in this landscape post-fire soil erosion has played a dominant role in the coevolved system-state combinations of standing biomass, fire frequency and soil depth. To test the hypothesis a 1D simulation model was developed that links together an ecohydrological model to drive the biomass production and water and energy partitioning, a stochastic fire model that is controlled by climate, fuel load and moisture conditions, and a geomorphic model that controls soil production and fluvial and diffusive sediment transport rates. The model was calibrated to the range of existing observed quasi-equalibrium system-states of soil depth, standing biomass, fuel loading and fire frequency using field measurements from 12 instrumented eco-hydrologic microclimate research sites. The long-term partitioning of rainfall into evaporation, transpiration, and streamflow was calibrated against field and literature values. Fuel moisture and micro-climate variables were calibrated to the field microclimate stations. The calibrated model was able to reasonably replicate the observed quasi-equilibrium system-states and hydrologic outputs using current climate forcings operating over a 10,000 year period, providing confidence in the model structure and performance. The model was then used to test the hypothesis stated above, by alternatively including or excluding the post fire erosion process. An alternate hypothesis, whereby the observed system states are dominated by climate related differences in soil production rates was also tested in this way. The results support the hypothesis that feedbacks between fire, ecology, hydrology and geomorphology have played a critical role in the coevolution of south east Australian forested uplands. Similar pyro-eco-hydrologic feedbacks may play a critical role in catchment coevolution in other forested systems globally.

Application of Ecosystem Models to Assess Environmental Drivers of Mosquito Abundance and Virus Transmission Risk and Associated Public Health Implications of Climate and Land Use Change

NASA Astrophysics Data System (ADS)

Melton, F.; Barker, C.; Park, B.; Reisen, W.; Michaelis, A.; Wang, W.; Hashimoto, H.; Milesi, C.; Hiatt, S.; Nemani, R.

2008-12-01

The NASA Terrestrial Observation and Prediction System (TOPS) is a modeling framework that integrates satellite observations, meteorological observations, and ancillary data to support monitoring and modeling of ecosystem and land surface conditions in near real-time. TOPS provides spatially continuous gridded estimates of a suite of measurements describing environmental conditions, and these data products are currently being applied to support the development of new models capable of forecasting estimated mosquito abundance and transmission risk for mosquito-borne diseases such as West Nile virus. We present results from the modeling analyses, describe their incorporation into the California Vectorborne Disease Surveillance System, and describe possible implications of projected climate and land use change for patterns in mosquito abundance and transmission risk for West Nile virus in California.

Carbon dioxide and climate: a second assessment

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

Not Available

For over a century, concern has been expressed that increases in atmospheric carbon dioxide (CO/sub 2/) concentration could affect global climate by changing the heat balance of the atmosphere and Earth. Observations reveal steadily increasing concentrations of CO/sub 2/, and experiments with numerical climate models indicate that continued increase would eventually produce significant climatic change. Comprehensive assessment of the issue will require projection of future CO/sub 2/ emissions and study of the disposition of this excess carbon in the atmosphere, ocean, and biota; the effect on climate; and the implications for human welfare. This study focuses on one aspect, estimationmore » of the effect on climate of assumed future increases in atmospheric CO/sub 2/. Conclusions are drawn principally from present-day numerical models of the climate system. To address the significant role of the oceans, the study also makes use of observations of the distributions of anthropogenic tracers other than CO/sub 2/. The rapid scientific developments in these areas suggest that periodic reassessments will be warranted. The starting point for the study was a similar 1979 review by a Climate Research Board panel chaired by the late Jule G. Charney. The present study has not found any new results that necessitate substantial revision of the conclusions of the Charney report.« less

Long Term Monitoring of Atmospheric Composition at NOAA - Driving Science with 60 Year-old Records

NASA Astrophysics Data System (ADS)

Butler, J. H.

2017-12-01

NOAA's Global Monitoring Division and its precursor organizations have provided some of the longest real-time records of the trends and distributions of climatically relevant substances in the atmosphere, some going back for 60 years (http://www.esrl.noaa.gov/gmd). The focus of these measurements has been on obtaining reliable records of global trends and distributions of these substances, but the experimental design and use of measurements have advanced over time with evolving scientific questions. Today, and into this century, scientific questions continue to progress and the observing systems that address them will need to progress accordingly. Long-term, ground based observing systems in NOAA's Global Monitoring Division focus largely on three sets of questions, two of which align with WCRP grand challenges. These are Carbon Cycle System Feedbacks, Trends in Surface Radiation and Cloud Distributions, and Recovery of Stratospheric Ozone. The data collected and analyzed help us understand radiative forcing, climate sensitivity, air quality, climate modification, renewable energy options, and arctic processes, and they are useful for verifying model output and satellite retrievals. Regional information will become increasingly important for mitigating and adapting to climate change, and this information must be accurate, precise, and without bias. NOAA, with its long-standing networks and its role in providing calibrations for partnering organizations, is well positioned to provide the linkages necessary to assure that regional measurements are comparable. This presentation will identify major, climate-relevant findings that have come from NOAA's networks in the past and will address the long-term monitoring needs to support decision-making over coming decades as society begins to seriously address climate change.

Arctic summer school onboard an icebreaker

NASA Astrophysics Data System (ADS)

Alexeev, Vladimir A.; Repina, Irina A.

2014-05-01

The International Arctic Research Center (IARC) of the University of Alaska Fairbanks conducted a summer school for PhD students, post-docs and early career scientists in August-September 2013, jointly with an arctic expedition as a part of NABOS project (Nansen and Amundsen Basin Observational System) onboard the Russian research vessel "Akademik Fedorov". Both the summer school and NABOS expedition were funded by the National Science Foundation. The one-month long summer school brought together graduate students and young scientists with specialists in arctic oceanography and climate to convey to a new generation of scientists the opportunities and challenges of arctic climate observations and modeling. Young scientists gained hands-on experience during the field campaign and learned about key issues in arctic climate from observational, diagnostic, and modeling perspectives. The summer school consisted of background lectures, participation in fieldwork and mini-projects. The mini-projects were performed in collaboration with summer school instructors and members of the expedition. Key topics covered in the lectures included: - arctic climate: key characteristics and processes; - physical processes in the Arctic Ocean; - sea ice and the Arctic Ocean; - trace gases, aerosols, and chemistry: importance for climate changes; - feedbacks in the arctic system (e.g., surface albedo, clouds, water vapor, circulation); - arctic climate variations: past, ongoing, and projected; - global climate models: an overview. An outreach specialist from the Miami Science Museum was writing a blog from the icebreaker with some very impressive statistics (results as of January 1, 2014): Total number of blog posts: 176 Blog posts written/contributed by scientists: 42 Blog views: 22,684 Comments: 1,215 Number of countries who viewed the blog: 89 (on 6 continents) The 33-day long NABOS expedition started on August 22, 2013 from Kirkenes, Norway. The vessel ("Akademik Fedorov") returned to Kirkenes on September 23, 2013. In our presentation we will try to convey the spirit of learning and excitement of the students during the expedition and the summer school.

Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC)

NASA Astrophysics Data System (ADS)

Dethloff, Klaus; Rex, Markus; Shupe, Matthew

2016-04-01

The Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) is an international initiative under the International Arctic Science Committee (IASC) umbrella that aims to improve numerical model representations of sea ice, weather, and climate processes through coupled system observations and modeling activities that link the central Arctic atmosphere, sea ice, ocean, and the ecosystem. Observations of many critical parameters such as cloud properties, surface energy fluxes, atmospheric aerosols, small-scale sea-ice and oceanic processes, biological feedbacks with the sea-ice ice and ocean, and others have never been made in the central Arctic in all seasons, and certainly not in a coupled system fashion. The primary objective of MOSAiC is to develop a better understanding of these important coupled-system processes so they can be more accurately represented in regional- and global-scale weather- and climate models. Such enhancements will contribute to improved modeling of global climate and weather, and Arctic sea-ice predictive capabilities. The MOSAiC observations are an important opportunity to gather the high quality and comprehensive observations needed to improve numerical modeling of critical, scale-dependent processes impacting Arctic predictability given diminished sea ice coverage and increased model complexity. Model improvements are needed to understand the effects of a changing Arctic on mid-latitude weather and climate. MOSAiC is specifically designed to provide the multi-parameter, coordinated observations needed to improve sub-grid scale model parameterizations especially with respect to thinner ice conditions. To facilitate, evaluate, and develop the needed model improvements, MOSAiC will employ a hierarchy of modeling approaches ranging from process model studies, to regional climate model intercomparisons, to operational forecasts and assimilation of real-time observations. Model evaluations prior to the field program will be used to identify specific gaps and parameterization needs. Preliminary modeling and operational forecasting will also be necessary to directly guide field planning and optimal implementation of field resources, and to support the safety of the project. The MOSAiC Observatory will be deployed in, and drift with, the Arctic sea-ice pack for at least a full annual cycle, starting in fall 2019 and ending in autumn 2020. Initial plans are for the drift to start in the newly forming autumn sea-ice in, or near, the East Siberian Sea. The specific location will be selected to allow for the observatory to follow the Transpolar Drift towards the North Pole and on to the Fram Strait. IASC has adopted MOSAiC as a key international activity, the German Alfred Wegener Institute has made the huge contribution of the icebreaker Polarstern to serve as the central drifting observatory for this year long endeavor, and the US Department of Energy has committed a comprehensive atmospheric measurement suite. Many other nations and agencies have expressed interest in participation and in gaining access to this unprecedented observational dataset. International coordination is needed to support this groundbreaking endeavor.

Understanding and Reconciling Differences in Surface and Satellite-Based Lower Troposphere Temperatures

NASA Astrophysics Data System (ADS)

Hausfather, Z.; Thorne, P.; Mears, C. A.

2017-12-01

One of the main remaining uncertainties in global temperatures over the past few decades is the disagreement between surface and microwave sounding unit (MSU) satellite-based observations of the lower troposphere. Reconciling these will prove an important step in improving our understanding of modern climate change, and help resolve an issue that has been frequently brought to the attention of policymakers and highlighted as a reason to distrust climate observations. To assess differences between surface and satellite records, we examine data from radiosondes, from atmospheric reanalysis, from numerous different satellites, from surface observations over the land and ocean, and from global climate models. Controlling for spatial coverage, we determine where these datasets agree and disagree, isolate the differences, and identify for common factors to explain the divergences. We find large systemic differences between surface and lower troposphere warming in MSU/AMSU records compared to radiosondes, reanalysis products, and climate models that suggest possible residual inhomogeneities in satellite records. We further show that no reasonable subset of surface temperature records exhibits as little warming over the last two decades as satellite observations, suggesting that inhomogeneities in the surface record are very likely not responsible for the divergence.

CALIPSO: Global Aerosol and Cloud Observations from Lidar and Passive Instruments

NASA Technical Reports Server (NTRS)

Poole, L. R.; Winker, D. M.; Pelon, J. R.; McCormick, M. P.

2002-01-01

CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Spaceborne Observations) is an approved satellite mission being developed through collaboration between NASA and the French space agency CNES. The mission is scheduled for launch in 2004 and will operate for 3 years as part of a five-satellite formation called the Aqua constellation. This constellation will provide a unique data set on aerosol and cloud optical and physical properties and aerosol-cloud interactions that will substantially increase our understanding of the climate system and the potential for climate change.

Nonlinear Synergistic Emergence and Predictability in Complex Systems: Theory and Hydro-Climatic Applications

NASA Astrophysics Data System (ADS)

Perdigão, Rui A. P.; Hall, Julia; Pires, Carlos A. L.; Blöschl, Günter

2017-04-01

Classical and stochastic dynamical system theories assume structural coherence and dynamic recurrence with invariants of motion that are not necessarily so. These are grounded on the unproven assumption of universality in the dynamic laws derived from statistical kinematic evaluation of non-representative empirical records. As a consequence, the associated formulations revolve around a restrictive set of configurations and intermittencies e.g. in an ergodic setting, beyond which any predictability is essentially elusive. Moreover, dynamical systems are fundamentally framed around dynamic codependence among intervening processes, i.e. entail essentially redundant interactions such as couplings and feedbacks. That precludes synergistic cooperation among processes that, whilst independent from each other, jointly produce emerging dynamic behaviour not present in any of the intervening parties. In order to overcome these fundamental limitations, we introduce a broad class of non-recursive dynamical systems that formulate dynamic emergence of unprecedented states in a fundamental synergistic manner, with fundamental principles in mind. The overall theory enables innovations to be predicted from the internal system dynamics before any a priori information is provided about the associated dynamical properties. The theory is then illustrated to anticipate, from non-emergent records, the spatiotemporal emergence of multiscale hyper chaotic regimes, critical transitions and structural coevolutionary changes in synthetic and real-world complex systems. Example applications are provided within the hydro-climatic context, formulating and dynamically forecasting evolving hydro-climatic distributions, including the emergence of extreme precipitation and flooding in a structurally changing hydro-climate system. Validation is then conducted with a posteriori verification of the simulated dynamics against observational records. Agreement between simulations and observations is confirmed with robust nonlinear information diagnostics.

Downscaling climate information for local disease mapping.

PubMed

Bernardi, M; Gommes, R; Grieser, J

2006-06-01

The study of the impacts of climate on human health requires the interdisciplinary efforts of health professionals, climatologists, biologists, and social scientists to analyze the relationships among physical, biological, ecological, and social systems. As the disease dynamics respond to variations in regional and local climate, climate variability affects every region of the world and the diseases are not necessarily limited to specific regions, so that vectors may become endemic in other regions. Climate data at local level are thus essential to evaluate the dynamics of vector-borne disease through health-climate models and most of the times the climatological databases are not adequate. Climate data at high spatial resolution can be derived by statistical downscaling using historical observations but the method is limited by the availability of historical data at local level. Since the 90s', the statistical interpolation of climate data has been an important priority of the Agrometeorology Group of the Food and Agriculture Organization of the United Nations (FAO), as they are required for agricultural planning and operational activities at the local level. Since 1995, date of the first FAO spatial interpolation software for climate data, more advanced applications have been developed such as SEDI (Satellite Enhanced Data Interpolation) for the downscaling of climate data, LOCCLIM (Local Climate Estimator) and the NEW_LOCCLIM in collaboration with the Deutscher Wetterdienst (German Weather Service) to estimate climatic conditions at locations for which no observations are available. In parallel, an important effort has been made to improve the FAO climate database including at present more than 30,000 stations worldwide and expanding the database from developing countries coverage to global coverage.

Climate variability and predictability associated with the Indo-Pacific Oceanic Channel Dynamics in the CCSM4 Coupled System Model

NASA Astrophysics Data System (ADS)

Yuan, Dongliang; Xu, Peng; Xu, Tengfei

2017-01-01

An experiment using the Community Climate System Model (CCSM4), a participant of the Coupled Model Intercomparison Project phase-5 (CMIP5), is analyzed to assess the skills of this model in simulating and predicting the climate variabilities associated with the oceanic channel dynamics across the Indo-Pacific Oceans. The results of these analyses suggest that the model is able to reproduce the observed lag correlation between the oceanic anomalies in the southeastern tropical Indian Ocean and those in the cold tongue in the eastern equatorial Pacific Ocean at a time lag of 1 year. This success may be largely attributed to the successful simulation of the interannual variations of the Indonesian Throughflow, which carries the anomalies of the Indian Ocean Dipole (IOD) into the western equatorial Pacific Ocean to produce subsurface temperature anomalies, which in turn propagate to the eastern equatorial Pacific to generate ENSO. This connection is termed the "oceanic channel dynamics" and is shown to be consistent with the observational analyses. However, the model simulates a weaker connection between the IOD and the interannual variability of the Indonesian Throughflow transport than found in the observations. In addition, the model overestimates the westerly wind anomalies in the western-central equatorial Pacific in the year following the IOD, which forces unrealistic upwelling Rossby waves in the western equatorial Pacific and downwelling Kelvin waves in the east. This assessment suggests that the CCSM4 coupled climate system has underestimated the oceanic channel dynamics and overestimated the atmospheric bridge processes.

Global Observations of Aerosols and Clouds from Combined Lidar and Passive Instruments to Improve Radiation Budget and Climate Studies

NASA Technical Reports Server (NTRS)

Winker, David M.

1999-01-01

Current uncertainties in the effects of clouds and aerosols on the Earth radiation budget limit our understanding of the climate system and the potential for global climate change. Pathfinder Instruments for Cloud and Aerosol Spaceborne Observations - Climatologie Etendue des Nuages et des Aerosols (PICASSO-CENA) is a recently approved satellite mission within NASA's Earth System Science Pathfinder (ESSP) program which will address these uncertainties with a unique suite of active and passive instruments. The Lidar In-space Technology Experiment (LITE) demonstrated the potential benefits of space lidar for studies of clouds and aerosols. PICASSO-CENA builds on this experience with a payload consisting of a two-wavelength polarization-sensitive lidar, an oxygen A-band spectrometer (ABS), an imaging infrared radiometer (IIR), and a wide field camera (WFC). Data from these instruments will be used to measure the vertical distributions of aerosols and clouds in the atmosphere, as well as optical and physical properties of aerosols and clouds which influence the Earth radiation budget. PICASSO-CENA will be flown in formation with the PM satellite of the NASA Earth Observing System (EOS) to provide a comprehensive suite of coincident measurements of atmospheric state, aerosol and cloud optical properties, and radiative fluxes. The mission will address critical uncertainties iin the direct radiative forcing of aerosols and clouds as well as aerosol influences on cloud radiative properties and cloud-climate radiation feedbacks. PICASSO-CENA is planned for a three year mission, with a launch in early 2003. PICASSO-CENA is being developed within the framework of a collaboration between NASA and CNES.

Theoretical electron scattering amplitudes and spin polarizations. Electron energies 100 to 1500 eV Part II. Be, N, O, Al, Cl, V, Co, Cu, As, Nb, Ag, Sn, Sb, I, and Ta targets

NASA Astrophysics Data System (ADS)

Wildhaber, M. L.; Wikle, C. K.; Anderson, C. J.; Franz, K. J.; Moran, E. H.; Dey, R.

2012-12-01

Recent decades have brought substantive changes in land use and climate across the earth, prompting a need to think of population and community ecology not as a static entity, but as a dynamic process. Increasingly there is evidence of ecological changes due to climate change. Although much of this evidence comes from ground-truth observations of biogeographic data, there is increasing reliance on models that relate climate variables to biological systems. Such models can then be used to explore potential changes to population and community level ecological systems in response to climate scenarios as obtained from global climate models (GCMs). A key issue associated with modeling ecosystem response to climate is GCM downscaling to regional and local ecological/biological response models that can be used in vulnerability and risk assessments of the potential effects of climate change. The need is for an explicit means for scaling results up or down multiple hierarchical levels and an effective assessment of the level of uncertainty surrounding current knowledge, data, and data collection methods with these goals identified as in need of acceleration in the U.S. Climate Change Science Program FY2009 Implementation Priorities. In the end, such work should provide the information needed to develop adaptation and mitigation methodologies to minimize the effects of directional and nonlinear climate change on the Nation's land, water, ecosystems, and biological populations. We are working to develop an approach that includes multi-scale and hierarchical Bayesian modeling of Missouri River sturgeon population dynamics. Statistical linkages are defined to quantify implications of climate on fish populations of the Missouri River ecosystem. This approach is a hybrid between physical (deterministic) downscaling and statistical downscaling, recognizing that there is uncertainty in both. The model must include linkages between climate and habitat, and between habitat and population. A key advantage of the hierarchical approach used in this study is that it incorporates various sources of observations and includes established scientific knowledge, and associated uncertainties. The goal is to evaluate the potential distributional changes in an ecological system, given distributional changes implied by a series of linked climate and system models under various emissions/use scenarios. The predictive modeling system being developed will be a powerful tool for evaluating management options for coping with global change consequences and assessing uncertainty of those evaluations. Specifically for the endangered pallid sturgeon (Scaphirhynchus albus), we are already able to assess potential effects of any climate scenario on growth and population size distribution. Future models will incorporate survival and reproduction. Ultimately, these models provide guidance for successful recovery and conservation of the pallid sturgeon. Here we present a basic outline of the approach we are developing and a simple pallid sturgeon example to demonstrate how multiple scales and parameter uncertainty are incorporated.

Big Data Challenges in Climate Science: Improving the Next-Generation Cyberinfrastructure

NASA Technical Reports Server (NTRS)

Schnase, John L.; Lee, Tsengdar J.; Mattmann, Chris A.; Lynnes, Christopher S.; Cinquini, Luca; Ramirez, Paul M.; Hart, Andre F.; Williams, Dean N.; Waliser, Duane; Rinsland, Pamela;

Towards a Tropical Pacific Observing System for 2020 and Beyond.

NASA Astrophysics Data System (ADS)

Hill, K. L.; Kessler, W. S.; Smith, N.

2016-02-01

The international TPOS 2020 Project arose out of a review workshop in January 2014, following challenges sustaining TAO-TRITON array in 2012, with the aim of rethinking the tropical Pacific arrays in light of new scientific understanding and new ocean technology since its original design in the 1980s-90s. Observing and understanding ENSO remains a fundamental motivation, extending to biogeochemical phenomena, to processes on smaller scales that rectify into the low frequency, and, to the interaction of the coupled boundary layers of the upper ocean and lower atmosphere. Our primary customers remain the operational prediction centers and we will design an array to support research into physical processes, especially those not well represented in current-generation models. Current-generation forecast systems (data assimilation and the model physics) do not make effective-enough use of observations, thus the modeling centers are well-represented in the TPOS 2020 structure and our sampling is targeted to where the forecasts systems need guidance for improvement While we advocate evolution of the present arrays, the long climate records built up at mooring sites, repeated ship surveys, and island stations are fundamental to detecting and diagnosing both natural climate variability and detecting climate change signatures. Task teams have been established in specific topic areas. These will report in mid-2016, when a plan for the revised arrays will be presented to the agencies and governments, for completion of the evolution by 2020.This presentation will discuss the motivation, guiding principles, and potential changes of direction for the tropical Pacific observing system.

SORCE: Solar Radiation and Climate Experiment

NASA Technical Reports Server (NTRS)

Cahalan, Robert; Rottman, Gary; Lau, William K. M. (Technical Monitor)

2002-01-01

Contents include the following: Understanding the Sun's influence on the Earth; How the Sun affect Earth's climate; By how much does the Sun's radiation very; Understanding Solar irradiance; History of Solar irradiance observations; The SORCE mission; How do the SORCE instruments measure solar radiation; Total irradiance monitor (TIM); Spectral irradiance monitor (SIM); Solar stellar irradiance comparison experiment (SOLSTICE); XUV photometer system (XPS).

An approach for the long-term 30-m land surface snow-free albedo retrieval from historic Landsat surface reflectance and MODIS-based a priori anisotropy knowledge

USDA-ARS?s Scientific Manuscript database

Land surface albedo has been recognized by the Global Terrestrial Observing System (GTOS) as an essential climate variable crucial for accurate modeling and monitoring of the Earth’s radiative budget. While global climate studies can leverage albedo datasets from MODIS, VIIRS, and other coarse-reso...

Earth Observations in Support of Offshore Wind Energy Management in the Euro-Atlantic Region

NASA Astrophysics Data System (ADS)

Liberato, M. L. R.

2017-12-01

Climate change is one of the most important challenges in the 21st century and the energy sector is a major contributor to GHG emissions. Therefore greater attention has been given to the evaluation of offshore wind energy potentials along coastal areas, as it is expected offshore wind energy to be more efficient and cost-effective in the near future. Europe is developing offshore sites for over two decades and has been growing at gigawatt levels in annual capacity. Portugal is among these countries, with the development of a 25MW WindFloat Atlantic wind farm project. The international scientific community has developed robust ability on the research of the climate system components and their interactions. Climate scientists have gained expertise in the observation and analysis of the climate system as well as on the improvement of model and predictive capabilities. Developments on climate science allow advancing our understanding and prediction of the variability and change of Earth's climate on all space and time scales, while improving skilful climate assessments and tools for dealing with future challenges of a warming planet. However the availability of greater datasets amplifies the complexity on manipulation, representation and consequent analysis and interpretation of such datasets. Today the challenge is to translate scientific understanding of the climate system into climate information for society and decision makers. Here we discuss the development of an integration tool for multidisciplinary research, which allows access, management, tailored pre-processing and visualization of datasets, crucial to foster research as a service to society. One application is the assessment and monitoring of renewable energy variability, such as wind or solar energy, at several time and space scales. We demonstrate the ability of the e-science platform for planning, monitoring and management of renewable energy, particularly offshore wind energy in the Euro-Atlantic region. Further we explore the automatization of processes using different domains and datasets, which facilitate further research in evaluating and understanding renewable energy variability. AcknowledgementsThis work is supported by Foundation for Science and Technology (FCT), Portugal, project UID/GEO/50019/2013 - Instituto Dom Luiz.

CUAHSI Hydrologic Information Systems

NASA Astrophysics Data System (ADS)

Maidment, D.; Zaslavsky, I.; Tarboton, D.; Piasecki, M.; Goodall, J.

2006-12-01

The Consortium of Universities for the Advancement of Hydrologic Science, Inc (CUAHSI) has a Hydrologic Information System (HIS) project, which is supported by NSF to develop infrastructure and services to support the advance of hydrologic science in the United States. This paper provides an overview of the HIS project. A set of web services called WaterOneFlow is being developed to provide better access to water observations data (point measurements of streamflow, water quality, climate and groundwater levels) from government agencies and individual investigator projects. Successful partnerships have been created with the USGS National Water Information System, EPA Storet and the NCDC Climate Data Online. Observations catalogs have been created for stations in the measurement networks of each of these data systems so that they can be queried in a uniform manner through CUAHSI HIS, and data delivered from them directly to the user via web services. A CUAHSI Observations Data Model has been designed for storing individual investigator data and an equivalent set of web services created for that so that individual investigators can publish their data onto the internet in the same format CUAHSI is providing for the federal agency data. These data will be accessed through HIS Servers hosted at the national level by CUAHSI and also by research centers and academic departments for regional application of HIS. An individual user application called HIS Analyst will enable individual hydrologic scientists to access the information from the network of HIS Servers. The present focus is on water observations data but later development of this system will include weather and climate grid information, GIS data, remote sensing data and linkages between data and hydrologic simulation models.

COST Action ES1206: Advanced GNSS Tropospheric Products forMonitoring Severe Weather Events and Climate (GNSS4SWEC)

NASA Astrophysics Data System (ADS)

Jones, J.; Guerova, G.; Dousa, J.; Dick, G.; Haan, de, S.; Pottiaux, E.; Bock, O.; Pacione, R.

2016-12-01

GNSS is now an established atmospheric observing system which can accurately sense water vapour, the mostabundant greenhouse gas, accounting for 60-70% of atmospheric warming. Water vapour observations arecurrently under-sampled and obtaining and exploiting additional high-quality humidity observations is essential tosevere weather forecasting and climate monitoring. COST Action ES1206 addresses new and improved capabilities from developments in both the GNSS andmeteorological communities to address these requirements. For the first time, the synergy of multi-GNSS(GPS, GLONASS and Galileo) will be used to develop new, advanced tropospheric products, exploiting the fullpotential of multi-GNSS water vapour estimates on a wide range of temporal and spatial scales, from real-timemonitoring and forecasting of severe weather, to climate research. In addition the Action will promote the useof meteorological data in GNSS positioning, navigation, and timing services and stimulate knowledge and datatransfer throughout Europe.

An Update on the VAMOS Extremes Working Group Activities

NASA Technical Reports Server (NTRS)

Schubert, Siegfried; Cavalcanti, Iracema

2011-01-01

We review here the progress of the Variability of the American MOnsoon Systems (VAMOS) extremes working group since it was formed in February of 2010. The goals of the working group are to 1) develop an atlas of warm-season extremes over the Americas, 2) evaluate existing and planned simulations, and 3) suggest new model runs to address mechanisms and predictability of extremes. Substantial progress has been made in the development of an extremes atlas based on gridded observations and several reanalysis products including Modern Era Retrospective-Analysis for Research and Applications (MERRA) and Climate Forecast System Reanalysis (CFSR). The status of the atlas, remaining issues and plans for its expansion to include model data will be discussed. This includes the possibility of adding a companion atlas based on station observations based on the software developed under the World Climate Research Programme (WCRP) Expert Team on Climate Change. Detection and Indices (ETCCDI) activity. We will also review progress on relevant research and plans for the use and validation of the atlas results.

A satellite view of aerosols in the climate system

NASA Technical Reports Server (NTRS)

Kaufman, Yoram J.; Tanre, Didier; Boucher, Olivier

2002-01-01

Anthropogenic aerosols are intricately linked to the climate system and to the hydrologic cycle. The net effect of aerosols is to cool the climate system by reflecting sunlight. Depending on their composition, aerosols can also absorb sunlight in the atmosphere, further cooling the surface but warming the atmosphere in the process. These effects of aerosols on the temperature profile, along with the role of aerosols as cloud condensation nuclei, impact the hydrologic cycle, through changes in cloud cover, cloud properties and precipitation. Unravelling these feedbacks is particularly difficult because aerosols take a multitude of shapes and forms, ranging from desert dust to urban pollution, and because aerosol concentrations vary strongly over time and space. To accurately study aerosol distribution and composition therefore requires continuous observations from satellites, networks of ground-based instruments and dedicated field experiments. Increases in aerosol concentration and changes in their composition, driven by industrialization and an expanding population, may adversely affect the Earth's climate and water supply.

Atmospheric and oceanographic research review, 1979

NASA Technical Reports Server (NTRS)

1980-01-01

Papers generated by atmospheric, oceanographic, and climatological research performed during 1979 at the Goddard Laboratory for Atmospheric Sciences are presented. The GARP/global weather research is aimed at developing techniques for the utilization and analysis of the FGGE data sets. Observing system studies were aimed at developing a GLAS TIROS N sounding retrieval system and preparing for the joint NOAA/NASA AMTS simulation study. The climate research objective is to support the development and effective utilization of space acquired data systems by developing the GLAS GCM for short range climate predictions, studies of the sensitivity of climate to boundary conditions, and predictability studies. Ocean/air interaction studies concentrated on the development of models for the prediction of upper ocean currents, temperatures, sea state, mixed layer depths, and upwelling zones, and on studies of the interactions of the atmospheric and oceanic circulation systems on time scales of a month or more.

Meteorological Drivers of Extreme Air Pollution Events

NASA Astrophysics Data System (ADS)

Horton, D. E.; Schnell, J.; Callahan, C. W.; Suo, Y.

2017-12-01

The accumulation of pollutants in the near-surface atmosphere has been shown to have deleterious consequences for public health, agricultural productivity, and economic vitality. Natural and anthropogenic emissions of ozone and particulate matter can accumulate to hazardous concentrations when atmospheric conditions are favorable, and can reach extreme levels when such conditions persist. Favorable atmospheric conditions for pollutant accumulation include optimal temperatures for photochemical reaction rates, circulation patterns conducive to pollutant advection, and a lack of ventilation, dispersion, and scavenging in the local environment. Given our changing climate system and the dual ingredients of poor air quality - pollutants and the atmospheric conditions favorable to their accumulation - it is important to characterize recent changes in favorable meteorological conditions, and quantify their potential contribution to recent extreme air pollution events. To facilitate our characterization, this study employs the recently updated Schnell et al (2015) 1°×1° gridded observed surface ozone and particulate matter datasets for the period of 1998 to 2015, in conjunction with reanalysis and climate model simulation data. We identify extreme air pollution episodes in the observational record and assess the meteorological factors of primary support at local and synoptic scales. We then assess (i) the contribution of observed meteorological trends (if extant) to the magnitude of the event, (ii) the return interval of the meteorological event in the observational record, simulated historical climate, and simulated pre-industrial climate, as well as (iii) the probability of the observed meteorological trend in historical and pre-industrial climates.

Climatic variability leads to later seasonal flowering of Floridian plants.

PubMed

Von Holle, Betsy; Wei, Yun; Nickerson, David

2010-07-21

Understanding species responses to global change will help predict shifts in species distributions as well as aid in conservation. Changes in the timing of seasonal activities of organisms over time may be the most responsive and easily observable indicator of environmental changes associated with global climate change. It is unknown how global climate change will affect species distributions and developmental events in subtropical ecosystems or if climate change will differentially favor nonnative species. Contrary to previously observed trends for earlier flowering onset of plant species with increasing spring temperatures from mid and higher latitudes, we document a trend for delayed seasonal flowering among plants in Florida. Additionally, there were few differences in reproductive responses by native and nonnative species to climatic changes. We argue that plants in Florida have different reproductive cues than those from more northern climates. With global change, minimum temperatures have become more variable within the temperate-subtropical zone that occurs across the peninsula and this variation is strongly associated with delayed flowering among Florida plants. Our data suggest that climate change varies by region and season and is not a simple case of species responding to consistently increasing temperatures across the region. Research on climate change impacts need to be extended outside of the heavily studied higher latitudes to include subtropical and tropical systems in order to properly understand the complexity of regional and seasonal differences of climate change on species responses.

Defining climate modeling user needs: which data are actually required to support impact analysis and adaptation policy development?

NASA Astrophysics Data System (ADS)

Swart, R. J.; Pagé, C.

2010-12-01

Until recently, the policy applications of Earth System Models in general and climate models in particular were focusing mainly on the potential future changes in the global and regional climate and attribution of observed changes to anthropogenic activities. Is climate change real? And if so, why do we have to worry about it? Following the broad acceptance of the reality of the risks by the majority of governments, particularly after the publication of IPCC’s 4th Assessment Report and the increasing number of observations of changes in ecological and socio-economic systems that are consistent with the observed climatic changes, governments, companies and other societal groups have started to evaluate their own vulnerability in more detail and to develop adaptation and mitigation strategies. After an early focus on the most vulnerable developing countries, recently, an increasing number of industrialized countries have embarked on the design of adaptation and mitigation plans, or on studies to evaluate the level of climate resilience of their development plans and projects. Which climate data are actually required to effectively support these activities? This paper reports on the efforts of the IS-ENES project, the infrastructure project of the European Network for Earth System Modeling, to address this question. How do we define user needs and can the existing gap between the climate modeling and impact research communities be bridged in support of the ENES long-term strategy? In contrast from the climate modeling community, which has a relatively long history of collaboration facilitated by a relatively uniform subject matter, commonly agreed definitions of key terminology and some level of harmonization of methods, the climate change impacts research community is very diverse and fragmented, using a wide variety of data sources, methods and tools. An additional complicating factor is that researchers working on adaptation usually closely collaborate with non-scientific stakeholders in government, civil society and the private sector, in a context which is different in many European countries. In the IS-ENES effort, a dialogue is set up between the communities in Europe, building on various existing research networks in the area of climate change impacts, vulnerability and adaptation. Generally, the data needs have not been well articulated. If asked, people working on impacts and adaptation routinely seem to ask for data with the highest possible resolution. However, in reality for many impact and adaptation applications this is not needed, and the large resulting data sets may exceed the analytical capacity of the impact researchers. For impact analysis often various types of climate indices, derived from primary climate model output variables, are required, including indices for extremes and in probabilistic format. Rather than making output from climate modeling generically available, e.g. through a climate service e-portal, context-specific tailoring of information for specific applications is important for effective use. This may require some level of interaction between the users and the data providers, dependent on the specific questions to be addressed.

Climate Reanalysis: Progress and Future Prospects

NASA Technical Reports Server (NTRS)

Gelaro, Ron

2018-01-01

Reanalysis is the process whereby an unchanging data assimilation system is used to provide a consistent reprocessing of observations, typically spanning an extended segment of the historical data record. The process relies on an underlying model to combine often-disparate observations in a physically consistent manner, enabling production of gridded data sets for a broad range of applications including the study of historical weather events, preparation of climatologies, business sector development and, more recently, climate monitoring. Over the last few decades, several generations of reanalyses of the global atmosphere have been produced by various operational and research centers, focusing more or less on the period of regular conventional and satellite observations beginning in the mid to late twentieth century. There have also been successful efforts to extend atmospheric reanalyses back to the late nineteenth and early twentieth centuries, using mostly surface observations. Much progress has resulted from (and contributed to) advancements in numerical weather prediction, especially improved models and data assimilation techniques, increased computing capacity, the availability of new observation types and efforts to recover and improve the quality of historical ones. The recent extension of forecast systems that allow integrated modeling of meteorological, oceanic, land surface, and chemical variables provide the basic elements for coupled data assimilation. This has opened the door to the development of a new generation of coupled reanalyses of the Earth system, or integrated Earth system analyses (IESA). Evidence so far suggests that this approach can improve the analysis of currently uncoupled components of the Earth system, especially at their interface, and lead to increased predictability. However, extensive analysis coupling as envisioned for IESA, while progressing, still presents significant challenges. These include model biases that can be exacerbated when coupled, component systems with different physical characteristics and different spatial and temporal scales, and component observations in different media with different spatial and temporal frequencies and different latencies. Quantification of uncertainty in reanalyses is also a critical challenge and is important for expanding their utility as a tool for climate change assessment. This talk provides a brief overview of the progress of reanalysis development during recent decades, and describes remaining challenges in the progression toward coupled Earth system reanalyses.

Effects of adjusting cropping systems on utilization efficiency of climatic resources in Northeast China under future climate scenarios

NASA Astrophysics Data System (ADS)

Guo, Jianping; Zhao, Junfang; Xu, Yanhong; Chu, Zheng; Mu, Jia; Zhao, Qian

Quantitatively evaluating the effects of adjusting cropping systems on the utilization efficiency of climatic resources under climate change is an important task for assessing food security in China. To understand these effects, we used daily climate variables obtained from the regional climate model RegCM3 from 1981 to 2100 under the A1B scenario and crop observations from 53 agro-meteorological experimental stations from 1981 to 2010 in Northeast China. Three one-grade zones of cropping systems were divided by heat, water, topography and crop-type, including the semi-arid areas of the northeast and northwest (III), the one crop area of warm-cool plants in semi-humid plain or hilly regions of the northeast (IV), and the two crop area in irrigated farmland in the Huanghuaihai Plain (VI). An agro-ecological zone model was used to calculate climatic potential productivities. The effects of adjusting cropping systems on climate resource utilization in Northeast China under the A1B scenario were assessed. The results indicated that from 1981 to 2100 in the III, IV and VI areas, the planting boundaries of different cropping systems in Northeast China obviously shifted toward the north and the east based on comprehensively considering the heat and precipitation resources. However, due to high temperature stress, the climatic potential productivity of spring maize was reduced in the future. Therefore, adjusting the cropping system is an effective way to improve the climatic potential productivity and climate resource utilization. Replacing the one crop in one year model (spring maize) by the two crops in one year model (winter wheat and summer maize) significantly increased the total climatic potential productivity and average utilization efficiencies. During the periods of 2011-2040, 2041-2070 and 2071-2100, the average total climatic potential productivities of winter wheat and summer maize increased by 9.36%, 11.88% and 12.13% compared to that of spring maize, respectively. Additionally, compared with spring maize, the average utilization efficiencies of thermal resources of winter wheat and summer maize dramatically increased by 9.2%, 12.1% and 12.0%, respectively. The increases in the average utilization efficiencies of precipitation resources of winter wheat and summer maize were 1.78 kg hm-2 mm-1, 2.07 kg hm-2 mm-1 and 1.92 kg hm-2 mm-1 during 2011-2040, 2041-2070 and 2071-2100, respectively. Our findings highlight that adjusting cropping systems can dominantly contribute to utilization efficiency increases of agricultural climatic resources in Northeast China in the future.

The MIT IGSM-CAM framework for uncertainty studies in global and regional climate change

NASA Astrophysics Data System (ADS)

Monier, E.; Scott, J. R.; Sokolov, A. P.; Forest, C. E.; Schlosser, C. A.

2011-12-01

The MIT Integrated Global System Model (IGSM) version 2.3 is an intermediate complexity fully coupled earth system model that allows simulation of critical feedbacks among its various components, including the atmosphere, ocean, land, urban processes and human activities. A fundamental feature of the IGSM2.3 is the ability to modify its climate parameters: climate sensitivity, net aerosol forcing and ocean heat uptake rate. As such, the IGSM2.3 provides an efficient tool for generating probabilistic distribution functions of climate parameters using optimal fingerprint diagnostics. A limitation of the IGSM2.3 is its zonal-mean atmosphere model that does not permit regional climate studies. For this reason, the MIT IGSM2.3 was linked to the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM) version 3 and new modules were developed and implemented in CAM in order to modify its climate sensitivity and net aerosol forcing to match that of the IGSM. The IGSM-CAM provides an efficient and innovative framework to study regional climate change where climate parameters can be modified to span the range of uncertainty and various emissions scenarios can be tested. This paper presents results from the cloud radiative adjustment method used to modify CAM's climate sensitivity. We also show results from 21st century simulations based on two emissions scenarios (a median "business as usual" scenario where no policy is implemented after 2012 and a policy scenario where greenhouse-gas are stabilized at 660 ppm CO2-equivalent concentrations by 2100) and three sets of climate parameters. The three values of climate sensitivity chosen are median and the bounds of the 90% probability interval of the probability distribution obtained by comparing the observed 20th century climate change with simulations by the IGSM with a wide range of climate parameters values. The associated aerosol forcing values were chosen to ensure a good agreement of the simulations with the observed climate change over the 20th century. Because the concentrations of sulfate aerosols significantly decrease over the 21st century in both emissions scenarios, climate changes obtained in these six simulations provide a good approximation for the median, and the 5th and 95th percentiles of the probability distribution of 21st century climate change.

Volcanic Eruptions and Climate: Outstanding Research Issues

NASA Astrophysics Data System (ADS)

Robock, Alan

2016-04-01

Large volcanic eruptions inject sulfur gases into the stratosphere, which convert to sulfate aerosols with an e-folding residence time of about one year. The radiative and chemical effects of this aerosol cloud produce responses in the climate system. Based on observations after major eruptions of the past and experiments with numerical models of the climate system, we understand much about their climatic impact, but there are also a number of unanswered questions. Volcanic eruptions produce global cooling, and are an important natural cause of interannual, interdecadal, and even centennial-scale climate change. One of the most interesting volcanic effects is the "winter warming" of Northern Hemisphere continents following major tropical eruptions. During the winter in the Northern Hemisphere following every large tropical eruption of the past century, surface air temperatures over North America, Europe, and East Asia were warmer than normal, while they were colder over Greenland and the Middle East. This pattern and the coincident atmospheric circulation correspond to the positive phase of the Arctic Oscillation. While this response is observed after recent major eruptions, most state-of-the-art climate models have trouble simulating winter warming. Why? High latitude eruptions in the Northern Hemisphere, while also producing global cooling, do not have the same impact on atmospheric dynamics. Both tropical and high latitude eruptions can weaken the Indian and African summer monsoon, and the effects can be seen in past records of flow in the Nile and Niger Rivers. Since the Mt. Pinatubo eruption in the Philippines in 1991, there have been no large eruptions that affected climate, but the cumulative effects of small eruptions over the past decade have had a small effect on global temperature trends. Some important outstanding research questions include: How much seasonal, annual, and decadal predictability is possible following a large volcanic eruption? Do volcanic eruptions change the probability of El Niño or La Niña in the years following the eruption? Are there decadal-scale oceanic responses that can provide long-term predictability? What was the contribution of volcanic eruptions to initiation and maintenance of the Little Ice Age? What are the observational needs for future volcanic eruptions that will help to improve forecasts, observe responses following volcanic eruptions, and better understand nucleation and growth of sulfate aerosols, which is important for evaluating suggestions for considering anthropogenic stratospheric clouds for climate engineering?

The Seasonal cycle of the Tropical Lower Stratospheric Water Vapor in Chemistry-Climate Models in Comparison with Observations

NASA Astrophysics Data System (ADS)

Wang, X.; Dessler, A. E.

2017-12-01

The seasonal cycle is one of the key features of the tropical lower stratospheric water vapor, so it is important that the climate models reproduce it. In this analysis, we evaluate how well the Goddard Earth Observing System Chemistry Climate Model (GEOSCCM) and the Whole Atmosphere Community Climate Model (WACCM) reproduce the seasonal cycle of tropical lower stratospheric water vapor. We do this by comparing the models to observations from the Microwave Limb Sounder (MLS) and the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim (ERAi). We also evaluate if the chemistry-climate models (CCMs) reproduce the key transport and dehydration processes that regulate the seasonal cycle using a forward, domain filling, diabatic trajectory model. Finally, we explore the changes of the seasonal cycle during the 21st century in the two CCMs. Our results show general agreement in the seasonal cycles from the MLS, the ERAi, and the CCMs. Despite this agreement, there are some clear disagreements between the models and the observations on the details of transport and dehydration in the TTL. Finally, both the CCMs predict a moister seasonal cycle by the end of the 21st century. But they disagree on the changes of the seasonal amplitude, which is predicted to increase in the GEOSCCM and decrease in the WACCM.

Climate impact of idealized winter polar mesospheric and stratospheric ozone losses as caused by energetic particle precipitation

NASA Astrophysics Data System (ADS)

Meraner, Katharina; Schmidt, Hauke

2018-01-01

Energetic particles enter the polar atmosphere and enhance the production of nitrogen oxides and hydrogen oxides in the winter stratosphere and mesosphere. Both components are powerful ozone destroyers. Recently, it has been inferred from observations that the direct effect of energetic particle precipitation (EPP) causes significant long-term mesospheric ozone variability. Satellites observe a decrease in mesospheric ozone up to 34 % between EPP maximum and EPP minimum. Stratospheric ozone decreases due to the indirect effect of EPP by about 10-15 % observed by satellite instruments. Here, we analyze the climate impact of winter boreal idealized polar mesospheric and polar stratospheric ozone losses as caused by EPP in the coupled Max Planck Institute Earth System Model (MPI-ESM). Using radiative transfer modeling, we find that the radiative forcing of mesospheric ozone loss during polar night is small. Hence, climate effects of mesospheric ozone loss due to energetic particles seem unlikely. Stratospheric ozone loss due to energetic particles warms the winter polar stratosphere and subsequently weakens the polar vortex. However, those changes are small, and few statistically significant changes in surface climate are found.

PM2.5 and tropospheric ozone in China: overview of situation and responses

NASA Astrophysics Data System (ADS)

Zhang, Hua

This work reviewed the observational status of PM2.5 and tropospheric ozone in China. It told us the observational facts on the ratios of typical types of aerosol components to the total PM2.5/PM10, and daily and seasonal change of near surface ozone concentration at different cities of China; the global concentration distribution of tropospheric ozone observed by satellite in 2010-2013 was also given for comparison; the PM2.5 concentration distribution and their seasonal change in China region were simulated by an aerosol chemistry-global climate modeling system. Different contribution from five kinds of aerosols to the simulated PM2.5 was analyzed. Then, it linked the emissions of aerosol and greenhouse gases and their radiative forcing and thus gave their climatic effect by reducing their emissions on the basis of most recently published IPCC AR5. Finally it suggested policies on reducing emissions of short-lived climate pollutants (SLCPs) (such as PM2.5 and tropospheric ozone) in China from protecting both climate and environment.

COST Action ES1206: Advanced GNSS Tropospheric Products for Monitoring Severe Weather Events and Climate (GNSS4SWEC)

NASA Astrophysics Data System (ADS)

Jones, Jonathan; Guerova, Guergana; Dousa, Jan; Dick, Galina; de Haan, Siebren; Pottiaux, Eric; Bock, Olivier; Pacione, Rosa

2017-04-01

GNSS is a well established atmospheric observing technique which can accurately sense atmospheric water vapour, the most abundant greenhouse gas, accounting for up to 70% of atmospheric warming. Water vapour is typically under-sampled in modern operational meteorological observing systems and obtaining and exploiting additional high-quality humidity observations is essential to improve weather forecasting and climate monitoring. COST Action ES1206 is a 4-year project, running from 2013 to 2017, which is coordinating the research activities and improved capabilities from concurrent developments in the GNSS, meteorological and climate communities. For the first time, the synergy of multi-GNSS constellations is used to develop new, more advanced tropospheric products, exploiting the full potential of multi-GNSS on a wide range of temporal and spatial scales - from real-time products monitoring and forecasting severe weather, to the highest quality post-processed products suitable for climate research. The Action also promotes the use of meteorological data as an input to real-time GNSS services and is stimulating the transfer of knowledge and data throughout Europe and beyond.

Dynamics of the Coupled Human-climate System Resulting from Closed-loop Control of Solar Geoengineering

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

MacMartin, Douglas; Kravitz, Benjamin S.; Keith, David

2014-07-08

If solar radiation management (SRM) were ever implemented, feedback of the observed climate state might be used to adjust the radiative forcing of SRM, in order to compensate for uncertainty in either the forcing or the climate response; this would also compensate for unexpected changes in the system, e.g. a nonlinear change in climate sensitivity. This feedback creates an emergent coupled human-climate system, with entirely new dynamics. In addition to the intended response to greenhouse-gas induced changes, the use of feedback would also result in a geoengineering response to natural climate variability. We use a simple box-diffusion dynamic model tomore » understand how changing feedback-control parameters and time delay affect the behavior of this coupled natural-human system, and verify these predictions using the HadCM3L general circulation model. In particular, some amplification of natural variability is unavoidable; any time delay (e.g., to average out natural variability, or due to decision-making) exacerbates this amplification, with oscillatory behavior possible if there is a desire for rapid correction (high feedback gain), but a delayed response needed for decision making. Conversely, the need for feedback to compensate for uncertainty, combined with a desire to avoid excessive amplification, results in a limit on how rapidly SRM could respond to uncertain changes.« less

Developing the architecture for the Climate Information Portal for Copernicus

NASA Astrophysics Data System (ADS)

Som de Cerff, Wim; Thijsse, Peter; Plieger, Maarten; Pascoe, Stephen; Jukes, Martin; Leadbetter, Adam; Goosen, Hasse; de Vreede, Ernst

2015-04-01

Climate change is impacting the environment, society and policy decisions. Information about climate change is available from many sources, but not all of them are reliable. The CLIPC project is developing a portal to provide a single point of access for authoritative scientific information on climate change. This ambitious objective is made possible through the Copernicus Earth Observation Programme for Europe, which will deliver a new generation of environmental measurements of climate quality. The data about the physical environment which is used to inform climate change policy and adaptation measures comes from several categories: satellite measurements, terrestrial observing systems, model projections and simulations and from re-analyses (syntheses of all available observations constrained with numerical weather prediction systems). These data categories are managed by different communities: CLIPC will provide a single point of access for the whole range of data. Information on data value and limitations will be provided as part of a knowledge base of authoritative climate information. The impacts of climate change on society will generally reflect a range of different environmental and climate system changes, and different sectors and actors within society will react differently to these changes. The CLIPC portal will provide some a number of indicators showing impacts on specific sectors which have been generated using a range of factors selected through structured expert consultation. It will also, as part of the transformation services, allow users to explore the consequences of using different combinations of driving factors which they consider to be of particular relevance to their work or life. The portal will provide information on the scientific quality and pitfalls of such transformations to prevent misleading usage of the results. The CLIPC project will not be able to process a comprehensive range of climate change impacts on the physical environment and society, but will develop an end to end processing chain (indicator toolkit), from comprehensive information on the climate state through to highly aggregated decision relevant products. This processing chain will be demonstrated within three thematic areas: water, rural and urban. Indicators of climate change and climate change impact will be provided, and a toolkit to update and post process the collection of indicators will be integrated into the portal. For the indicators three levels (Tiers) have been loosely defined: Tier 1: field summarising properties of the climate system; e.g. temperature change; Tier 2: expressed in terms of environmental properties outside the climate system; e.g. flooding change; Tier 3: expressed in social and economic impact. For the architecture, CLIPC has two interlocked themes: 1. Harmonised access to climate datasets derived from models, observations and re-analyses 2. A climate impact toolkit to evaluate, rank and aggregate indicators For development of the CLIPC architecture an Agile 'storyline' approach is taken. The storyline is a real world use case and consists of producing a Tier 3 indicator (Urban Heat Vulnerability) and making it available through the CLIPC infrastructure for a user group. In this way architecture concepts can be directly tested and improved. Also, the produced indicator can be shown to users to refine requirements. Main components of the CLIPC architecture are 1) Data discovery and access, 2) Data processing, 3) Data visualization, 4) Knowledge base and 5) User Management. The Data discovery and access component main challenge is to provide harmonized access to various sources of climate data (ngEO, EMODNET/SeaDataNet, ESGF, MyOcean). The discovery service concept will be provided using a CLIPC data and data product catalogue and via a structured data search on selected infrastructures, using NERC vocabulary services and mappings. Data processing will be provided using OGC WPS services, linking/re-using existing processing services from climate4impact.eu. The processing services will allow users to calculate climate impact indicators (Tier 1, 2 and 3). Processing wizards will guide users in processing indicators. The PyWPS framework will be used. The CLIPC portal will have its own central viewing service, using OGC standards for interoperability. For the WMS server side the ADAGUC framework will be used. For Tier 3 visualizations specific tailored visualisations will be developed. Tier 3 can be complicated to build and require manual work from specialists to provide meaningful results before they can be published as e.g. interactive maps. The CLIPC knowledge base is a set of services that supply explanatory information to the users when working with CLIPC services. It is structured around 1) a catalogue, containing ISO standardized metadata, citations, background information, links to data; 2) Commentary information, e.g. FAQ, annotation URLs , version information, disclaimers; 3) Technical documents, e.g. using vocabularies and mappings 4) Glossaries, adding and using existing glossaries from e.g. EUPORIAS/IS-ENES, IPCC; 5) literature references. CLIPC will have a very light weight user management system, providing as little barriers to the user as possible. We will make use of OpenID, accepting from selected OpenID providers such as Google and ESGF. In the presentation we will show the storyline implementation: the first results of the Tier 3 indicator, the architecture in development and the lessons learned.

Representing Extremes in Agricultural Models

NASA Technical Reports Server (NTRS)

Ruane, Alex

2015-01-01

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

Towards Consistent Aerosol and Cloud Climate Data Records from the Along Track Scanning Radiometer instruments

NASA Astrophysics Data System (ADS)

Thomas, G.

2015-12-01

The ESA Climate Change Initiative (CCI) programme has provided a mechanism for the production of new long-term data records of essential climate variables (ECVs) defined by WMO Global Climate Observing System (GCOS). These include consistent cloud (from the MODIS, AVHRR, ATSR-2 and AATSR instruments) and aerosol (from ATSR-2 and AATSR) products produced using the Optimal Retrieval of Aerosol and Cloud (ORAC) scheme. This talk will present an overview of the newly produced ORAC cloud and aerosol datasets, their evaluation and a joint aerosol-cloud product produced for the 1995-2012 ATSR-2-AATSR data record.

Interactive Ice Sheet Flowline Model for High School and College Students

NASA Astrophysics Data System (ADS)

Stearns, L. A.; Rezvanbehbahani, S.; Shankar, S.

2017-12-01

Teaching about climate and climate change is conceptually challenging. While teaching tools and lesson plans are rapidly evolving to help teachers and students improve their understanding of climate processes, there are very few tools targeting ice sheet and glacier dynamics. We have built an interactive ice sheet model that allows students to explore how Antarctic glaciers respond to different climate perturbations. Interactive models offer advantages that are hard to obtain in traditional classroom settings; users can systematically investigate hypothetical situations, explore the effects of modifying systems, and repeatedly observe how systems interrelate. As a result, this project provides a much-needed bridge between the data and models used by the scientific community and students in high school and college. We target our instructional and assessment activities to three high school and college students with the overall aim of increasing understanding of ice sheet dynamics and the different ways that ice sheets are impacted by climate change, while also improving their fundamental math skills.

Managing living marine resources in a dynamic environment: The role of seasonal to decadal climate forecasts

NASA Astrophysics Data System (ADS)

Tommasi, Desiree; Stock, Charles A.; Hobday, Alistair J.; Methot, Rick; Kaplan, Isaac C.; Eveson, J. Paige; Holsman, Kirstin; Miller, Timothy J.; Gaichas, Sarah; Gehlen, Marion; Pershing, Andrew; Vecchi, Gabriel A.; Msadek, Rym; Delworth, Tom; Eakin, C. Mark; Haltuch, Melissa A.; Séférian, Roland; Spillman, Claire M.; Hartog, Jason R.; Siedlecki, Samantha; Samhouri, Jameal F.; Muhling, Barbara; Asch, Rebecca G.; Pinsky, Malin L.; Saba, Vincent S.; Kapnick, Sarah B.; Gaitan, Carlos F.; Rykaczewski, Ryan R.; Alexander, Michael A.; Xue, Yan; Pegion, Kathleen V.; Lynch, Patrick; Payne, Mark R.; Kristiansen, Trond; Lehodey, Patrick; Werner, Francisco E.

2017-03-01

Recent developments in global dynamical climate prediction systems have allowed for skillful predictions of climate variables relevant to living marine resources (LMRs) at a scale useful to understanding and managing LMRs. Such predictions present opportunities for improved LMR management and industry operations, as well as new research avenues in fisheries science. LMRs respond to climate variability via changes in physiology and behavior. For species and systems where climate-fisheries links are well established, forecasted LMR responses can lead to anticipatory and more effective decisions, benefitting both managers and stakeholders. Here, we provide an overview of climate prediction systems and advances in seasonal to decadal prediction of marine-resource relevant environmental variables. We then describe a range of climate-sensitive LMR decisions that can be taken at lead-times of months to decades, before highlighting a range of pioneering case studies using climate predictions to inform LMR decisions. The success of these case studies suggests that many additional applications are possible. Progress, however, is limited by observational and modeling challenges. Priority developments include strengthening of the mechanistic linkages between climate and marine resource responses, development of LMR models able to explicitly represent such responses, integration of climate driven LMR dynamics in the multi-driver context within which marine resources exist, and improved prediction of ecosystem-relevant variables at the fine regional scales at which most marine resource decisions are made. While there are fundamental limits to predictability, continued advances in these areas have considerable potential to make LMR managers and industry decision more resilient to climate variability and help sustain valuable resources. Concerted dialog between scientists, LMR managers and industry is essential to realizing this potential.

Earth Observing System: Science Objectives and Challenges

NASA Technical Reports Server (NTRS)

King, Michael D.

1998-01-01

The Earth Observing System (EOS) is a space-based observing system comprised of a series of satellite sensors by which scientists can monitor the Earth, a Data and Information System (EOSDIS) enabling researchers worldwide to access the satellite data, and an interdisciplinary science research program to interpret the satellite data. In this presentation I will describe the key areas of scientific uncertainty in understanding climate and global change, and follow that with a description of the EOS goals, objectives, and scientific research elements that comprise the program (instrument science teams and interdisciplinary investigations). Finally, I will describe how scientists and policy makers intend to use EOS data to improve our understanding of key global change uncertainties, such as: (i) clouds and radiation, including fossil fuel and natural emissions of sulfate aerosol and its potential impact on cloud feedback, (ii) man's impact on ozone depletion, with examples of ClO and O3 obtained from the UARS satellite during the Austral Spring, and (iii) volcanic eruptions and their impact on climate, with examples from the eruption of Mt. Pinatubo.

Improving Assimilated Global Data Sets using TMI Rainfall and Columnar Moisture Observations

NASA Technical Reports Server (NTRS)

Hou, Arthur Y.; Zhang, Sara Q.; daSilva, Arlindo M.; Olson, William S.

1999-01-01

A global analysis that optimally combine observations from diverse sources with physical models of atmospheric and land processes can provide a comprehensive description of the climate systems. Currently, such data products contain significant errors in primary hydrological fields such as precipitation and evaporation, especially in the tropics. In this study, we show that assimilating precipitation and total precipitable water (TPW) retrievals derived from the TRMM Microwave Imager (TMI) improves not only the hydrological cycle but also key climate parameters such as clouds, radiation, and the large-scale circulation produced by the Goddard Earth Observing System (GEOS) data assimilation system (DAS). In particular, assimilating TMI rain improves clouds and radiation in areas of active convection, as well as the latent heating distribution and the large-scale motion field in the tropics, while assimilating TMI TPW heating distribution and the large-scale motion field in the tropics, while assimilating TMI TPW retrievals leads to reduced moisture biases and improved radiative fluxes in clear-sky regions. The improved analysis also improves short-range forecasts in the tropics. Ensemble forecasts initialized with the GEOS analysis incorporating TMI rain rates and TPW yield smaller biases in tropical precipitation forecasts beyond 1 day and better 500 hPa geopotential height forecasts up to 5 days. Results of this study demonstrate the potential of using high-quality space-borne rainfall and moisture observations to improve the quality of assimilated global data for climate analysis and weather forecasting applications

An assessment of a North American Multi-Model Ensemble (NMME) based global drought early warning forecast system

NASA Astrophysics Data System (ADS)

Wood, E. F.; Yuan, X.; Sheffield, J.; Pan, M.; Roundy, J.

2013-12-01

One of the key recommendations of the WCRP Global Drought Information System (GDIS) workshop is to develop an experimental real-time global monitoring and prediction system. While great advances has been made in global drought monitoring based on satellite observations and model reanalysis data, global drought forecasting has been stranded in part due to the limited skill both in climate forecast models and global hydrologic predictions. Having been working on drought monitoring and forecasting over USA for more than a decade, the Princeton land surface hydrology group is now developing an experimental global drought early warning system that is based on multiple climate forecast models and a calibrated global hydrologic model. In this presentation, we will test its capability in seasonal forecasting of meteorological, agricultural and hydrologic droughts over global major river basins, using precipitation, soil moisture and streamflow forecasts respectively. Based on the joint probability distribution between observations using Princeton's global drought monitoring system and model hindcasts and real-time forecasts from North American Multi-Model Ensemble (NMME) project, we (i) bias correct the monthly precipitation and temperature forecasts from multiple climate forecast models, (ii) downscale them to a daily time scale, and (iii) use them to drive the calibrated VIC model to produce global drought forecasts at a 1-degree resolution. A parallel run using the ESP forecast method, which is based on resampling historical forcings, is also carried out for comparison. Analysis is being conducted over global major river basins, with multiple drought indices that have different time scales and characteristics. The meteorological drought forecast does not have uncertainty from hydrologic models and can be validated directly against observations - making the validation an 'apples-to-apples' comparison. Preliminary results for the evaluation of meteorological drought onset hindcasts indicate that climate models increase drought detectability over ESP by 31%-81%. However, less than 30% of the global drought onsets can be detected by climate models. The missed drought events are associated with weak ENSO signals and lower potential predictability. Due to the high false alarms from climate models, the reliability is more important than sharpness for a skillful probabilistic drought onset forecast. Validations and skill assessments for agricultural and hydrologic drought forecasts are carried out using soil moisture and streamflow output from the VIC land surface model (LSM) forced by a global forcing data set. Given our previous drought forecasting experiences over USA and Africa, validating the hydrologic drought forecasting is a significant challenge for a global drought early warning system.

Modeling the influence of climate change on watershed systems: Adaptation through targeted practices

NASA Astrophysics Data System (ADS)

Dudula, John; Randhir, Timothy O.

2016-10-01

Climate change may influence hydrologic processes of watersheds (IPCC, 2013) and increased runoff may cause flooding, eroded stream banks, widening of stream channels, increased pollutant loading, and consequently impairment of aquatic life. The goal of this study was to quantify the potential impacts of climate change on watershed hydrologic processes and to evaluate scale and effectiveness of management practices for adaptation. We simulate baseline watershed conditions using the Hydrological Simulation Program Fortran (HSPF) simulation model to examine the possible effects of changing climate on watershed processes. We also simulate the effects of adaptation and mitigation through specific best management strategies for various climatic scenarios. With continuing low-flow conditions and vulnerability to climate change, the Ipswich watershed is the focus of this study. We quantify fluxes in runoff, evapotranspiration, infiltration, sediment load, and nutrient concentrations under baseline and climate change scenarios (near and far future). We model adaptation options for mitigating climate effects on watershed processes using bioretention/raingarden Best Management Practices (BMPs). It was observed that climate change has a significant impact on watershed runoff and carefully designed and maintained BMPs at subwatershed scale can be effective in mitigating some of the problems related to stormwater runoff. Policy options include implementation of BMPs through education and incentives for scale-dependent and site specific bioretention units/raingardens to increase the resilience of the watershed system to current and future climate change.

Climate Change and Agriculture in the U.S.: Effects and Adaptation (Invited)

NASA Astrophysics Data System (ADS)

Walsh, M. K.; Rippey, B.; Walthall, C. L.; Hatfield, J.; Backlund, P. W.; Lengnick, L.; Marshall, E.

2013-12-01

Agriculture in the United States has followed a path of continual adaptation to a wide range of factors throughout its history. However, observational evidence, supported by an understanding of the physical climate system, shows that human-induced climate change is underway in the U.S. and even now causing changes for which there is no historical reference for producers. Temperatures have increased and precipitation patterns have changed; the incidence, frequency, and extent of pest infestations have been altered, as well as the natural resource base (water, air, and soils) upon which production depends. Each factor challenges agricultural management as atmospheric concentrations of greenhouse gases rise. These trends are likely to continue over the next century. Importantly, a gap exists between U.S. agricultural producers and managers' needs related to climate-driven problems and the information that research currently offers them. In the past, agricultural research into climate change effects has largely focused on mean values of precipitation and temperature. Today's management requirements, however, often demand immediate response on shorter time scales to address abrupt, often novel needs. Further complicating this reality, future decisions will likely require even greater emphasis on managing under increasing levels of uncertainty, and planning for and adjusting to the extremes. Research is moving to better address these emerging issues for the relevant timescales and parameters in order to allow the formulation of improved and resilient management strategies that apply to a future in which past experience has become less applicable. A climate-ready U.S. agricultural system requires easy access to useable climate knowledge and technical resources, improved climate risk management strategies, new processes to support effective adaptive actions, and the development of sustainable production systems resilient to climate effects. Mainstreaming climate knowledge improves adaptive capacity of the agricultural system by ensuring that land managers, technical advisors, researchers, private businesspeople, government program managers, and policymakers are aware of current and projected climate impacts and can access best management practices to reduce risks and capture opportunities.

IPCC Climate Change 2013: Impacts, Adaptation and Vulnerability: Key findings and lessons learned

NASA Astrophysics Data System (ADS)

Giorgi, Filippo; Field, Christopher; Barros, Vicente

2014-05-01

The Working Group II contribution to the Fifth Assessment Report of the Intergivernmental Panel on Climate Change, Impacts, Adaptation and Vulnerability, will be completed and approved in March 2014. It includes two parts, Part A covering Global and Sectoral Aspects, and Part B, covering Regional Aspects. The WGII report spans a very broad range of topics which are approached in a strong interdisciplinary context. It highlights how observed impacts of climate change are now widespread and consequential, particularly for natural systems, and can be observed on all continents and across the oceans. Vulnerability to climate change depends on interactions with non-climatic stressors and inequalities, resulting in highly differential risks associated with climate change. It is also found that adaptation is already occurring across scales and is embedded in many planning processes. Continued sustained warming thrughout the 21st century will exacerbate risks and vulnerabilities across multiple sectors, such as freshwater resources, terrestrial and inland water systems, coastal and marine systems, food production, human health, security and livelihood. The report stresses how risks and vulnerabilities need to be assessed within a multi-stressor and regionally specific context, and can be reduced and managed by adopting climate-resilient pathwyas combining suitable adaptation and mitigation options with synergies and tradeoffs occurring both within and across regions. The Working group II report includes a large number of Chapters (30) and contributors (310 including authors and review editors), with expertise in a broad range of disciplines, from the physical science to the impact and socio-economic sciences. The communication across chapters and disciplines has been a challenge, and will continue to be one as the Global Change problem will increasingly require a fully integrated and holistic approach. Note that text on this abstract is not approved at the time its submission, but it will be discussed in the report.

Unraveling multiple changes in complex climate time series using Bayesian inference

NASA Astrophysics Data System (ADS)

Berner, Nadine; Trauth, Martin H.; Holschneider, Matthias

2016-04-01

Change points in time series are perceived as heterogeneities in the statistical or dynamical characteristics of observations. Unraveling such transitions yields essential information for the understanding of the observed system. The precise detection and basic characterization of underlying changes is therefore of particular importance in environmental sciences. We present a kernel-based Bayesian inference approach to investigate direct as well as indirect climate observations for multiple generic transition events. In order to develop a diagnostic approach designed to capture a variety of natural processes, the basic statistical features of central tendency and dispersion are used to locally approximate a complex time series by a generic transition model. A Bayesian inversion approach is developed to robustly infer on the location and the generic patterns of such a transition. To systematically investigate time series for multiple changes occurring at different temporal scales, the Bayesian inversion is extended to a kernel-based inference approach. By introducing basic kernel measures, the kernel inference results are composed into a proxy probability to a posterior distribution of multiple transitions. Thus, based on a generic transition model a probability expression is derived that is capable to indicate multiple changes within a complex time series. We discuss the method's performance by investigating direct and indirect climate observations. The approach is applied to environmental time series (about 100 a), from the weather station in Tuscaloosa, Alabama, and confirms documented instrumentation changes. Moreover, the approach is used to investigate a set of complex terrigenous dust records from the ODP sites 659, 721/722 and 967 interpreted as climate indicators of the African region of the Plio-Pleistocene period (about 5 Ma). The detailed inference unravels multiple transitions underlying the indirect climate observations coinciding with established global climate events.

Observational needs for estimating Alaskan soil carbon stocks under current and future climate

DOE PAGES

Vitharana, U. W. A.; Mishra, U.; Jastrow, J. D.; ...

2017-01-24

Representing land surface spatial heterogeneity when designing observation networks is a critical scientific challenge. Here we present a geospatial approach that utilizes the multivariate spatial heterogeneity of soil-forming factors—namely, climate, topography, land cover types, and surficial geology—to identify observation sites to improve soil organic carbon (SOC) stock estimates across the State of Alaska, USA. Standard deviations in existing SOC samples indicated that 657, 870, and 906 randomly distributed pedons would be required to quantify the average SOC stocks for 0–1 m, 0–2 m, and whole-profile depths, respectively, at a confidence interval of 5 kg C m -2. Using the spatialmore » correlation range of existing SOC samples, we identified that 309, 446, and 484 new observation sites are needed to estimate current SOC stocks to 1 m, 2 m, and whole-profile depths, respectively. We also investigated whether the identified sites might change under future climate by using eight decadal (2020–2099) projections of precipitation, temperature, and length of growing season for three representative concentration pathway (RCP 4.5, 6.0, and 8.5) scenarios of the Intergovernmental Panel on Climate Change. These analyses determined that 12 to 41 additional sites (906 + 12 to 41; depending upon the emission scenarios) would be needed to capture the impact of future climate on Alaskan whole-profile SOC stocks by 2100. The identified observation sites represent spatially distributed locations across Alaska that captures the multivariate heterogeneity of soil-forming factors under current and future climatic conditions. This information is needed for designing monitoring networks and benchmarking of Earth system model results.« less

Observational needs for estimating Alaskan soil carbon stocks under current and future climate

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

Vitharana, U. W. A.; Mishra, U.; Jastrow, J. D.

Representing land surface spatial heterogeneity when designing observation networks is a critical scientific challenge. Here we present a geospatial approach that utilizes the multivariate spatial heterogeneity of soil-forming factors—namely, climate, topography, land cover types, and surficial geology—to identify observation sites to improve soil organic carbon (SOC) stock estimates across the State of Alaska, USA. Standard deviations in existing SOC samples indicated that 657, 870, and 906 randomly distributed pedons would be required to quantify the average SOC stocks for 0–1 m, 0–2 m, and whole-profile depths, respectively, at a confidence interval of 5 kg C m -2. Using the spatialmore » correlation range of existing SOC samples, we identified that 309, 446, and 484 new observation sites are needed to estimate current SOC stocks to 1 m, 2 m, and whole-profile depths, respectively. We also investigated whether the identified sites might change under future climate by using eight decadal (2020–2099) projections of precipitation, temperature, and length of growing season for three representative concentration pathway (RCP 4.5, 6.0, and 8.5) scenarios of the Intergovernmental Panel on Climate Change. These analyses determined that 12 to 41 additional sites (906 + 12 to 41; depending upon the emission scenarios) would be needed to capture the impact of future climate on Alaskan whole-profile SOC stocks by 2100. The identified observation sites represent spatially distributed locations across Alaska that captures the multivariate heterogeneity of soil-forming factors under current and future climatic conditions. This information is needed for designing monitoring networks and benchmarking of Earth system model results.« less

Satellite-derived SIF and CO2 Observations Show Coherent Responses to Interannual Climate Variations

NASA Astrophysics Data System (ADS)

Butterfield, Z.; Hogikyan, A.; Kulawik, S. S.; Keppel-Aleks, G.

2017-12-01

Gross primary production (GPP) is the single largest carbon flux in the Earth system, but its sensitivity to changes in climate is subject to significant uncertainty. Satellite measurements of solar-induced chlorophyll fluorescence (SIF) offer insight into spatial and temporal patterns in GPP at a global scale and, combined with other satellite-derived datasets, provide unprecedented opportunity to explore interactions between atmospheric CO2, GPP, and climate variability. To explore potential drivers of GPP in the Northern Hemisphere (NH), we compare monthly-averaged SIF data from the Global Ozone Monitoring Experiment 2 (GOME-2) with observed anomalies in temperature (T; CRU-TS), liquid water equivalent (LWE) from the Gravity Recovery and Climate Experiment (GRACE), and photosynthetically active radiation (PAR; CERES SYN1deg). Using observations from 2007 through 2015 for several NH regions, we calculate month-specific sensitivities of SIF to variability in T, LWE, and PAR. These sensitivities provide insight into the seasonal progression of how productivity is affected by climate variability and can be used to effectively model the observed SIF signal. In general, we find that high temperatures are beneficial to productivity in the spring, but detrimental in the summer. The influences of PAR and LWE are more heterogeneous between regions; for example, higher LWE in North American temperate forest leads to decreased springtime productivity, while exhibiting a contrasting effect in water-limited regions. Lastly, we assess the influence of variations in terrestrial productivity on atmospheric carbon using a new lower tropospheric CO2 product derived from the Greenhouse Gases Observing Satellite (GOSAT). Together, these data shed light on the drivers of interannual variability in the annual cycle of NH atmospheric CO2, and may provide improved constraints on projections of long-term carbon cycle responses to climate change.

Study of Regional Downscaled Climate and Air Quality in the United States

NASA Astrophysics Data System (ADS)

Gao, Y.; Fu, J. S.; Drake, J.; Lamarque, J.; Lam, Y.; Huang, K.

2011-12-01

Due to the increasing anthropogenic greenhouse gas emissions, the global and regional climate patterns have significantly changed. Climate change has exerted strong impact on ecosystem, air quality and human life. The global model Community Earth System Model (CESM v1.0) was used to predict future climate and chemistry under projected emission scenarios. Two new emission scenarios, Representative Community Pathways (RCP) 4.5 and RCP 8.5, were used in this study for climate and chemistry simulations. The projected global mean temperature will increase 1.2 and 1.7 degree Celcius for the RCP 4.5 and RCP 8.5 scenarios in 2050s, respectively. In order to take advantage of local detailed topography, land use data and conduct local climate impact on air quality, we downscaled CESM outputs to 4 km by 4 km Eastern US domain using Weather Research and Forecasting (WRF) Model and Community Multi-scale Air Quality modeling system (CMAQ). The evaluations between regional model outputs and global model outputs, regional model outputs and observational data were conducted to verify the downscaled methodology. Future climate change and air quality impact were also examined on a 4 km by 4 km high resolution scale.

Climate changes impact the surface albedo of a forest ecosystem based on MODIS satellite data

NASA Astrophysics Data System (ADS)

Zoran, M. A.; Nemuc, A. V.

2007-10-01

Surface albedo is one of the most important biophysical parameter responsible for energy balance control and the surface temperature and boundary-layer structure of the atmosphere. Forest land surface albedo is also highly variable temporally showing both diurnal as well as seasonal variations. In forest systems, albedo controls the microclimate conditions which affects ecosystem physical, physiological, and biogeochemical processes such as energy balance, evapotranspiration, photosynthesis. Due to anthropogenic and natural factors, land cover and land use changes result is the land surfaces albedo change. The main aim of this paper is to investigate the albedo patterns due to the impact of atmospheric pollution and climate variations of a forest ecosystem Branesti-Cernica, placed to the North-East of Bucharest city, Romania based on satellite Landsat ETM+, IKONOS and MODIS data and climate station observations. Our study focuses on 3 years of data (2003-2005), each of which had a different climatic regime. As the physical climate system is very sensitive to surface albedo, forest ecosystems could significantly feedback to the projected climate change modeling scenarios through albedo changes. The results of this research have a number of applications in weather forecasting, climate change, and forest ecosystem studies.

A Climate Benchmark of Upper Air Temperature Observations from GNSS Radio Occultation

NASA Astrophysics Data System (ADS)

Ao, C. O.; Mannucci, A. J.; Leroy, S. S.; Verkhoglyadova, O. P.

2017-12-01

GPS (Global Positioning System), or more generally Global Navigation Satellite System (GNSS), radio occultation (RO) is a remote sensing technique that produces highly accurate temperature in the upper troposphere and lower stratosphere across the globe with fine vertical resolution. Its fundamental measurement is the time delay of the microwave signal as it travels from a GNSS satellite to the receiver in low Earth orbit. With a relatively simple physical retrieval, the uncertainty in the derived temperature can be traced rigorously through the retrieval chain back to the raw measurements. The high absolute accuracy of RO allows these observations to be assimilated without bias correction in numerical weather prediction models and provides an anchor for assimilating other types of observations. The high accuracy, coupled with long-term stability, makes RO valuable in detecting decadal temperature trends. In this presentation, we will summarize the current state of RO observations and show temperature trends derived from 15 years of RO data in the upper troposphere and lower stratosphere. We will discuss our recent efforts in developing retrieval algorithms that are more tailored towards climate applications. Despite the relatively robust "self-calibrating" nature of RO observations, disparity in receiver hardware and software may introduce subtle differences that need to be carefully addressed. While the historic RO data record came from relatively homogeneous hardware based largely on NASA/JPL design (e.g., CHAMP and COSMIC), the future data will likely be comprised of a diverse set of observations from Europe, China, and various commercial data providers. In addition, the use of non-GPS navigation systems will become more prevalent. We will discuss the challenges involved in establishing a long-term RO climate data record from a suite of research and operational weather satellites with changes in instrumentation and coverage.

Advancing land surface model development with satellite-based Earth observations

NASA Astrophysics Data System (ADS)

Orth, Rene; Dutra, Emanuel; Trigo, Isabel F.; Balsamo, Gianpaolo

2017-04-01

The land surface forms an essential part of the climate system. It interacts with the atmosphere through the exchange of water and energy and hence influences weather and climate, as well as their predictability. Correspondingly, the land surface model (LSM) is an essential part of any weather forecasting system. LSMs rely on partly poorly constrained parameters, due to sparse land surface observations. With the use of newly available land surface temperature observations, we show in this study that novel satellite-derived datasets help to improve LSM configuration, and hence can contribute to improved weather predictability. We use the Hydrology Tiled ECMWF Scheme of Surface Exchanges over Land (HTESSEL) and validate it comprehensively against an array of Earth observation reference datasets, including the new land surface temperature product. This reveals satisfactory model performance in terms of hydrology, but poor performance in terms of land surface temperature. This is due to inconsistencies of process representations in the model as identified from an analysis of perturbed parameter simulations. We show that HTESSEL can be more robustly calibrated with multiple instead of single reference datasets as this mitigates the impact of the structural inconsistencies. Finally, performing coupled global weather forecasts we find that a more robust calibration of HTESSEL also contributes to improved weather forecast skills. In summary, new satellite-based Earth observations are shown to enhance the multi-dataset calibration of LSMs, thereby improving the representation of insufficiently captured processes, advancing weather predictability and understanding of climate system feedbacks. Orth, R., E. Dutra, I. F. Trigo, and G. Balsamo (2016): Advancing land surface model development with satellite-based Earth observations. Hydrol. Earth Syst. Sci. Discuss., doi:10.5194/hess-2016-628

Interpretation of Recent Temperature Trends in California

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

Duffy, P B; Bonfils, C; Lobell, D

2007-09-21

Regional-scale climate change and associated societal impacts result from large-scale (e.g. well-mixed greenhouse gases) and more local (e.g. land-use change) 'forcing' (perturbing) agents. It is essential to understand these forcings and climate responses to them, in order to predict future climate and societal impacts. California is a fine example of the complex effects of multiple climate forcings. The State's natural climate is diverse, highly variable, and strongly influenced by ENSO. Humans are perturbing this complex system through urbanization, irrigation, and emission of multiple types of aerosols and greenhouse gases. Despite better-than-average observational coverage, we are only beginning to understand themore » manifestations of these forcings in California's temperature record.« less

Human-Induced Climate Variations Linked to Urbanization: From Observations to Modeling

NASA Technical Reports Server (NTRS)

Shepherd, J. Marshall; Jin, Menglin

2004-01-01

The goal of this session is to bring together scientists from interdisciplinary backgrounds to discuss the data, scientific approaches and recent results focusing on the impact of urbanization on the climate. The discussion will highlight current observational and modeling capabilities being employed for investigating the urban environment and its linkage to the change in the Earth's climate system. The goal of the session is to identify our current stand and the future direction on the topic. Urbanization is one of the extreme cases of land use change. Most of population of the world has moved to urban areas. By 1995, more than 70% of population of North America and Europe were living in cities. By 2025, the United Nations estimates that 60% of the worlds population will live in cities. Although currently only 1.2% of the land is urban, better understanding of how the atmosphere-ocean-land-biosphere components interact as a coupled system and the influence of human activities on this system is critical. Our understanding of urbanization effect is incomplete, partly because human activities induce new changes on climate in addition to the original natural variations, and partly because previously few data available for study urban effect globally. Urban construction changes surface roughness, albedo, heat capacity and vegetation coverage. Traffic and industry increase atmospheric aerosol. It is suggested that urbanization may modify rainfall processes through aerosol-cloud interactions or dynamic feedbacks. Because urbanization effect on climate is determined by many factors including land cover, the city's microscale features, population density, and human lifestyle patterns, it is necessary to study urban areas over globe.

The origin of climate changes.

PubMed

Delecluse, P

2008-08-01

Investigation on climate change is coordinated by the Intergovernmental Panel on Climate Change (IPCC), which has the delicate task of collecting recent knowledge on climate change and the related impacts of the observed changes, and then developing a consensus statement from these findings. The IPCC's last review, published at the end of 2007, summarised major findings on the present climate situation. The observations show a clear increase in the temperature of the Earth's surface and the oceans, a reduction in the land snow cover, and melting of the sea ice and glaciers. Numerical modelling combined with statistical analysis has shown that this warming trend is very likely the signature of increasing emissions of greenhouse gases linked with human activities. Given the continuing social and economic development around the world, the IPCC emission scenarios forecast an increasing greenhouse effect, at least until 2050 according to the most optimistic models. The model ensemble predicts a rising temperature that will reach dangerous levels for the biosphere and ecosystems within this century. Hydrological systems and the potential significant impacts of these systems on the environment are also discussed. Facing this challenging future, societies must take measures to reduce emissions and work on adapting to an inexorably changing environment. Present knowledge is sufficientto start taking action, but a stronger foundation is needed to ensure that pertinent long-term choices are made that will meet the demands of an interactive and rapidly evolving world.

Future Flight Opportunities and Calibration Protocols for CERES: Continuation of Observations in Support of the Long-Term Earth Radiation Budget Climate Data Record

NASA Technical Reports Server (NTRS)

Priestley, Kory J.; Smith, George L.

2010-01-01

The goal of the Clouds and the Earth s Radiant Energy System (CERES) project is to provide a long-term record of radiation budget at the top-of-atmosphere (TOA), within the atmosphere, and at the surface with consistent cloud and aerosol properties at climate accuracy. CERES consists of an integrated instrument-algorithm validation science team that provides development of higher-level products (Levels 1-3) and investigations. It involves a high level of data fusion, merging inputs from 25 unique input data sources to produce 18 CERES data products. Over 90% of the CERES data product volume involves two or more instruments. Continuation of the Earth Radiation Budget (ERB) Climate Data Record (CDR) has been identified as critical in the 2007 NRC Decadal Survey, the Global Climate Observing System WCRP report, and in an assessment titled Impacts of NPOESS Nunn-McCurdy Certification on Joint NASA-NOAA Climate Goals . Five CERES instruments have flown on three different spacecraft: TRMM, EOS-Terra and EOS-Aqua. In response, NASA, NOAA and NPOESS have agreed to fly the existing CERES Flight Model (FM-5) on the NPP spacecraft in 2011 and to procure an additional CERES Sensor with modest upgrades for flight on the JPSS C1 spacecraft in 2014, followed by a CERES follow-on sensor for flight in 2018. CERES is a scanning broadband radiometer that measures filtered radiance in the SW (0.3-5 m), total (TOT) (0.3-200 m) and WN (8-12 m) regions. Pre-launch calibration is performed on each Flight Model to meet accuracy requirements of 1% for SW and 0.5% for outgoing LW observations. Ground to flight or in-flight changes are monitored using protocols employing onboard and vicarious calibration sources. Studies of flight data show that SW response can change dramatically due to optical contamination. with greatest impact in blue-to UV radiance, where tungsten lamps are largely devoid of output. While science goals remain unchanged for ERB Climate Data Record, it is now understood that achieving these goals is more difficult for two reasons. The first is an increased understanding of the dynamics of the Earth/atmosphere system which demonstrates that separation of natural variability from anthropogenic change on decadal time scales requires observations with higher accuracy and stabilit

A Functional Response Metric for the Temperature Sensitivity of Tropical Ecosystems

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

Keppel-Aleks, Gretchen; Basile, Samantha J.; Hoffman, Forrest M.

Earth system models (ESMs) simulate a large spread in carbon cycle feedbacks to climate change, particularly in their prediction of cumulative changes in terrestrial carbon storage. Evaluating the performance of ESMs against observations and assessing the likelihood of long-term climate predictions are crucial for model development. Here, we assessed the use of atmospheric CO 2 growth rate variations to evaluate the sensitivity of tropical ecosystem carbon fluxes to interannual temperature variations. We found that the temperature sensitivity of the observed CO 2 growth rate depended on the time scales over which atmospheric CO 2 observations were averaged. The temperature sensitivitymore » of the CO 2 growth rate during Northern Hemisphere winter is most directly related to the tropical carbon flux sensitivity since winter variations in Northern Hemisphere carbon fluxes are relatively small. This metric can be used to test the fidelity of interactions between the physical climate system and terrestrial ecosystems within ESMs, which is especially important since the short-term relationship between ecosystem fluxes and temperature stress may be related to the long-term feedbacks between ecosystems and climate. If the interannual temperature sensitivity is used to constrain long-term temperature responses, the inferred sensitivity may be biased by 20%, unless the seasonality of the relationship between the observed CO 2 growth rate and tropical fluxes is taken into account. Lastly, these results suggest that atmospheric data can be used directly to evaluate regional land fluxes from ESMs, but underscore that the interaction between the time scales for land surface processes and those for atmospheric processes must be considered.« less

A Functional Response Metric for the Temperature Sensitivity of Tropical Ecosystems

DOE PAGES

Keppel-Aleks, Gretchen; Basile, Samantha J.; Hoffman, Forrest M.

2018-04-23

Earth system models (ESMs) simulate a large spread in carbon cycle feedbacks to climate change, particularly in their prediction of cumulative changes in terrestrial carbon storage. Evaluating the performance of ESMs against observations and assessing the likelihood of long-term climate predictions are crucial for model development. Here, we assessed the use of atmospheric CO 2 growth rate variations to evaluate the sensitivity of tropical ecosystem carbon fluxes to interannual temperature variations. We found that the temperature sensitivity of the observed CO 2 growth rate depended on the time scales over which atmospheric CO 2 observations were averaged. The temperature sensitivitymore » of the CO 2 growth rate during Northern Hemisphere winter is most directly related to the tropical carbon flux sensitivity since winter variations in Northern Hemisphere carbon fluxes are relatively small. This metric can be used to test the fidelity of interactions between the physical climate system and terrestrial ecosystems within ESMs, which is especially important since the short-term relationship between ecosystem fluxes and temperature stress may be related to the long-term feedbacks between ecosystems and climate. If the interannual temperature sensitivity is used to constrain long-term temperature responses, the inferred sensitivity may be biased by 20%, unless the seasonality of the relationship between the observed CO 2 growth rate and tropical fluxes is taken into account. Lastly, these results suggest that atmospheric data can be used directly to evaluate regional land fluxes from ESMs, but underscore that the interaction between the time scales for land surface processes and those for atmospheric processes must be considered.« less

The Deep South Clouds & Aerosols project: Improving the modelling of clouds in the Southern Ocean region

NASA Astrophysics Data System (ADS)

Morgenstern, Olaf; McDonald, Adrian; Harvey, Mike; Davies, Roger; Katurji, Marwan; Varma, Vidya; Williams, Jonny

2016-04-01

Southern-Hemisphere climate projections are subject to persistent climate model biases affecting the large majority of contemporary climate models, which degrade the reliability of these projections, particularly at the regional scale. Southern-Hemisphere specific problems include the fact that satellite-based observations comparisons with model output indicate that cloud occurrence above the Southern Ocean is substantially underestimated, with consequences for the radiation balance, sea surface temperatures, sea ice, and the position of storm tracks. The Southern-Ocean and Antarctic region is generally characterized by an acute paucity of surface-based and airborne observations, further complicating the situation. In recognition of this and other Southern-Hemisphere specific problems with climate modelling, the New Zealand Government has launched the Deep South National Science Challenge, whose purpose is to develop a new Earth System Model which reduces these very large radiative forcing problems associated with erroneous clouds. The plan is to conduct a campaign of targeted observations in the Southern Ocean region, leveraging off international measurement campaigns in this area, and using these and existing measurements of cloud and aerosol properties to improve the representation of clouds in the nascent New Zealand Earth System Model. Observations and model development will target aerosol physics and chemistry, particularly sulphate, sea salt, and non-sulphate organic aerosol, its interactions with clouds, and cloud microphysics. The hypothesis is that the cloud schemes in most GCMs are trained on Northern-Hemisphere data characterized by substantial anthropogenic or terrestrial aerosol-related influences which are almost completely absent in the Deep South.

A simple object-oriented and open-source model for scientific and policy analyses of the global climate system – Hector v1.0

DOE PAGES

Hartin, Corinne A.; Patel, Pralit L.; Schwarber, Adria; ...

2015-04-01

Simple climate models play an integral role in the policy and scientific communities. They are used for climate mitigation scenarios within integrated assessment models, complex climate model emulation, and uncertainty analyses. Here we describe Hector v1.0, an open source, object-oriented, simple global climate carbon-cycle model. This model runs essentially instantaneously while still representing the most critical global-scale earth system processes. Hector has a three-part main carbon cycle: a one-pool atmosphere, land, and ocean. The model's terrestrial carbon cycle includes primary production and respiration fluxes, accommodating arbitrary geographic divisions into, e.g., ecological biomes or political units. Hector actively solves the inorganicmore » carbon system in the surface ocean, directly calculating air–sea fluxes of carbon and ocean pH. Hector reproduces the global historical trends of atmospheric [CO 2], radiative forcing, and surface temperatures. The model simulates all four Representative Concentration Pathways (RCPs) with equivalent rates of change of key variables over time compared to current observations, MAGICC (a well-known simple climate model), and models from the 5th Coupled Model Intercomparison Project. Hector's flexibility, open-source nature, and modular design will facilitate a broad range of research in various areas.« less

Comparison of different synthetic 5-min rainfall time series on the results of rainfall runoff simulations in urban drainage modelling

NASA Astrophysics Data System (ADS)

Krämer, Stefan; Rohde, Sophia; Schröder, Kai; Belli, Aslan; Maßmann, Stefanie; Schönfeld, Martin; Henkel, Erik; Fuchs, Lothar

2015-04-01

The design of urban drainage systems with numerical simulation models requires long, continuous rainfall time series with high temporal resolution. However, suitable observed time series are rare. As a result, usual design concepts often use uncertain or unsuitable rainfall data, which renders them uneconomic or unsustainable. An expedient alternative to observed data is the use of long, synthetic rainfall time series as input for the simulation models. Within the project SYNOPSE, several different methods to generate synthetic rainfall data as input for urban drainage modelling are advanced, tested, and compared. Synthetic rainfall time series of three different precipitation model approaches, - one parametric stochastic model (alternating renewal approach), one non-parametric stochastic model (resampling approach), one downscaling approach from a regional climate model-, are provided for three catchments with different sewer system characteristics in different climate regions in Germany: - Hamburg (northern Germany): maritime climate, mean annual rainfall: 770 mm; combined sewer system length: 1.729 km (City center of Hamburg), storm water sewer system length (Hamburg Harburg): 168 km - Brunswick (Lower Saxony, northern Germany): transitional climate from maritime to continental, mean annual rainfall: 618 mm; sewer system length: 278 km, connected impervious area: 379 ha, height difference: 27 m - Friburg in Brisgau (southern Germany): Central European transitional climate, mean annual rainfall: 908 mm; sewer system length: 794 km, connected impervious area: 1 546 ha, height difference 284 m Hydrodynamic models are set up for each catchment to simulate rainfall runoff processes in the sewer systems. Long term event time series are extracted from the - three different synthetic rainfall time series (comprising up to 600 years continuous rainfall) provided for each catchment and - observed gauge rainfall (reference rainfall) according national hydraulic design standards. The synthetic and reference long term event time series are used as rainfall input for the hydrodynamic sewer models. For comparison of the synthetic rainfall time series against the reference rainfall and against each other the number of - surcharged manholes, - surcharges per manhole, - and the average surcharge volume per manhole are applied as hydraulic performance criteria. The results are discussed and assessed to answer the following questions: - Are the synthetic rainfall approaches suitable to generate high resolution rainfall series and do they produce, - in combination with numerical rainfall runoff models - valid results for design of urban drainage systems? - What are the bounds of uncertainty in the runoff results depending on the synthetic rainfall model and on the climate region? The work is carried out within the SYNOPSE project, funded by the German Federal Ministry of Education and Research (BMBF).

Utility of High Temporal Resolution Observations for Heat Health Event Characterization

NASA Astrophysics Data System (ADS)

Palecki, M. A.

2017-12-01

Many heat health watch systems produce a binary on/off warning when conditions are predicted to exceed a given threshold during a day. Days with warnings and their mortality/morbidity statistics are analyzed relative to days not warned to determine the impacts of the event on human health, the effectiveness of warnings, and other statistics. The climate analyses of the heat waves or extreme temperature events are often performed with hourly or daily observations of air temperature, humidity, and other measured or derived variables, especially the maxima and minima of these data. However, since the beginning of the century, 5-minute observations are readily available for many weather and climate stations in the United States. NOAA National Centers for Environmental Information (NCEI) has been collecting 5-minute observations from the NOAA Automated Surface Observing System (ASOS) stations since 2000, and from the U.S. Climate Reference Network (USCRN) stations since 2005. This presentation will demonstrate the efficacy of utilizing 5-minute environmental observations to characterize heat waves by counting the length of time conditions exceed extreme thresholds based on individual and multiple variables and on derived variables such as the heat index. The length and depth of recovery periods between daytime heating periods will also be examined. The length of time under extreme conditions will influence health outcomes for those directly exposed. Longer periods of dangerous conditions also could increase the chances for poor health outcomes for those only exposed intermittently through cumulative impacts.

Virtual Observation System for Earth System Model: An Application to ACME Land Model Simulations

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

Wang, Dali; Yuan, Fengming; Hernandez, Benjamin

Investigating and evaluating physical-chemical-biological processes within an Earth system model (EMS) can be very challenging due to the complexity of both model design and software implementation. A virtual observation system (VOS) is presented to enable interactive observation of these processes during system simulation. Based on advance computing technologies, such as compiler-based software analysis, automatic code instrumentation, and high-performance data transport, the VOS provides run-time observation capability, in-situ data analytics for Earth system model simulation, model behavior adjustment opportunities through simulation steering. A VOS for a terrestrial land model simulation within the Accelerated Climate Modeling for Energy model is also presentedmore » to demonstrate the implementation details and system innovations.« less

Virtual Observation System for Earth System Model: An Application to ACME Land Model Simulations

DOE PAGES

Wang, Dali; Yuan, Fengming; Hernandez, Benjamin; ...

2017-01-01

Investigating and evaluating physical-chemical-biological processes within an Earth system model (EMS) can be very challenging due to the complexity of both model design and software implementation. A virtual observation system (VOS) is presented to enable interactive observation of these processes during system simulation. Based on advance computing technologies, such as compiler-based software analysis, automatic code instrumentation, and high-performance data transport, the VOS provides run-time observation capability, in-situ data analytics for Earth system model simulation, model behavior adjustment opportunities through simulation steering. A VOS for a terrestrial land model simulation within the Accelerated Climate Modeling for Energy model is also presentedmore » to demonstrate the implementation details and system innovations.« less

2016 International Land Model Benchmarking (ILAMB) Workshop Report

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

Hoffman, Forrest M.; Koven, Charles D.; Keppel-Aleks, Gretchen

As Earth system models become increasingly complex, there is a growing need for comprehensive and multi-faceted evaluation of model projections. To advance understanding of biogeochemical processes and their interactions with hydrology and climate under conditions of increasing atmospheric carbon dioxide, new analysis methods are required that use observations to constrain model predictions, inform model development, and identify needed measurements and field experiments. Better representations of biogeochemistry–climate feedbacks and ecosystem processes in these models are essential for reducing uncertainties associated with projections of climate change during the remainder of the 21st century.

An adaptation strategy of sandland peasants in Yogyakarta toward climate change

NASA Astrophysics Data System (ADS)

Rusdiyana, E.; Suminah

2018-03-01

This study aims to explore and describe the adaptation strategies of sandland peasants toward climate change. Qualitative research method was employed and the data were collected through observation. In addition, the recording of the data, interview and the validity of data were determined by triangulation of sources. The results of the research showed that the adaptation strategies of sandland peasants toward climate change were; (1) the adjustment of crop varieties, (2) the utilization of productive crops as wind breaking, and (3) the irrigation system using “sumur panthek”.

An Overview of the Future Development of Climate and Earth System Models for Scientific and Policy Use (Invited)

NASA Astrophysics Data System (ADS)

Washington, W. M.

2010-12-01

The development of climate and earth system models has been regarded primarily as the making of scientific tools to study the complex nature of the Earth’s climate. These models have a long history starting with very simple physical models based on fundamental physics in the 1960s and over time they have become much more complex with atmospheric, ocean, sea ice, land/vegetation, biogeochemical, glacial and ecological components. The policy use aspects of these models did not start in the 1960s and 1970s as decision making tools but were used to answer fundamental scientific questions such as what happens when the atmospheric carbon dioxide concentration increases or is doubled. They gave insights into the various interactions and were extensively compared with observations. It was realized that models of the earlier time periods could only give first order answers to many of the fundamental policy questions. As societal concerns about climate change rose, the policy questions of anthropogenic climate change became better defined; they were mostly concerned with the climate impacts of increasing greenhouse gases, aerosols, and land cover change. In the late 1980s, the United Nations set up the Intergovernmental Panel on Climate Change to perform assessments of the published literature. Thus, the development of climate and Earth system models became intimately linked to the need to not only improve our scientific understanding but also answering fundamental policy questions. In order to meet this challenge, the models became more complex and realistic so that they could address these policy oriented science questions such as rising sea level. The presentation will discuss the past and future development of global climate and earth system models for science and policy purposes. Also to be discussed is their interactions with economic integrated assessment models, regional and specialized models such as river transport or ecological components. As an example of one development pathway, the NSF/Department of Energy supported Community Climate System and Earth System Models will be featured in the presentation. Computational challenges will also part of the discussion.

Interactions of Vegetation and Climate: Remote Observations, Earth System Models, and the Amazon Forest

NASA Astrophysics Data System (ADS)

Quetin, Gregory R.

The natural composition of terrestrial ecosystems can be shaped by climate to take advantage of local environmental conditions. Ecosystem functioning, e.g. interaction between photosynthesis and temperature, can also acclimate to different climatological states. The combination of these two factors thus determines ecological-climate interactions. The ecosystem functioning also plays a key role in predicting the carbon cycle, hydrological cycle, terrestrial surface energy balance, and the feedbacks in the climate system. Predicting the response of the Earth's biosphere to global warming requires the ability to mechanistically represent the processes controlling ecosystem functioning through photosynthesis, respiration, and water use. The physical environment in a place shapes the vegetation there, but vegetation also has the potential to shape the environment, e.g. increased photosynthesis and transpiration moisten the atmosphere. These two-way ecoclimate interactions create the potential for feedbacks between vegetation at the physical environment that depend on the vegetation and the climate of a place, and can change throughout the year. In Chapter 1, we derive a global empirical map of the sensitivity of vegetation to climate using the response of satellite-observed greenness to interannual variations in temperature and precipitation. We infer mechanisms constraining ecosystem functioning by analyzing how the sensitivity of vegetation to climate varies across climate space. Our analysis yields empirical evidence for multiple physical and biological mediators of the sensitivity of vegetation to climate at large spatial scales. In hot and wet locations, vegetation is greener in warmer years despite temperatures likely exceeding thermally optimum conditions. However, sunlight generally increases during warmer years, suggesting that the increased stress from higher atmospheric water demand is offset by higher rates of photosynthesis. The sensitivity of vegetation transitions in sign (greener when warmer or drier to greener when cooler or wetter) along an emergent line in climate space with a slope of about 59 mm/yr/°C, twice as steep as contours of aridity. The mismatch between these slopes is evidence at a global scale of the limitation of both water supply due to inefficiencies in plant access to rainfall, and plant physiological responses to atmospheric water demand. This empirical pattern can provide a functional constraint for process-based models, helping to improve predictions of the global-scale response of vegetation to a changing climate. In Chapter 2, we use observations of vegetation interaction with the physical environment to identify where ecosystem functioning is well simulated in an ensemble of Earth system models. We leverage this data-model comparison to hypothesize which physiological mechanisms--photosynthetic efficiency, respiration, water supply, atmospheric water demand, and sunlight availability--dominate the ecosystem response in places with different climates. The models are generally successful in reproducing the broad sign and shape of ecosystem function across climate space except for simulating generally lower leaf area during warmer years in places with hot wet climates. In addition, simulated ecosystem interaction with temperature is generally larger and changes more rapidly across a gradient of temperature than is observed. We hypothesize that the amplified interaction and change are both due to a lack of adaptation and acclimation in simulations. This discrepancy with observations suggests that simulated responses of vegetation to global warming, and feedbacks between vegetation and climate, are too strong in the models. Finally, models and observations share an abrupt threshold between dry regions and wet regions where strong positive vegetation response to precipitation falls to nearly zero in places receiving around 1000 mm/year. In Chapter 3, we investigate how ecoclimate interactions change across seasons in the Amazon basin. We use observations of solar induced fluorescence from the Orbiting Carbon Observatory 2 (OCO2) to statistically analyze the sensitivity of fluorescence to synoptic variations in temperature and precipitation. In addition to studying the sensitivity of vegetation to climate across seasons, we use OCO2 measurements of total column water vapor (TCWV) and CO2 concentration (XCO2) to investigate the influence of the Amazon basin vegetation on the CO2 concentration and water vapor of the atmosphere leaving the basin. Our analysis determines the seasonal importance of vegetation activity on the outflow of CO2 from the Amazon basin, while providing evidence that transpiration is primarily driven by variations in temperature during the dry season, rather than photosynthesis. We establish a statistical relationship between fluorescence (as a proxy for vegetation photosynthesis), temperature, and precipitation, as well as the difference between the outflow of atmospheric water vapor from the inflow water vapor, basin fluorescence, temperature, and precipitation.

Using Copernicus earth observation services to monitor climate change impacts and adaptations

NASA Astrophysics Data System (ADS)

Becker, Daniel; Zebisch, Marc; Sonnenschein, Ruth; Schönthaler, Konstanze; von Andrian-Werburg, Stefan

2016-04-01

In the last years, earth observation made a big leap towards an operational monitoring of the state of environment. Remote sensing provides for instance information on the dynamics, trends and anomalies of snow and glaciers, vegetation, soil moisture or water temperature. In particular, the European Copernicus initiative offers new opportunities through new satellites with a higher temporal and spatial resolution, operational services for environmental monitoring and an open data access policy. With the Copernicus climate change service and the ESA climate change initiative, specific earth observation programs are in place to address the impacts of climate change. However, such products and services are until now rarely picked up in the field of policy or decision making oriented climate impact or climate risk assessments. In this talk, we will present results of a study, which focus on the question, if and how remote sensing approaches could be integrated into operational monitoring activities of climate impacts and response measures on a national and subnational scale. We assessed all existing and planned Copernicus services regarding their relevance for climate impact monitoring by comparing them against the indication fields from an indicator system for climate impact and response monitoring in Germany, which has lately been developed in the framework of the German national adaptation strategy. For several climate impact or response indicators, an immediate integration of remote sensing data could be identified and been recommended. For these cases, we will show practical examples on the benefit of remote sensing data. For other indication fields, promising approaches were found, which need further development. We argue that remote sensing is a very valuable complement to the existing indicator schemes by contributing with spatial explicit, timely information but not always easy to integrate with classical approaches, which are oriented towards consistent long term monitoring. Furthermore, we provide specific recommendations for the Copernicus services to ensure a consistent climate change monitoring in future and we indicate options and limitations for integrating service products into practical assessment and monitoring activities.

Recovery Migration After Hurricanes Katrina and Rita: Spatial Concentration and Intensification in the Migration System.

PubMed

Curtis, Katherine J; Fussell, Elizabeth; DeWaard, Jack

2015-08-01

Changes in the human migration systems of the Gulf of Mexico coastline counties affected by Hurricanes Katrina and Rita provide an example of how climate change may affect coastal populations. Crude climate change models predict a mass migration of "climate refugees," but an emerging literature on environmental migration suggests that most migration will be short-distance and short-duration within existing migration systems, with implications for the population recovery of disaster-stricken places. In this research, we derive a series of hypotheses on recovery migration predicting how the migration system of hurricane-affected coastline counties in the Gulf of Mexico was likely to have changed between the pre-disaster and the recovery periods. We test these hypotheses using data from the Internal Revenue Service on annual county-level migration flows, comparing the recovery period migration system (2007-2009) with the pre-disaster period (1999-2004). By observing county-to-county ties and flows, we find that recovery migration was strong: the migration system of the disaster-affected coastline counties became more spatially concentrated, while flows within it intensified and became more urbanized. Our analysis demonstrates how migration systems are likely to be affected by the more intense and frequent storms anticipated by climate change scenarios, with implications for the population recovery of disaster-affected places.

High sensitivity of Indian summer monsoon to Middle East dust absorptive properties.

PubMed

Jin, Qinjian; Yang, Zong-Liang; Wei, Jiangfeng

2016-07-28

The absorptive properties of dust aerosols largely determine the magnitude of their radiative impacts on the climate system. Currently, climate models use globally constant values of dust imaginary refractive index (IRI), a parameter describing the dust absorption efficiency of solar radiation, although it is highly variable. Here we show with model experiments that the dust-induced Indian summer monsoon (ISM) rainfall differences (with dust minus without dust) change from -9% to 23% of long-term climatology as the dust IRI is changed from zero to the highest values used in the current literature. A comparison of the model results with surface observations, satellite retrievals, and reanalysis data sets indicates that the dust IRI values used in most current climate models are too low, tending to significantly underestimate dust radiative impacts on the ISM system. This study highlights the necessity for developing a parameterization of dust IRI for climate studies.

Near real time/low latency data collection for climate warming manipulations and an elevated CO2 SPRUCE experiment

NASA Astrophysics Data System (ADS)

Krassovski, M.; Hanson, P. J.; Riggs, J. S.; Nettles, W. R., IV

2017-12-01

Climate change studies are one of the most important aspects of modern science and related experiments are getting bigger and more complex. One such experiment is the Spruce and Peatland Responses Under Climatic and Environmental Change experiment (SPRUCE, http://mnspruce.ornl.gov) conducted in in northern Minnesota, 40 km north of Grand Rapids, in the USDA Forest Service Marcell Experimental Forest (MEF). The SPRUCE experimental mission is to assess ecosystem-level biological responses of vulnerable, high carbon terrestrial ecosystems to a range of climate warming manipulations and an elevated CO2 atmosphere. This manipulation experiment generates a lot of observational data and requires a reliable onsite data collection system, dependable methods to transfer data to a robust scientific facility, and real-time monitoring capabilities. This presentation shares our experience of establishing near real time/low latency data collection and monitoring system using satellite communication.

Aerosol-Cloud Interactions in the South-East Atlantic: Knowledge Gaps, Planned Observations to Address Them, and Implications for Global Climate Change Modeling

NASA Technical Reports Server (NTRS)

Redemann, Jens; Wood, R.; Zuidema, P.; Haywood, J.; Luna, B.; Abel, S.

2015-01-01

Southern Africa produces almost a third of the Earth's biomass burning (BB) aerosol particles, yet the fate of these particles and their influence on regional and global climate is poorly understood. Particles lofted into the mid-troposphere are transported westward over the South-East (SE) Atlantic, home to one of the three permanent subtropical Stratocumulus (Sc) cloud decks in the world. The stratocumulus "climate radiators" are critical to the regional and global climate system. They interact with dense layers of BB aerosols that initially overlay the cloud deck, but later subside and are mixed into the clouds. These interactions include adjustments to aerosol-induced solar heating and microphysical effects. As emphasized in the latest IPCC report, the global representation of these aerosol-cloud interaction processes in climate models is one of the largest uncertainty in estimates of future climate. Hence, new observations over the SE Atlantic have significant implications for global climate change scenarios. We discuss the current knowledge of aerosol and cloud property distributions based on satellite observations and sparse suborbital sampling, and describe planned field campaigns in the region. Specifically, we describe the scientific objectives and implementation of the following four synergistic, international research activities aimed at providing a process-level understanding of aerosol-cloud interactions over the SE Atlantic: 1) ORACLES (Observations of Aerosols above Clouds and their interactions), a five-year investigation between 2015 and 2019 with three Intensive Observation Periods (IOP), recently funded by the NASA Earth-Venture Suborbital Program, 2) CLARIFY-2016 (Cloud-Aerosol-Radiation Interactions and Forcing: Year 2016), a comprehensive observational and modeling programme funded by the UK's Natural Environment Research Council (NERC), and supported by the UK Met Office. 3) LASIC (Layered Atlantic Smoke Interactions with Clouds), a funded deployment of the DOE (Department of Energy) ARM Mobile Facility (AMF1) to Ascension Island, nominally for April 1 2016 - March 31 2017, and 4) ONFIRE (Observations of Fire's Impact on the southeast Atlantic Region), a proposed deployment of the NCAR C-130 aircraft to Sao Tome Island in 2017.

Implications of Climate Change on the Heat Budget of Lentic Systems Used for Power Station Cooling: Case Study Clinton Lake, Illinois.

PubMed

Quijano, Juan C; Jackson, P Ryan; Santacruz, Santiago; Morales, Viviana M; García, Marcelo H

2016-01-05

We use a numerical model to analyze the impact of climate change-in particular higher air temperatures-on a nuclear power station that recirculates the water from a reservoir for cooling. The model solves the hydrodynamics, the transfer of heat in the reservoir, and the energy balance at the surface. We use the numerical model to (i) quantify the heat budget in the reservoir and determine how this budget is affected by the combined effect of the power station and climate change and (ii) quantify the impact of climate change on both the downstream thermal pollution and the power station capacity. We consider four different scenarios of climate change. Results of simulations show that climate change will reduce the ability to dissipate heat to the atmosphere and therefore the cooling capacity of the reservoir. We observed an increase of 25% in the thermal load downstream of the reservoir, and a reduction in the capacity of the power station of 18% during the summer months for the worst-case climate change scenario tested. These results suggest that climate change is an important threat for both the downstream thermal pollution and the generation of electricity by power stations that use lentic systems for cooling.

Implications of climate change on the heat budget of lentic systems used for power station cooling: Case study Clinton Lake, Illinois

USGS Publications Warehouse

Quijano, Juan C; Jackson, P. Ryan; Santacruz, Santiago; Morales, Viviana M; Garcia, Marcelo H.

2016-01-01

We use a numerical model to analyze the impact of climate change--in particular higher air temperatures--on a nuclear power station that recirculates the water from a reservoir for cooling. The model solves the hydrodynamics, the transfer of heat in the reservoir, and the energy balance at the surface. We use the numerical model to (i) quantify the heat budget in the reservoir and determine how this budget is affected by the combined effect of the power station and climate change and (ii) quantify the impact of climate change on both the downstream thermal pollution and the power station capacity. We consider four different scenarios of climate change. Results of simulations show that climate change will reduce the ability to dissipate heat to the atmosphere and therefore the cooling capacity of the reservoir. We observed an increase of 25% in the thermal load downstream of the reservoir, and a reduction in the capacity of the power station of 18% during the summer months for the worst-case climate change scenario tested. These results suggest that climate change is an important threat for both the downstream thermal pollution and the generation of electricity by power stations that use lentic systems for cooling.

Testing for the Possible Influence of Unknown Climate Forcings upon Global Temperature Increases from 1950-2000

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

Anderson, Bruce T.; Knight, Jeff R.; Ringer, Mark A.

2012-10-15

Global-scale variations in the climate system over the last half of the twentieth century, including long-term increases in global-mean near-surface temperatures, are consistent with concurrent human-induced emissions of radiatively active gases and aerosols. However, such consistency does not preclude the possible influence of other forcing agents, including internal modes of climate variability or unaccounted for aerosol effects. To test whether other unknown forcing agents may have contributed to multidecadal increases in global-mean near-surface temperatures from 1950 to 2000, data pertaining to observed changes in global-scale sea surface temperatures and observed changes in radiatively active atmospheric constituents are incorporated into numericalmore » global climate models. Results indicate that the radiative forcing needed to produce the observed long-term trends in sea surface temperatures—and global-mean near-surface temperatures—is provided predominantly by known changes in greenhouse gases and aerosols. Further, results indicate that less than 10% of the long-term historical increase in global-mean near-surface temperatures over the last half of the twentieth century could have been the result of internal climate variability. In addition, they indicate that less than 25%of the total radiative forcing needed to produce the observed long-term trend in global-mean near-surface temperatures could have been provided by changes in net radiative forcing from unknown sources (either positive or negative). These results, which are derived from simple energy balance requirements, emphasize the important role humans have played in modifying the global climate over the last half of the twentieth century.« less

Climate intercomparison of GPS radio occultation, RS90/92 radiosondes and GRUAN from 2002 to 2013

NASA Astrophysics Data System (ADS)

Ladstädter, F.; Steiner, A. K.; Schwärz, M.; Kirchengast, G.

2015-04-01

Observations from the GPS radio occultation (GPSRO) satellite technique and from the newly established GCOS Reference Upper Air Network (GRUAN) are both candidates to serve as reference observations in the Global Climate Observing System (GCOS). Such reference observations are key to decrease existing uncertainties in upper-air climate research. There are now more than 12 years of data available from GPSRO, with the recognized properties high accuracy, global coverage, high vertical resolution, and long-term stability. These properties make GPSRO a suitable choice for comparison studies with other upper-air observational systems. The GRUAN network consists of reference radiosonde ground stations (16 at present), which adhere to the GCOS climate monitoring principles. In this study, we intercompare GPSRO temperature and humidity profiles and Vaisala RS90/92 data from the "standard" global radiosonde network over the whole 2002 to 2013 time frame. Additionally, we include the first years of GRUAN data (using Vaisala RS92), available since 2009. GPSRO profiles which occur within 3 h and 300 km of radiosonde launches are used. Overall very good agreement is found between all three data sets with temperature differences usually less than 0.2 K. In the stratosphere above 30 hPa, temperature differences are larger but still within 0.5 K. Day/night comparisons with GRUAN data reveal small deviations likely related to a warm bias of the radiosonde data at high altitudes, but also residual errors from the GPSRO retrieval process might play a role. Vaisala RS90/92 specific humidity exhibits a dry bias of up to 40% in the upper troposphere, with a smaller bias at lower altitudes within 15%. GRUAN shows a marked improvement in the bias characteristics, with less than 5% difference to GPSRO, up to 300 hPa. GPSRO dry temperature and physical temperature are validated using radiosonde data as reference. We find that GPSRO provides valuable long-term stable reference observations with well-defined error characteristics for climate applications and for anchoring other upper-air measurements.

Climate intercomparison of GPS radio occultation, RS90/92 radiosondes and GRUAN over 2002 to 2013

NASA Astrophysics Data System (ADS)

Ladstädter, F.; Steiner, A. K.; Schwärz, M.; Kirchengast, G.

2014-11-01

Observations from the GPS radio occultation (GPSRO) satellite technique and from the newly established GCOS Reference Upper Air Network (GRUAN) are both candidates to serve as reference observations in the Global Climate Observing System (GCOS). Such reference observations are key to decrease existing uncertainties in upper-air climate research. There are now more than 12 years of data available from GPSRO, with the recognized properties high accuracy, global coverage, high vertical resolution, and long-term stability. These properties make GPSRO a suitable choice for comparison studies with other upper-air observational systems. The GRUAN network consists of reference radiosonde ground stations (16 at present), which adhere to the GCOS climate monitoring principles. In this study, we intercompare GPSRO temperature and humidity profiles and Vaisala RS90/92 data from the "standard" global radiosonde network over the whole 2002 to 2013 time frame. Additionally, we include the first years of GRUAN data (using Vaisala RS92), available since 2009. GPSRO profiles which occur within 3 h and 300 km of radiosonde launches are used. Very good agreement is found between all three datasets with temperature differences usually less than 0.2 K. In the stratosphere above 30 hPa, temperature differences are larger but still within 0.5 K. Day/night comparisons with GRUAN data reveal small deviations likely related to a warm bias of the radiosonde data at high altitudes, but also residual errors from the GPSRO retrieval process might play a role. Vaisala RS90/92 specific humidity exhibits a dry bias of up to 40% in the upper troposphere, with a smaller bias at lower altitudes within 15%. GRUAN shows a marked improvement in the bias characteristics, with less than 5% difference to GPSRO up to 300 hPa. GPSRO dry temperature and physical temperature are validated using radiosonde data as reference. We find that GPSRO provides valuable long-term stable reference observations with well-defined error characteristics for climate applications and for anchoring other upper-air measurements.

Integrating uncertainty propagation in GNSS radio occultation retrieval: from excess phase to atmospheric bending angle profiles

NASA Astrophysics Data System (ADS)

Schwarz, Jakob; Kirchengast, Gottfried; Schwaerz, Marc

2018-05-01

Global Navigation Satellite System (GNSS) radio occultation (RO) observations are highly accurate, long-term stable data sets and are globally available as a continuous record from 2001. Essential climate variables for the thermodynamic state of the free atmosphere - such as pressure, temperature, and tropospheric water vapor profiles (involving background information) - can be derived from these records, which therefore have the potential to serve as climate benchmark data. However, to exploit this potential, atmospheric profile retrievals need to be very accurate and the remaining uncertainties quantified and traced throughout the retrieval chain from raw observations to essential climate variables. The new Reference Occultation Processing System (rOPS) at the Wegener Center aims to deliver such an accurate RO retrieval chain with integrated uncertainty propagation. Here we introduce and demonstrate the algorithms implemented in the rOPS for uncertainty propagation from excess phase to atmospheric bending angle profiles, for estimated systematic and random uncertainties, including vertical error correlations and resolution estimates. We estimated systematic uncertainty profiles with the same operators as used for the basic state profiles retrieval. The random uncertainty is traced through covariance propagation and validated using Monte Carlo ensemble methods. The algorithm performance is demonstrated using test day ensembles of simulated data as well as real RO event data from the satellite missions CHAllenging Minisatellite Payload (CHAMP); Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC); and Meteorological Operational Satellite A (MetOp). The results of the Monte Carlo validation show that our covariance propagation delivers correct uncertainty quantification from excess phase to bending angle profiles. The results from the real RO event ensembles demonstrate that the new uncertainty estimation chain performs robustly. Together with the other parts of the rOPS processing chain this part is thus ready to provide integrated uncertainty propagation through the whole RO retrieval chain for the benefit of climate monitoring and other applications.

Climate Data Service in the FP7 EarthServer Project

NASA Astrophysics Data System (ADS)

Mantovani, Simone; Natali, Stefano; Barboni, Damiano; Grazia Veratelli, Maria

2013-04-01

EarthServer is a European Framework Program project that aims at developing and demonstrating the usability of open standards (OGC and W3C) in the management of multi-source, any-size, multi-dimensional spatio-temporal data - in short: "Big Earth Data Analytics". In order to demonstrate the feasibility of the approach, six thematic Lighthouse Applications (Cryospheric Science, Airborne Science, Atmospheric/ Climate Science, Geology, Oceanography, and Planetary Science), each with 100+ TB, are implemented. Scope of the Atmospheric/Climate lighthouse application (Climate Data Service) is to implement the system containing global to regional 2D / 3D / 4D datasets retrieved either from satellite observations, from numerical modelling and in-situ observations. Data contained in the Climate Data Service regard atmospheric profiles of temperature / humidity, aerosol content, AOT, and cloud properties provided by entities such as the European Centre for Mesoscale Weather Forecast (ECMWF), the Austrian Meteorological Service (Zentralanstalt für Meteorologie und Geodynamik - ZAMG), the Italian National Agency for new technologies, energies and sustainable development (ENEA), and the Sweden's Meteorological and Hydrological Institute (Sveriges Meteorologiska och Hydrologiska Institut -- SMHI). The system, through an easy-to-use web application permits to browse the loaded data, visualize their temporal evolution on a specific point with the creation of 2D graphs of a single field, or compare different fields on the same point (e.g. temperatures from different models and satellite observations), and visualize maps of specific fields superimposed with high resolution background maps. All data access operations and display are performed by means of OGC standard operations namely WMS, WCS and WCPS. The EarthServer project has just started its second year over a 3-years development plan: the present status the system contains subsets of the final database, with the scope of demonstrating I/O modules and visualization tools. At the end of the project all datasets will be available to the users.

Secular trends and climate drift in coupled ocean-atmosphere general circulation models

NASA Astrophysics Data System (ADS)

Covey, Curt; Gleckler, Peter J.; Phillips, Thomas J.; Bader, David C.

2006-02-01

Coupled ocean-atmosphere general circulation models (coupled GCMs) with interactive sea ice are the primary tool for investigating possible future global warming and numerous other issues in climate science. A long-standing problem with such models is that when different components of the physical climate system are linked together, the simulated climate can drift away from observation unless constrained by ad hoc adjustments to interface fluxes. However, 11 modern coupled GCMs, including three that do not employ flux adjustments, behave much better in this respect than the older generation of models. Surface temperature trends in control run simulations (with external climate forcing such as solar brightness and atmospheric carbon dioxide held constant) are small compared with observed trends, which include 20th century climate change due to both anthropogenic and natural factors. Sea ice changes in the models are dominated by interannual variations. Deep ocean temperature and salinity trends are small enough for model control runs to extend over 1000 simulated years or more, but trends in some regions, most notably the Arctic, differ substantially among the models and may be problematic. Methods used to initialize coupled GCMs can mitigate climate drift but cannot eliminate it. Lengthy "spin-ups" of models, made possible by increasing computer power, are one reason for the improvements this paper documents.

An integrated assessment modeling framework for uncertainty studies in global and regional climate change: the MIT IGSM-CAM (version 1.0)

NASA Astrophysics Data System (ADS)

Monier, E.; Scott, J. R.; Sokolov, A. P.; Forest, C. E.; Schlosser, C. A.

2013-12-01

This paper describes a computationally efficient framework for uncertainty studies in global and regional climate change. In this framework, the Massachusetts Institute of Technology (MIT) Integrated Global System Model (IGSM), an integrated assessment model that couples an Earth system model of intermediate complexity to a human activity model, is linked to the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM). Since the MIT IGSM-CAM framework (version 1.0) incorporates a human activity model, it is possible to analyze uncertainties in emissions resulting from both uncertainties in the underlying socio-economic characteristics of the economic model and in the choice of climate-related policies. Another major feature is the flexibility to vary key climate parameters controlling the climate system response to changes in greenhouse gases and aerosols concentrations, e.g., climate sensitivity, ocean heat uptake rate, and strength of the aerosol forcing. The IGSM-CAM is not only able to realistically simulate the present-day mean climate and the observed trends at the global and continental scale, but it also simulates ENSO variability with realistic time scales, seasonality and patterns of SST anomalies, albeit with stronger magnitudes than observed. The IGSM-CAM shares the same general strengths and limitations as the Coupled Model Intercomparison Project Phase 3 (CMIP3) models in simulating present-day annual mean surface temperature and precipitation. Over land, the IGSM-CAM shows similar biases to the NCAR Community Climate System Model (CCSM) version 3, which shares the same atmospheric model. This study also presents 21st century simulations based on two emissions scenarios (unconstrained scenario and stabilization scenario at 660 ppm CO2-equivalent) similar to, respectively, the Representative Concentration Pathways RCP8.5 and RCP4.5 scenarios, and three sets of climate parameters. Results of the simulations with the chosen climate parameters provide a good approximation for the median, and the 5th and 95th percentiles of the probability distribution of 21st century changes in global mean surface air temperature from previous work with the IGSM. Because the IGSM-CAM framework only considers one particular climate model, it cannot be used to assess the structural modeling uncertainty arising from differences in the parameterization suites of climate models. However, comparison of the IGSM-CAM projections with simulations of 31 CMIP5 models under the RCP4.5 and RCP8.5 scenarios show that the range of warming at the continental scale shows very good agreement between the two ensemble simulations, except over Antarctica, where the IGSM-CAM overestimates the warming. This demonstrates that by sampling the climate system response, the IGSM-CAM, even though it relies on one single climate model, can essentially reproduce the range of future continental warming simulated by more than 30 different models. Precipitation changes projected in the IGSM-CAM simulations and the CMIP5 multi-model ensemble both display a large uncertainty at the continental scale. The two ensemble simulations show good agreement over Asia and Europe. However, the ranges of precipitation changes do not overlap - but display similar size - over Africa and South America, two continents where models generally show little agreement in the sign of precipitation changes and where CCSM3 tends to be an outlier. Overall, the IGSM-CAM provides an efficient and consistent framework to explore the large uncertainty in future projections of global and regional climate change associated with uncertainty in the climate response and projected emissions.

Evidence for climate change in the satellite cloud record

DOE PAGES

Norris, Joel R.; Allen, Robert J.; Evan, Amato T.; ...

2016-07-11

Clouds substantially affect Earth’s energy budget by reflecting solar radiation back to space and by restricting emission of thermal radiation to space 1. They are perhaps the largest uncertainty in our understanding of climate change, owing to disagreement among climate models and observational datasets over what cloud changes have occurred during recent decades and will occur in response to global warming 2, 3. This is because observational systems originally designed for monitoring weather have lacked sufficient stability to detect cloud changes reliably over decades unless they have been corrected to remove artefacts 4, 5. Here we show that several independent,more » empirically corrected satellite records exhibit large-scale patterns of cloud change between the 1980s and the 2000s that are similar to those produced by model simulations of climate with recent historical external radiative forcing. Observed and simulated cloud change patterns are consistent with poleward retreat of mid-latitude storm tracks, expansion of subtropical dry zones, and increasing height of the highest cloud tops at all latitudes. The primary drivers of these cloud changes appear to be increasing greenhouse gas concentrations and a recovery from volcanic radiative cooling. Here, these results indicate that the cloud changes most consistently predicted by global climate models are currently occurring in nature.« less

The highs and lows of cloud radiative feedback: Comparing observational data and CMIP5 models

NASA Astrophysics Data System (ADS)

Jenney, A.; Randall, D. A.

2014-12-01

Clouds play a complex role in the climate system, and remain one of the more difficult aspects of the future climate to predict. Over subtropical eastern ocean basins, particularly next to California, Peru, and Southwest Africa, low marine stratocumulus clouds (MSC) help to reduce the amount of solar radiation that reaches the surface by reflecting incident sunlight. The climate feedback associated with these clouds is thought to be positive. This project looks at CMIP5 models and compares them to observational data from CERES and ERA-Interim to try and find observational evidence and model agreement for low, marine stratocumulus cloud feedback. Although current evidence suggests that the low cloud feedback is positive (IPCC, 2014), an analysis of the simulated relationship between July lower tropospheric stability (LTS) and shortwave cloud forcing in MSC regions suggests that this feedback is not due to changes in LTS. IPCC, 2013: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Stocker, T.F., D. Qin, G.-K. Plattner, M. Tignor, S.K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex and P.M. Midgley (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 1535 pp.

Evidence for climate change in the satellite cloud record

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

Norris, Joel R.; Allen, Robert J.; Evan, Amato T.

Clouds substantially affect Earth’s energy budget by reflecting solar radiation back to space and by restricting emission of thermal radiation to space 1. They are perhaps the largest uncertainty in our understanding of climate change, owing to disagreement among climate models and observational datasets over what cloud changes have occurred during recent decades and will occur in response to global warming 2, 3. This is because observational systems originally designed for monitoring weather have lacked sufficient stability to detect cloud changes reliably over decades unless they have been corrected to remove artefacts 4, 5. Here we show that several independent,more » empirically corrected satellite records exhibit large-scale patterns of cloud change between the 1980s and the 2000s that are similar to those produced by model simulations of climate with recent historical external radiative forcing. Observed and simulated cloud change patterns are consistent with poleward retreat of mid-latitude storm tracks, expansion of subtropical dry zones, and increasing height of the highest cloud tops at all latitudes. The primary drivers of these cloud changes appear to be increasing greenhouse gas concentrations and a recovery from volcanic radiative cooling. Here, these results indicate that the cloud changes most consistently predicted by global climate models are currently occurring in nature.« less

Current State of Climate Education in the United States: Are Graduate Students being Adequately Prepared to Address Climate Issues?

NASA Astrophysics Data System (ADS)

Kuster, E.; Fox, G.

2016-12-01

Climate change is happening; scientists have already observed changes in sea level, increases in atmospheric carbon dioxide, and declining polar ice. The students of today are the leaders of tomorrow, and it is our duty to make sure they are well equipped and they understand the implications of climate change as part of their research and professional careers. Graduate students, in particular, are gaining valuable and necessary research, leadership, and critical thinking skills, but we need to ensure that they are receiving the appropriate climate education in their graduate training. Previous studies have primarily focused on capturing the K-12, college level, and general publics' knowledge of the climate system, concluding with recommendations on how to improve climate literacy in the classroom. While this is extremely important to study, very few studies have captured the current perception that graduate students hold regarding the amount of climate education being offered to them. This information is important to capture, as it can inform future curriculum development. We developed and distributed a nationwide survey (495 respondents) for graduate students to capture their perception on the level of climate system education being offered and their view on the importance of having climate education. We also investigated differences in the responses based on either geographic area or discipline. We compared how important graduate students felt it was to include climate education in their own discipline versus outside disciplines. The authors will discuss key findings from this ongoing research.

A Data-Driven Assessment of the Sensitivity of Global Ecosystems to Climate Anomalies

NASA Astrophysics Data System (ADS)

Miralles, D. G.; Papagiannopoulou, C.; Demuzere, M.; Decubber, S.; Waegeman, W.; Verhoest, N.; Dorigo, W.

2017-12-01

Vegetation is a central player in the climate system, constraining atmospheric conditions through a series of feedbacks. This fundamental role highlights the importance of understanding regional drivers of ecological sensitivity and the response of vegetation to climatic changes. While nutrient availability and short-term disturbances can be crucial for vegetation at various spatiotemporal scales, natural vegetation dynamics are overall driven by climate. At monthly scales, the interactions between vegetation and climate become complex: some vegetation types react preferentially to specific climatic changes, with different levels of intensity, resilience and lagged response. For our current Earth System Models (ESMs) being able to capture this complexity is crucial but extremely challenging. This adds uncertainty to our projections of future climate and the fate of global ecosystems. Here, following a Granger causality framework based on a non-linear random forest predictive model, we exploit the current wealth of satellite data records to uncover the main climatic drivers of monthly vegetation variability globally. Results based on three decades of satellite data indicate that water availability is the most dominant factor driving vegetation in over 60% of the vegetated land. This overall dependency of ecosystems on water availability is larger than previously reported, partly owed to the ability of our machine-learning framework to disentangle the co-linearites between climatic drivers, and to quantify non-linear impacts of climate on vegetation. Our observation-based results are then used to benchmark ESMs on their representation of vegetation sensitivity to climate and climatic extremes. Our findings indicate that the sensitivity of vegetation to climatic anomalies is ill-reproduced by some widely-used ESMs.

Contribution of the climatic transect approach application to the study of soil degradation in South of Spain.

NASA Astrophysics Data System (ADS)

Ruiz-Sinoga, José D.; Gabarrón-Galeote, Miguel A.; Cerdà, Artemi; Martínez-Murillo, Juan F.

2014-05-01

Since 1990s, the climatic transect approach has been widely applied to Mediterranean mountainous areas where climatic conditions are modified in few kilometres, from semiarid to humid conditions. The target in most of the cases was to evaluate the climatic change effect on the spatial variability of eco-geomorphological system, runoff and erosion and soil degradation processes, especially, in abandoned fields and Mediterranean rangeland. The Physical Geography and Land Management Research Group from the University of Málaga is applying this experimental approach since 2001. The study area corresponded to the Mediterranean Cordillera Bética in South of Spain, from the Strait of Gibraltar to Cabo de Gata, where a longitudinal climatic transect can be observed: from humid Mediterranean climate in the West (>1,500 mm/y) to nearly arid Mediterranean climate in the East (200 mm/y). More specifically, the investigations were focussed on the spatial and temporal variability of eco-geomorphological system (vegetation, soil and water relationship), runoff and erosion processes and controlling factors affecting to abandoned fields located in steep hillslopes of metamorphic and acid bedrocks (phyllites, schists and mica-schists) but differing in climatic conditions (humid, subhumid, dry and semiarid Mediterranean climate). The aim of this contribution is to share our findings and challenges from the last 13 years being some of the most important ones: i) Mediterranean summer drought homogenise the functioning of eco-geomorphological system independently of the geographical location along the climatic transect; ii) drought period affects more dramatically to humid and subhumid Mediterranean areas, especially, to the vegetation cover and pattern; iii) areas characterised by dry-Mediterranean climate are found as threshold areas and in risk of aridification due to Climate Change; iv) runoff and erosion processes can be similar in humid and semiarid abandoned lands as it has to be taken into account local factors, such as exposure, repellency of soils to water and, especially, soil surface conditions. Further researches follow the transect approach but being applying to areas affected by recent and old fires in order to assess the effects of climate in the post-fire recovery of Mediterranean eco-geomorphological system and erosion processes.

Improving our fundamental understanding of the role of aerosol-cloud interactions in the climate system.

PubMed

Seinfeld, John H; Bretherton, Christopher; Carslaw, Kenneth S; Coe, Hugh; DeMott, Paul J; Dunlea, Edward J; Feingold, Graham; Ghan, Steven; Guenther, Alex B; Kahn, Ralph; Kraucunas, Ian; Kreidenweis, Sonia M; Molina, Mario J; Nenes, Athanasios; Penner, Joyce E; Prather, Kimberly A; Ramanathan, V; Ramaswamy, Venkatachalam; Rasch, Philip J; Ravishankara, A R; Rosenfeld, Daniel; Stephens, Graeme; Wood, Robert

2016-05-24

The effect of an increase in atmospheric aerosol concentrations on the distribution and radiative properties of Earth's clouds is the most uncertain component of the overall global radiative forcing from preindustrial time. General circulation models (GCMs) are the tool for predicting future climate, but the treatment of aerosols, clouds, and aerosol-cloud radiative effects carries large uncertainties that directly affect GCM predictions, such as climate sensitivity. Predictions are hampered by the large range of scales of interaction between various components that need to be captured. Observation systems (remote sensing, in situ) are increasingly being used to constrain predictions, but significant challenges exist, to some extent because of the large range of scales and the fact that the various measuring systems tend to address different scales. Fine-scale models represent clouds, aerosols, and aerosol-cloud interactions with high fidelity but do not include interactions with the larger scale and are therefore limited from a climatic point of view. We suggest strategies for improving estimates of aerosol-cloud relationships in climate models, for new remote sensing and in situ measurements, and for quantifying and reducing model uncertainty.

Improving Our Fundamental Understanding of the Role of Aerosol Cloud Interactions in the Climate System

NASA Technical Reports Server (NTRS)

Seinfeld, John H.; Bretherton, Christopher; Carslaw, Kenneth S.; Coe, Hugh; DeMott, Paul J.; Dunlea, Edward J.; Feingold, Graham; Ghan, Steven; Guenther, Alex B.; Kahn, Ralph;

Improving our fundamental understanding of the role of aerosol-cloud interactions in the climate system

DOE PAGES

Seinfeld, John H.; Bretherton, Christopher; Carslaw, Kenneth S.; ...

2016-05-24

The effect of an increase in atmospheric aerosol concentrations on the distribution and radiative properties of Earth’s clouds is the most uncertain component of the overall global radiative forcing from pre-industrial time. General Circulation Models (GCMs) are the tool for predicting future climate, but the treatment of aerosols, clouds, and aerosol-cloud radiative effects carries large uncertainties that directly affect GCM predictions, such as climate sensitivity. Predictions are hampered by the large range of scales of interaction between various components that need to be captured. Observation systems (remote sensing, in situ) are increasingly being used to constrain predictions but significant challengesmore » exist, to some extent because of the large range of scales and the fact that the various measuring systems tend to address different scales. Fine-scale models represent clouds, aerosols, and aerosol-cloud interactions with high fidelity but do not include interactions with the larger scale and are therefore limited from a climatic point of view. Lastly, we suggest strategies for improving estimates of aerosol-cloud relationships in climate models, for new remote sensing and in situ measurements, and for quantifying and reducing model uncertainty.« less

Improving our fundamental understanding of the role of aerosol−cloud interactions in the climate system

PubMed Central

Seinfeld, John H.; Bretherton, Christopher; Carslaw, Kenneth S.; Coe, Hugh; DeMott, Paul J.; Dunlea, Edward J.; Feingold, Graham; Ghan, Steven; Guenther, Alex B.; Kraucunas, Ian; Molina, Mario J.; Nenes, Athanasios; Penner, Joyce E.; Prather, Kimberly A.; Ramanathan, V.; Ramaswamy, Venkatachalam; Rasch, Philip J.; Ravishankara, A. R.; Rosenfeld, Daniel; Stephens, Graeme; Wood, Robert

2016-01-01

The effect of an increase in atmospheric aerosol concentrations on the distribution and radiative properties of Earth’s clouds is the most uncertain component of the overall global radiative forcing from preindustrial time. General circulation models (GCMs) are the tool for predicting future climate, but the treatment of aerosols, clouds, and aerosol−cloud radiative effects carries large uncertainties that directly affect GCM predictions, such as climate sensitivity. Predictions are hampered by the large range of scales of interaction between various components that need to be captured. Observation systems (remote sensing, in situ) are increasingly being used to constrain predictions, but significant challenges exist, to some extent because of the large range of scales and the fact that the various measuring systems tend to address different scales. Fine-scale models represent clouds, aerosols, and aerosol−cloud interactions with high fidelity but do not include interactions with the larger scale and are therefore limited from a climatic point of view. We suggest strategies for improving estimates of aerosol−cloud relationships in climate models, for new remote sensing and in situ measurements, and for quantifying and reducing model uncertainty. PMID:27222566

Climate Engine - Monitoring Drought with Google Earth Engine

NASA Astrophysics Data System (ADS)

Hegewisch, K.; Daudert, B.; Morton, C.; McEvoy, D.; Huntington, J. L.; Abatzoglou, J. T.

2016-12-01

Drought has adverse effects on society through reduced water availability and agricultural production and increased wildfire risk. An abundance of remotely sensed imagery and climate data are being collected in near-real time that can provide place-based monitoring and early warning of drought and related hazards. However, in an era of increasing wealth of earth observations, tools that quickly access, compute, and visualize archives, and provide answers at relevant scales to better inform decision-making are lacking. We have developed ClimateEngine.org, a web application that uses Google's Earth Engine platform to enable users to quickly compute and visualize real-time observations. A suite of drought indices allow us to monitor and track drought from local (30-meters) to regional scales and contextualize current droughts within the historical record. Climate Engine is currently being used by U.S. federal agencies and researchers to develop baseline conditions and impact assessments related to agricultural, ecological, and hydrological drought. Climate Engine is also working with the Famine Early Warning Systems Network (FEWS NET) to expedite monitoring agricultural drought over broad areas at risk of food insecurity globally.

A review of our understanding of the role played in the climate system by land surface processes (Invited)

NASA Astrophysics Data System (ADS)

Nicholson, S. E.

2013-12-01

The paper provides an historical review of research on the impact of the land surface on climate. It commences will the seminal work of Jule Charney on albedo as a potential cause of drought and follows the trail of follow-up studies on the question of desertification and its role in climate. With the exception of a very early paper by Namias, early work was limited mainly to modeling efforts. At the same time, several observational studies provided evidence that land surface feedbacks could enhance and prolong drought, especially in the African Sahel. Later work emphasized the role of soil moisture rather than albedo. Several important field studies also examined the role of the land surface. Examples include FIFE, HAPEX-Sahel and BOREAS. In recent years some major changes in the concept have occurred. There is now substantial observational evidence of an impact at the mesoscale. The role of land surface feedback on climate has become mainstream. Finally, a new subdiscipline has emerged that emphasizes feedbacks between the water cycle, vegetation and climate, namely ecohydrology.

Understanding the Role of the Saharan Heat Low in Modifying Atmospheric Dust Distributions - Observations From Two Research Aircraft Flying Simultaneously Over Western Africa

NASA Astrophysics Data System (ADS)

Engelstaedter, S.; Washington, R.; Allen, C.; Flamant, C.; Chaboureau, J.-P.; Kocha, C.; Lavaysse, C.

2012-04-01

The near-surface low pressure system that develops over western Africa in Boreal summer (know as the Saharan Heat Low) is thought to have a significant influence on regional and global climate due to its links with the Monsoon, the Northern Atlantic and the Mediterranean climate system. The SHL is associated with the deepest atmospheric boundary layer on the planet and is co-located with the highest dust loadings in the world. The processes that link the heat low and dust distribution are only poorly understood. Improving the representation of the heat low and the processes that control the emission and atmospheric distribution of dust in climate and NWP models is crucial if we are to reduce known systematic errors in climate predictions and weather forecasts. In collaboration with European partners, the UK-based consortium project "Fennec - The Saharan Climate System" aims at improving our understanding of this complex climate system by integrating for the first time coordinated ground and aircraft observations from the central Sahara, newly developed satellite products, and the application of regional and global models. On 22 June 2011, two research aircraft operating out of Fuerteventura (Spain) surveyed the Saharan Heat Low centred over Mauritania-Mali border. The aircraft flew simultaneously in the morning and in the afternoon on two different tracks thereby sampling each track four times on that day. Both aircraft were equipped with a downward looking LIDAR for aerosol detection. In total, 51 sondes were dropped during the flights making this the most comprehensive dataset to study the spatio-temporal diurnal evolution of the heat low including the interactions between the atmospheric boundary layer and dust distributions. Combining LIDAR observations, satellite imagery and back-trajectory modelling we show that an aged dust layer was present in the heat low region resulting from previous day's dust activity associated with a south-moving density current from the Atlas mountains and westward-moving Haboob fronts originating along the Algeria-Mali border. We show how the dust is distributed within the atmosphere and how it is modified during the course of the day by various processes including the development of the atmospheric boundary layer and associated dry convection as well as the inflow of moisture-rich monsoon air from the south.

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

NASA Technical Reports Server (NTRS)

Putman, William M.

2010-01-01

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.

The NASA Modern Era Reanalysis for Research and Applications, Version-2 (MERRA-2)

NASA Astrophysics Data System (ADS)

Gelaro, R.; McCarty, W.; Molod, A.; Suarez, M.; Takacs, L.; Todling, R.

2014-12-01

The NASA Modern Era Reanalysis for Research Applications Version-2 (MERRA-2) is a reanalysis for the satellite era using an updated version of the Goddard Earth Observing System Data Assimilation System Version-5 (GEOS-5) produced by the Global Modeling and Assimilation Office (GMAO). MERRA-2 will assimilate meteorological and aerosol observations not available to MERRA and includes improvements to the GEOS-5 model and analysis scheme so as to provide an ongoing climate analysis beyond MERRA's terminus. MERRA-2 will also serve as a development milestone for a future GMAO coupled Earth system analysis. Production of MERRA-2 began in June 2014 in four processing streams, with convergence to a single near-real time climate analysis expected by early 2015. This talk provides an overview of the MERRA-2 system developments and key science results. For example, compared with MERRA, MERRA-2 exhibits a well-balanced relationship between global precipitation and evaporation, with significantly reduced sensitivity to changes in the global observing system through time. Other notable improvements include reduced biases in the tropical middle- and upper-tropospheric wind and near-surface temperature over continents.

Broad-Band Analysis of Polar Motion Excitations

NASA Astrophysics Data System (ADS)

Chen, J.

2016-12-01

Earth rotational changes, i.e. polar motion and length-of-day (LOD), are driven by two types of geophysical excitations: 1) mass redistribution within the Earth system, and 2) angular momentum exchange between the solid Earth (more precisely the crust) and other components of the Earth system. Accurate quantification of Earth rotational excitations has been difficult, due to the lack of global-scale observations of mass redistribution and angular momentum exchange. The over 14-years time-variable gravity measurements from the Gravity Recovery and Climate Experiment (GRACE) have provided a unique means for quantifying Earth rotational excitations from mass redistribution in different components of the climate system. Comparisons between observed Earth rotational changes and geophysical excitations estimated from GRACE, satellite laser ranging (SLR) and climate models show that GRACE-derived excitations agree remarkably well with polar motion observations over a broad-band of frequencies. GRACE estimates also suggest that accelerated polar region ice melting in recent years and corresponding sea level rise have played an important role in driving long-term polar motion as well. With several estimates of polar motion excitations, it is possible to estimate broad-band noise variance and noise power spectra in each, given reasonable assumptions about noise independence. Results based on GRACE CSR RL05 solutions clearly outperform other estimates with the lowest noise levels over a broad band of frequencies.

Use of Machine Learning Techniques for Iidentification of Robust Teleconnections to East African Rainfall Variability in Observations and Models

NASA Technical Reports Server (NTRS)

Roberts, J. Brent; Robertson, Franklin R.; Funk, Chris

2014-01-01

Providing advance warning of East African rainfall variations is a particular focus of several groups including those participating in the Famine Early Warming Systems Network. Both seasonal and long-term model projections of climate variability are being used to examine the societal impacts of hydrometeorological variability on seasonal to interannual and longer time scales. The NASA / USAID SERVIR project, which leverages satellite and modeling-based resources for environmental decision making in developing nations, is focusing on the evaluation of both seasonal and climate model projections to develop downscaled scenarios for using in impact modeling. The utility of these projections is reliant on the ability of current models to capture the embedded relationships between East African rainfall and evolving forcing within the coupled ocean-atmosphere-land climate system. Previous studies have posited relationships between variations in El Niño, the Walker circulation, Pacific decadal variability (PDV), and anthropogenic forcing. This study applies machine learning methods (e.g. clustering, probabilistic graphical model, nonlinear PCA) to observational datasets in an attempt to expose the importance of local and remote forcing mechanisms of East African rainfall variability. The ability of the NASA Goddard Earth Observing System (GEOS5) coupled model to capture the associated relationships will be evaluated using Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations.

An Enhanced Engineering Perspective of Global Climate Systems and Statistical Formulation of Terrestrial CO2 Exchanges

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

Dai, Yuanshun; Baek, Seung H.; Garcia-Diza, Alberto

2012-01-01

This paper designs a comprehensive approach based on the engineering machine/system concept, to model, analyze, and assess the level of CO2 exchange between the atmosphere and terrestrial ecosystems, which is an important factor in understanding changes in global climate. The focus of this article is on spatial patterns and on the correlation between levels of CO2 fluxes and a variety of influencing factors in eco-environments. The engineering/machine concept used is a system protocol that includes the sequential activities of design, test, observe, and model. This concept is applied to explicitly include various influencing factors and interactions associated with CO2 fluxes.more » To formulate effective models of a large and complex climate system, this article introduces a modeling technique that will be referred to as Stochastic Filtering Analysis of Variance (SFANOVA). The CO2 flux data observed from some sites of AmeriFlux are used to illustrate and validate the analysis, prediction and globalization capabilities of the proposed engineering approach and the SF-ANOVA technology. The SF-ANOVA modeling approach was compared to stepwise regression, ridge regression, and neural networks. The comparison indicated that the proposed approach is a valid and effective tool with similar accuracy and less complexity than the other procedures.« less

Probabilistic Estimates of Climate Impacts of the Paris Agreement and Contributions from Different Countries.

NASA Astrophysics Data System (ADS)

Sokolov, A. P.; Paltsev, S.; Chen, Y. H. H.; Monier, E.; Libardoni, A. G.; Forest, C. E.

2017-12-01

In December of 2015 during COP21 meeting in Paris almost 200 countries signed an agreement pledging to reduce their anthropogenic greenhouse gas (GHG) emissions. Recently USA announced plans to withdraw from the agreement. In this study, we estimate an impact of this decision on future climate using the MIT Integrated Global System Model, which consists of the human activity model, Economic Projection and Policy Analysis (EPPA) model, and a climate model of intermediate complexity, the MIT Earth System Model (MESM). For comparison, we also estimated impacts of possible withdrawals of China, Europe or India. In addition to the "no climate policy" scenario, we consider five emissions scenarios: Paris, Paris_no_USA, Paris_no_EUR and so on. Climate simulations were carried out from 1861 to 2005 driven by prescribed changes in GHGs and natural forcings and them continued to 2100 driven by GHG emissions produced by EPPA model. Because Paris agreement only cover the period up to 2030, last five scenarios were created assuming that emissions or carbon intensity will continue to decrease after 2030 at the same rate as in the 2020-2030 period. To account for uncertainty in climate system response to external forcing, we carry out 400 member ensembles on climate simulations for each scenario. Probability distributions for climate parameters are obtained by comparing simulated climate for 1861 to 2010 with observations. Our analysis shows that, full implementation of Paris agreement (under above-descried assumptions) will increase probability of surface air temperature in the last decade of this century increasing by less than 3oC relative to pre-industrial form about 20% for "no climate policy" to about 86%. Withdrawal of USA, China, Europe or India will decrease this probability to about 63, 67, 75 and 82%, respectively.

High Resolution Global Climate Modeling with GEOS-5: Intense Precipitation, Convection and Tropical Cyclones on Seasonal Time-Scales.

NASA Technical Reports Server (NTRS)

Putnam, WilliamM.

2011-01-01

In 2008 the World Modeling Summit for Climate Prediction concluded that "climate modeling will need-and is ready-to move to fundamentally new high-resolution approaches to capitalize on the seamlessness of the weather-climate continuum." Following from this, experimentation with very high-resolution global climate modeling has gained enhanced priority within many modeling groups and agencies. The NASA Goddard Earth Observing System model (GEOS-5) has been enhanced to provide a capability for the execution at the finest horizontal resolutions POS,SIOle with a global climate model today. Using this high-resolution, non-hydrostatic version of GEOS-5, we have developed a unique capability to explore the intersection of weather and climate within a seamless prediction system. Week-long weather experiments, to mUltiyear climate simulations at global resolutions ranging from 3.5- to 14-km have demonstrated the predictability of extreme events including severe storms along frontal systems, extra-tropical storms, and tropical cyclones. The primary benefits of high resolution global models will likely be in the tropics, with better predictions of the genesis stages of tropical cyclones and of the internal structure of their mature stages. Using satellite data we assess the accuracy of GEOS-5 in representing extreme weather phenomena, and their interaction within the global climate on seasonal time-scales. The impacts of convective parameterization and the frequency of coupling between the moist physics and dynamics are explored in terms of precipitation intensity and the representation of deep convection. We will also describe the seasonal variability of global tropical cyclone activity within a global climate model capable of representing the most intense category 5 hurricanes.

Examining Challenges Related to the Production of Actionable Climate Knowledge for Adaptation Decision-Making: A Focus on Climate Knowledge System Producers

NASA Astrophysics Data System (ADS)

Ernst, K.; Preston, B. L.; Tenggren, S.; Klein, R.; Gerger-Swartling, Å.

2017-12-01

Many challenges to adaptation decision-making and action have been identified across peer-reviewed and gray literature. These challenges have primarily focused on the use of climate knowledge for adaptation decision-making, the process of adaptation decision-making, and the needs of the decision-maker. Studies on climate change knowledge systems often discuss the imperative role of climate knowledge producers in adaptation decision-making processes and stress the need for producers to engage in knowledge co-production activities and to more effectively meet decision-maker needs. While the influence of climate knowledge producers on the co-production of science for adaptation decision-making is well-recognized, hardly any research has taken a direct approach to analyzing the challenges that climate knowledge producers face when undertaking science co-production. Those challenges can influence the process of knowledge production and may hinder the creation, utilization, and dissemination of actionable knowledge for adaptation decision-making. This study involves semi-structured interviews, focus groups, and participant observations to analyze, identify, and contextualize the challenges that climate knowledge producers in Sweden face as they endeavor to create effective climate knowledge systems for multiple contexts, scales, and levels across the European Union. Preliminary findings identify complex challenges related to education, training, and support; motivation, willingness, and culture; varying levels of prioritization; professional roles and responsibilities; the type and amount of resources available; and professional incentive structures. These challenges exist at varying scales and levels across individuals, organizations, networks, institutions, and disciplines. This study suggests that the creation of actionable knowledge for adaptation decision-making is not supported across scales and levels in the climate knowledge production landscape. Additionally, enabling the production of actionable knowledge for adaptation decision-making requires multi-level effort beyond the individual level.

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

NASA Technical Reports Server (NTRS)

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

2014-01-01

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

The NASA Earth Science Flight Program: an update

NASA Astrophysics Data System (ADS)

Neeck, Steven P.

2015-10-01

Earth's changing environment impacts every aspect of life on our planet and climate change has profound implications on society. Studying Earth as a single complex system is essential to understanding the causes and consequences of climate change and other global environmental concerns. NASA's Earth Science Division (ESD) shapes an interdisciplinary view of Earth, exploring interactions among the atmosphere, oceans, ice sheets, land surface interior, and life itself. This enables scientists to measure global and climate changes and to inform decisions by government, other organizations, and people in the United States and around the world. The data collected and results generated are accessible to other agencies and organizations to improve the products and services they provide, including air quality indices, disaster prediction and response, agricultural yield projections, and aviation safety. ESD's Flight Program provides the space based observing systems and infrastructure for mission operations and scientific data processing and distribution that support NASA's Earth science research and modeling activities. The Flight Program currently has 21 operating Earth observing space missions, including the recently launched Global Precipitation Measurement (GPM) mission, the Orbiting Carbon Observatory-2 (OCO-2), the Soil Moisture Active Passive (SMAP) mission, and the International Space Station (ISS) RapidSCAT and Cloud-Aerosol Transport System (CATS) instruments. The ESD has 22 more missions and instruments planned for launch over the next decade. These include first and second tier missions from the 2007 Earth Science Decadal Survey, Climate Continuity missions and selected instruments to assure availability of key climate data sets, operational missions to ensure sustained land imaging provided by the Landsat system, and small-sized competitively selected orbital missions and instrument missions of opportunity belonging to the Earth Venture (EV) Program. Some examples are the NASA-ISRO Synthetic Aperture Radar (NISAR), Surface Water and Ocean Topography (SWOT), ICESat-2, SAGE III on ISS, Gravity Recovery and Climate Experiment Follow On (GRACE FO), Tropospheric Emissions: Monitoring of Pollution (TEMPO), Cyclone Global Navigation Satellite System (CYGNSS), ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS), and Global Ecosystem Dynamics Investigation (GEDI) Lidar missions. An overview of plans and current status will be presented.

The NASA Earth Science Program and Small Satellites

NASA Technical Reports Server (NTRS)

Neeck, Steven P.

2015-01-01

Earth's changing environment impacts every aspect of life on our planet and climate change has profound implications on society. Studying Earth as a single complex system is essential to understanding the causes and consequences of climate change and other global environmental concerns. NASA's Earth Science Division (ESD) shapes an interdisciplinary view of Earth, exploring interactions among the atmosphere, oceans, ice sheets, land surface interior, and life itself. This enables scientists to measure global and climate changes and to inform decisions by Government, other organizations, and people in the United States and around the world. The data collected and results generated are accessible to other agencies and organizations to improve the products and services they provide, including air quality indices, disaster prediction and response, agricultural yield projections, and aviation safety. ESD's Flight Program provides the spacebased observing systems and supporting infrastructure for mission operations and scientific data processing and distribution that support NASA's Earth science research and modeling activities. The Flight Program currently has 21 operating Earth observing space missions, including the recently launched Global Precipitation Measurement (GPM) mission, the Orbiting Carbon Observatory-2 (OCO-2), the Soil Moisture Active Passive (SMAP) mission, and the International Space Station (ISS) RapidSCAT and Cloud-Aerosol Transport System (CATS) instruments. The ESD has 22 more missions and instruments planned for launch over the next decade. These include first and second tier missions from the 2007 Earth Science Decadal Survey, Climate Continuity missions to assure availability of key climate data sets, and small-sized competitively selected orbital missions and instrument missions of opportunity belonging to the Earth Venture (EV) Program. Small satellites (500 kg or less) are critical contributors to these current and future satellite missions. Some examples are the aforementioned Orbiting Carbon Observatory-2 (OCO-2), the Gravity Recovery and Climate Experiment Follow On (GRACE FO), and the Cyclone Global Navigation Satellite System (CYGNSS) microsatellite constellation. Small satellites also support ESD in space validation and risk reduction of enabling technologies (components and systems). The status of the ESD Flight Program and the role of small satellites will be discussed.

weather@home 2: validation of an improved global-regional climate modelling system

NASA Astrophysics Data System (ADS)

Guillod, Benoit P.; Jones, Richard G.; Bowery, Andy; Haustein, Karsten; Massey, Neil R.; Mitchell, Daniel M.; Otto, Friederike E. L.; Sparrow, Sarah N.; Uhe, Peter; Wallom, David C. H.; Wilson, Simon; Allen, Myles R.

2017-05-01

Extreme weather events can have large impacts on society and, in many regions, are expected to change in frequency and intensity with climate change. Owing to the relatively short observational record, climate models are useful tools as they allow for generation of a larger sample of extreme events, to attribute recent events to anthropogenic climate change, and to project changes in such events into the future. The modelling system known as weather@home, consisting of a global climate model (GCM) with a nested regional climate model (RCM) and driven by sea surface temperatures, allows one to generate a very large ensemble with the help of volunteer distributed computing. This is a key tool to understanding many aspects of extreme events. Here, a new version of the weather@home system (weather@home 2) with a higher-resolution RCM over Europe is documented and a broad validation of the climate is performed. The new model includes a more recent land-surface scheme in both GCM and RCM, where subgrid-scale land-surface heterogeneity is newly represented using tiles, and an increase in RCM resolution from 50 to 25 km. The GCM performs similarly to the previous version, with some improvements in the representation of mean climate. The European RCM temperature biases are overall reduced, in particular the warm bias over eastern Europe, but large biases remain. Precipitation is improved over the Alps in summer, with mixed changes in other regions and seasons. The model is shown to represent the main classes of regional extreme events reasonably well and shows a good sensitivity to its drivers. In particular, given the improvements in this version of the weather@home system, it is likely that more reliable statements can be made with regards to impact statements, especially at more localized scales.

Adaptation of rainfed agriculture to climatic variability in the Mixteca Alta Region of Oaxaca, Mexico

NASA Astrophysics Data System (ADS)

Rogé, P.; Friedman, A. R.; Astier, M.; Altieri, M.

2015-12-01

The traditional management systems of the Mixteca Alta Region of Oaxaca, Mexico offer historical lessons about resilience to climatic variability. We interviewed small farmers to inquire about the dynamics of abandonment and persistence of a traditional management systems. We interpret farmers' narratives from a perspective of general agroecological resilience. In addition, we facilitated workshops in small farmers described their adaptation to past climate challenges and identified 14 indicators that they subsequently used to evaluate the condition of their agroecosystems. The most recent years presented increasingly extreme climatic and socioeconomic hardships: increased temperatures, delayed rainy seasons, reduced capacity of soils to retain soil moisture, changing cultural norms, and reduced rural labor. Farmers reported that their cropping systems were changing for multiple reasons: more drought, later rainfall onset, decreased rural labor, and introduced labor-saving technologies. Examination of climate data found that farmers' climate narratives were largely consistent with the observational record. There have been increases in temperature and rainfall intensity, and an increase in rainfall seasonality that may be perceived as later rainfall onset. Farmers ranked landscape-scale indicators as more marginal than farmer management or soil quality indicators. From this analysis, farmers proposed strategies to improve the ability of their agroecosystems to cope with climatic variability. Notably, they recognized that social organizing and education are required for landscape-level indicators to be improved. Transformative change is required to develop novel cropping systems and complementary activities to agriculture that will allow for farming to be sustained in the face of these challenges. Climate change adaptation by small farmers involves much more than just a set of farming practices, but also community action to tackle collective problems.

The Copernicus Climate Change Service (C3S): Open Access to a Climate Data Store

NASA Astrophysics Data System (ADS)

Thepaut, Jean-Noel; Dee, Dick

2016-04-01

In November 2014, The European Centre for Medium-range Weather Forecasts (ECMWF) signed an agreement with the European Commission to deliver two of the Copernicus Earth Observation Programme Services on the Commission's behalf. The ECMWF delivered services - the Copernicus Climate Change Service (C3S) and Atmosphere Monitoring Service (CAMS) - will bring a consistent standard to how we monitor and predict atmospheric conditions and climate change. They will maximise the potential of past, current and future earth observations - ground, ocean, airborne, satellite - and analyse these to monitor and predict atmospheric conditions and in the future, climate change. With the wealth of free and open data that the services provide, they will help business users to assess the impact of their business decisions and make informed choices, delivering a more energy efficient and climate aware economy. These sound investment decisions now will not only stimulate growth in the short term, but reduce the impact of climate change on the economy and society in the future. C3S is in its proof of concept phase and through its Climate Data Store will provide • global and regional climate data reanalyses; • multi-model seasonal forecasts; • customisable visual data to enable examination of wide range of scenarios and model the impact of changes; • access to all the underlying data, including climate data records from various satellite and in-situ observations. In addition, C3S will provide key indicators on climate change drivers (such as carbon dioxide) and impacts (such as reducing glaciers). The aim of these indicators will be to support European adaptation and mitigation policies in a number of economic sectors. At the heart of the Service is the provision of open access to a one stop shop (the Climate Data Store) of climate data and modelling, analysing more than 20 Essential Climate Variables to build a global picture of our past, present and future climate and developing customisable climate indicators for key economic sectors, such as energy, water management, agriculture, insurance, health… This talk will focus on the Climate Data Store facility, designed as a distributed system, providing improved access to existing datasets though a unified web interface. This service will accommodate the needs of the highly diverse set of users, from policy makers to expert practitioners and scientists.

Undergraduate Students as Climate Communicators

NASA Astrophysics Data System (ADS)

Sharif, H. O.; Joseph, J.; Mullendore, G. L.

2012-12-01

The University of Texas at San Antonio (UTSA), San Antonio College (SAC), and the University of North Dakota (UND) are partnering with NASA to provide underrepresented undergraduates from UTSA, SAC, and other community colleges climate-related research and education experiences. The program aims to develop a robust response to climate change by providing K-16 climate change education; enhance the effectiveness of K-16 education particularly in engineering and other STEM disciplines by use of new instructional technologies; increase the enrollment in engineering programs and the number of engineering degrees awarded by showing engineering's usefulness in relation to the much-discussed contemporary issue of climate change; increase persistence in STEM degrees by providing student research opportunities; and increase the ethnic diversity of those receiving engineering degrees and help ensure an ethnically diverse response to climate change. Students will have the opportunity to participate in guided research experiences aligned with NASA Science Plan objectives for climate and Earth system science and the educational objectives of the three institutions. An integral part of the learning process will include training in modern media technology (webcasts), and in using this technology to communicate the information on climate change to others, especially high school students, culminating in production of a webcast about investigating aspects of climate change using NASA data. Content developed is leveraged by NASA Earth observation data and NASA Earth system models and tools. Several departments are involved in the educational program.

The Earth System Grid Federation (ESGF): Climate Science Infrastructure for Large-scale Data Management and Dissemination

NASA Astrophysics Data System (ADS)

Williams, D. N.

2015-12-01

Progress in understanding and predicting climate change requires advanced tools to securely store, manage, access, process, analyze, and visualize enormous and distributed data sets. Only then can climate researchers understand the effects of climate change across all scales and use this information to inform policy decisions. With the advent of major international climate modeling intercomparisons, a need emerged within the climate-change research community to develop efficient, community-based tools to obtain relevant meteorological and other observational data, develop custom computational models, and export analysis tools for climate-change simulations. While many nascent efforts to fill these gaps appeared, they were not integrated and therefore did not benefit from collaborative development. Sharing huge data sets was difficult, and the lack of data standards prevented the merger of output data from different modeling groups. Thus began one of the largest-ever collaborative data efforts in climate science, resulting in the Earth System Grid Federation (ESGF), which is now used to disseminate model, observational, and reanalysis data for research assessed by the Intergovernmental Panel on Climate Change (IPCC). Today, ESGF is an open-source petabyte-level data storage and dissemination operational code-base that manages secure resources essential for climate change study. It is designed to remain robust even as data volumes grow exponentially. The internationally distributed, peer-to-peer ESGF "data cloud" archive represents the culmination of an effort that began in the late 1990s. ESGF portals are gateways to scientific data collections hosted at sites around the globe that allow the user to register and potentially access the entire ESGF network of data and services. The growing international interest in ESGF development efforts has attracted many others who want to make their data more widely available and easy to use. For example, the World Climate Research Program, which provides governance for CMIP, has now endorsed the ESGF software foundation to be used for ~70 other model intercomparison projects (MIPs), such as obs4MIPs, TAMIP, CFMIP, and GeoMIP. At present, more than 40 projects disseminate their data via ESGF.

Graphics Processing Units (GPU) and the Goddard Earth Observing System atmospheric model (GEOS-5): Implementation and Potential Applications

NASA Technical Reports Server (NTRS)

Putnam, William M.

2011-01-01

Earth system models like the Goddard Earth Observing System model (GEOS-5) have been pushing the limits of large clusters of multi-core microprocessors, producing breath-taking fidelity in resolving cloud systems at a global scale. GPU computing presents an opportunity for improving the efficiency of these leading edge models. A GPU implementation of GEOS-5 will facilitate the use of cloud-system resolving resolutions in data assimilation and weather prediction, at resolutions near 3.5 km, improving our ability to extract detailed information from high-resolution satellite observations and ultimately produce better weather and climate predictions

Severe Weather in a Changing Climate: Getting to Adaptation

NASA Astrophysics Data System (ADS)

Wuebbles, D. J.; Janssen, E.; Kunkel, K.

2011-12-01

Analyses of observation records from U.S. weather stations indicate there is an increasing trend over recent decades in certain types of severe weather, especially large precipitation events. Widespread changes in temperature extremes have been observed over the last 50 years. In particular, the number of heat waves globally (and some parts of the U.S.) has increased, and there have been widespread increases in the numbers of warm nights. Also, analyses show that we are now breaking twice as many heat records as cold records in the U.S. Since 1957, there has been an increase in the number of historically top 1% of heavy precipitation events across the U.S. Our new analyses of the repeat or reoccurrence frequencies of large precipitation storms are showing that such events are occurring more often than in the past. The pattern of precipitation change is one of increases generally at higher northern latitudes and drying in the tropics and subtropics over land. It needs to be recognized that every weather event that happens nowadays takes place in the context of the changes in the background climate system. So nothing is entirely "natural" anymore. It's a fallacy to think that individual events are caused entirely by any one thing, either natural variation or human-induced climate change. Every event is influenced by many factors. Human-induced climate change is now a factor in weather events. The changes occurring in precipitation are consistent with the analyses of our changing climate. For extreme precipitation, we know that more precipitation is falling in very heavy events. And we know key reasons why; warmer air holds more water vapor, and so when any given weather system moves through, the extra water dumps can lead to a heavy downpour. As the climate system continues to warm, models of the Earth's climate system indicate severe precipitation events will likely become more commonplace. Water vapor will continue to increase in the atmosphere along with the warming, and large precipitation events will likely increase in intensity and frequency. In the presentation, we will not only discuss the recent trends in severe weather and the projections of the impacts of climate change on severe weather in the future, but also specific examples of how this information is being used in developing and applying adaptation policies.

Assessing Weather-Yield Relationships in Rice at Local Scale Using Data Mining Approaches

PubMed Central

Delerce, Sylvain; Dorado, Hugo; Grillon, Alexandre; Rebolledo, Maria Camila; Prager, Steven D.; Patiño, Victor Hugo; Garcés Varón, Gabriel; Jiménez, Daniel

2016-01-01

Seasonal and inter-annual climate variability have become important issues for farmers, and climate change has been shown to increase them. Simultaneously farmers and agricultural organizations are increasingly collecting observational data about in situ crop performance. Agriculture thus needs new tools to cope with changing environmental conditions and to take advantage of these data. Data mining techniques make it possible to extract embedded knowledge associated with farmer experiences from these large observational datasets in order to identify best practices for adapting to climate variability. We introduce new approaches through a case study on irrigated and rainfed rice in Colombia. Preexisting observational datasets of commercial harvest records were combined with in situ daily weather series. Using Conditional Inference Forest and clustering techniques, we assessed the relationships between climatic factors and crop yield variability at the local scale for specific cultivars and growth stages. The analysis showed clear relationships in the various location-cultivar combinations, with climatic factors explaining 6 to 46% of spatiotemporal variability in yield, and with crop responses to weather being non-linear and cultivar-specific. Climatic factors affected cultivars differently during each stage of development. For instance, one cultivar was affected by high nighttime temperatures in the reproductive stage but responded positively to accumulated solar radiation during the ripening stage. Another was affected by high nighttime temperatures during both the vegetative and reproductive stages. Clustering of the weather patterns corresponding to individual cropping events revealed different groups of weather patterns for irrigated and rainfed systems with contrasting yield levels. Best-suited cultivars were identified for some weather patterns, making weather-site-specific recommendations possible. This study illustrates the potential of data mining for adding value to existing observational data in agriculture by allowing embedded knowledge to be quickly leveraged. It generates site-specific information on cultivar response to climatic factors and supports on-farm management decisions for adaptation to climate variability. PMID:27560980

Assessing Weather-Yield Relationships in Rice at Local Scale Using Data Mining Approaches.

PubMed

Delerce, Sylvain; Dorado, Hugo; Grillon, Alexandre; Rebolledo, Maria Camila; Prager, Steven D; Patiño, Victor Hugo; Garcés Varón, Gabriel; Jiménez, Daniel

2016-01-01

Seasonal and inter-annual climate variability have become important issues for farmers, and climate change has been shown to increase them. Simultaneously farmers and agricultural organizations are increasingly collecting observational data about in situ crop performance. Agriculture thus needs new tools to cope with changing environmental conditions and to take advantage of these data. Data mining techniques make it possible to extract embedded knowledge associated with farmer experiences from these large observational datasets in order to identify best practices for adapting to climate variability. We introduce new approaches through a case study on irrigated and rainfed rice in Colombia. Preexisting observational datasets of commercial harvest records were combined with in situ daily weather series. Using Conditional Inference Forest and clustering techniques, we assessed the relationships between climatic factors and crop yield variability at the local scale for specific cultivars and growth stages. The analysis showed clear relationships in the various location-cultivar combinations, with climatic factors explaining 6 to 46% of spatiotemporal variability in yield, and with crop responses to weather being non-linear and cultivar-specific. Climatic factors affected cultivars differently during each stage of development. For instance, one cultivar was affected by high nighttime temperatures in the reproductive stage but responded positively to accumulated solar radiation during the ripening stage. Another was affected by high nighttime temperatures during both the vegetative and reproductive stages. Clustering of the weather patterns corresponding to individual cropping events revealed different groups of weather patterns for irrigated and rainfed systems with contrasting yield levels. Best-suited cultivars were identified for some weather patterns, making weather-site-specific recommendations possible. This study illustrates the potential of data mining for adding value to existing observational data in agriculture by allowing embedded knowledge to be quickly leveraged. It generates site-specific information on cultivar response to climatic factors and supports on-farm management decisions for adaptation to climate variability.

Improved Rainfall Estimates and Predictions for 21st Century Drought Early Warning

NASA Technical Reports Server (NTRS)

Funk, Chris; Peterson, Pete; Shukla, Shraddhanand; Husak, Gregory; Landsfeld, Marty; Hoell, Andrew; Pedreros, Diego; Roberts, J. B.; Robertson, F. R.; Tadesse, Tsegae;

Quantifying alluvial fan sensitivity to climate in Death Valley, California, from field observations and numerical models

NASA Astrophysics Data System (ADS)

Brooke, Sam; Whittaker, Alexander; Armitage, John; D'Arcy, Mitch; Watkins, Stephen

2017-04-01

A quantitative understanding of landscape sensitivity to climate change remains a key challenge in the Earth Sciences. The stream-flow deposits of coupled catchment-fan systems offer one way to decode past changes in external boundary conditions as they comprise simple, closed systems that can be represented effectively by numerical models. Here we combine the collection and analysis of grain size data on well-dated alluvial fan surfaces in Death Valley, USA, with numerical modelling to address the extent to which sediment routing systems record high-frequency, high-magnitude climate change. We compile a new database of Holocene and Late-Pleistocene grain size trends from 11 alluvial fans in Death Valley, capturing high-resolution grain size data ranging from the Recent to 100 kyr in age. We hypothesise the observed changes in average surface grain size and fining rate over time are a record of landscape response to glacial-interglacial climatic forcing. With this data we are in a unique position to test the predictions of landscape evolution models and evaluate the extent to which climate change has influenced the volume and calibre of sediment deposited on alluvial fans. To gain insight into our field data and study area, we employ an appropriately-scaled catchment-fan model that calculates an eroded volumetric sediment budget to be deposited in a subsiding basin according to mass balance where grain size trends are predicted by a self-similarity fining model. We use the model to compare predicted trends in alluvial fan stratigraphy as a function of boundary condition change for a range of model parameters and input grain size distributions. Subsequently, we perturb our model with a plausible glacial-interglacial magnitude precipitation change to estimate the requisite sediment flux needed to generate observed field grain size trends in Death Valley. Modelled fluxes are then compared with independent measurements of sediment supply over time. Our results constitute one of the first attempts to combine the detailed collection of alluvial fan grain size data in time and space with coupled catchment-fan models, affording us the means to evaluate how well field and model data can be reconciled for simple sediment routing systems.

The International Arctic Buoy Programme (IABP) - An International Polar Year Every Year

NASA Astrophysics Data System (ADS)

Hanna, M.; Rigor, I.; Ortmeyer, M.; Haas, C.

2004-12-01

A network of automatic data buoys to monitor synoptic-scale fields of sea level pressure (SLP), surface air temperature (SAT), and ice motion throughout the Arctic Ocean was recommended by the U.S. National Academy of Sciences in 1974. Based on the Academy's recommendation, the Arctic Ocean Buoy Program was established by the Polar Science Center, Applied Physics Laboratory (APL), University of Washington, in 1978 to support the Global Weather Experiment. Operations began in early 1979, and the program continued through 1990 under funding from various agencies. In 1991, the International Arctic Buoy Programme (IABP) succeeded the Arctic Ocean Buoy Program, but the basic objective remains - to maintain a network of drifting buoys on the Arctic Ocean to provide meteorological and oceanographic data for real-time operational requirements and research purposes including support to the World Climate Research Programme and the World Weather Watch Programme. The IABP currently has 37 buoys deployed on the Arctic Ocean. Most of the buoys measure SLP and SAT, but many buoys are enhanced to measure other geophysical variables such as sea ice thickness, ocean temperature and salinity. This observational array is maintained by the 20 Participants from 10 different countries, who support the program through contributions of buoys, deployment logistics, and other services. The observations from the IABP are posted on the Global Telecommunications System for operational use, are archived at the World Data Center for Glaciology at the National Snow and Ice Data Center (http://nsidc.org), and can also be obtained from the IABP web server for research (http://iabp.apl.washington.edu). The observations from the IABP have been essential for: 1.) Monitoring Arctic and global climate change; 2.) Forecasting weather and sea ice conditions; 3.) Forcing, assimilation and validation of global weather and climate models; 4.) Validation of satellite data; etc. As of 2003, over 450 papers have been written using the observations collected by the IABP. The observations from IABP have been one of the cornerstones for environmental forecasting and studies of climate and climate change, i.e. many of the changes in Arctic climate were first observed or explained using data from the IABP. The IABP is also evolving to better support the operational and research requirements of the community. For example, some of the Participants of the IABP have been deploying buoys which not only measure SLP and SAT, but also ocean currents, temperatures and salinity. Other buoys have been enhanced to measure the ice mass balance (IMB) using thermistor strings and pingers aimed at the top and bottom of the sea ice. Some of these ocean and IMB buoys are deployed in close proximity to each other in order to provide a myriad of concurrent observations at a few points across the Arctic Ocean. From these data we can also estimate time variations in other geophysical variables such as oceanic heat storage and heat flux. These stations provide critical atmospheric, ice, and upper ocean hydrographic measurements that cannot be obtained by other means. The Arctic and global climate system is changing. These changes threaten our native cultures and ecosystems, but may also provide economic and social opportunities. In order to understand and respond to these changes, we need to sustain our current observational systems, and for the Arctic, the IABP provides the longest continuing record of observations.

Variability of Equatorward Transport in the Tropical Southwestern Pacific

NASA Astrophysics Data System (ADS)

Alberty, M. S.; Sprintall, J.; MacKinnon, J. A.; Cravatte, S. E.; Ganachaud, A. S.; Germineaud, C.

2016-02-01

Situated in the Pacific warm pool, the Solomon Sea is a semi-enclosed sea containing a system of low latitude Western boundary currents that serve as the primary source water for the Equatorial Undercurrent. The variability of equatorward heat and volume transport through the Solomon Sea has the capability to modulate regional and basin-scale climate processes, yet there are few and synoptic observations of these fluxes. Here we present the mean and variability of heat and volume transport out of the Solomon Sea observed during the MoorSPICE experiment. MoorSPICE is the Solomon Sea mooring-based observational component of the Southwest Pacific Ocean Circulation and Climate Experiment (SPICE), an international research project working to observe and improve our understanding of the southwest Pacific Ocean circulation and climate. Arrays of moorings were deployed in the outflow channels of the Solomon Sea for July 2012 until March 2014 to resolve the temperature and velocity fields in each strait. In particular we will discuss the phasing of the observed transport variability for each channel compared to that of the satellite-observed monsoonal wind forcing and annual cycle of the mesoscale eddy field.

Human activities and climate variability drive fast-paced change across the world's estuarine-coastal ecosystems

USGS Publications Warehouse

Cloern, James E.; Abreu, Paulo C.; Carstensen, Jacob; Chauvaud, Laurent; Elmgren, Ragnar; Grall, Jacques; Greening, Holly; Johansson, John O.R.; Kahru, Mati; Sherwood, Edward T.; Xu, Jie; Yin, Kedong

2016-01-01

Time series of environmental measurements are essential for detecting, measuring and understanding changes in the Earth system and its biological communities. Observational series have accumulated over the past 2–5 decades from measurements across the world's estuaries, bays, lagoons, inland seas and shelf waters influenced by runoff. We synthesize information contained in these time series to develop a global view of changes occurring in marine systems influenced by connectivity to land. Our review is organized around four themes: (i) human activities as drivers of change; (ii) variability of the climate system as a driver of change; (iii) successes, disappointments and challenges of managing change at the sea-land interface; and (iv) discoveries made from observations over time. Multidecadal time series reveal that many of the world's estuarine–coastal ecosystems are in a continuing state of change, and the pace of change is faster than we could have imagined a decade ago. Some have been transformed into novel ecosystems with habitats, biogeochemistry and biological communities outside the natural range of variability. Change takes many forms including linear and nonlinear trends, abrupt state changes and oscillations. The challenge of managing change is daunting in the coastal zone where diverse human pressures are concentrated and intersect with different responses to climate variability over land and over ocean basins. The pace of change in estuarine–coastal ecosystems will likely accelerate as the human population and economies continue to grow and as global climate change accelerates. Wise stewardship of the resources upon which we depend is critically dependent upon a continuing flow of information from observations to measure, understand and anticipate future changes along the world's coastlines.

Impacts of climate change and internal climate variability on french rivers streamflows

NASA Astrophysics Data System (ADS)

Dayon, Gildas; Boé, Julien; Martin, Eric

2016-04-01

The assessment of the impacts of climate change often requires to set up long chains of modeling, from the model to estimate the future concentration of greenhouse gases to the impact model. Throughout the modeling chain, sources of uncertainty accumulate making the exploitation of results for the development of adaptation strategies difficult. It is proposed here to assess the impacts of climate change on the hydrological cycle over France and the associated uncertainties. The contribution of the uncertainties from greenhouse gases emission scenario, climate models and internal variability are addressed in this work. To have a large ensemble of climate simulations, the study is based on Global Climate Models (GCM) simulations from the Coupled Model Intercomparison Phase 5 (CMIP5), including several simulations from the same GCM to properly assess uncertainties from internal climate variability. Simulations from the four Radiative Concentration Pathway (RCP) are downscaled with a statistical method developed in a previous study (Dayon et al. 2015). The hydrological system Isba-Modcou is then driven by the downscaling results on a 8 km grid over France. Isba is a land surface model that calculates the energy and water balance and Modcou a hydrogeological model that routes the surface runoff given by Isba. Based on that framework, uncertainties uncertainties from greenhouse gases emission scenario, climate models and climate internal variability are evaluated. Their relative importance is described for the next decades and the end of this century. In a last part, uncertainties due to internal climate variability on streamflows simulated with downscaled GCM and Isba-Modcou are evaluated against observations and hydrological reconstructions on the whole 20th century. Hydrological reconstructions are based on the downscaling of recent atmospheric reanalyses of the 20th century and observations of temperature and precipitation. We show that the multi-decadal variability of streamflows observed in the 20th century is generally weaker in the hydrological simulations done with the historical simulations from climate models. References: Dayon et al. (2015), Transferability in the future climate of a statistical downscaling mehtod for precipitation in France, J. Geophys. Res. Atmos., 120, 1023-1043, doi:10.1002/2014JD022236

Evaluating Transient Global and Regional Model Simulations: Bridging the Model/Observations Information Gap

NASA Astrophysics Data System (ADS)

Rutledge, G. K.; Karl, T. R.; Easterling, D. R.; Buja, L.; Stouffer, R.; Alpert, J.

2001-05-01

A major transition in our ability to evaluate transient Global Climate Model (GCM) simulations is occurring. Real-time and retrospective numerical weather prediction analysis, model runs, climate simulations and assessments are proliferating from a handful of national centers to dozens of groups across the world. It is clear that it is no longer sufficient for any one national center to develop its data services alone. The comparison of transient GCM results with the observational climate record is difficult for several reasons. One limitation is that the global distributions of a number of basic climate quantities, such as precipitation, are not well known. Similarly, observational limitations exist with model re-analysis data. Both the NCEP/NCAR, and the ECMWF, re-analysis eliminate the problems of changing analysis systems but observational data also contain time-dependant biases. These changes in input data are blended with the natural variability making estimates of true variability uncertain. The need for data homogeneity is critical to study questions related to the ability to evaluate simulation of past climate. One approach to correct for time-dependant biases and data sparse regions is the development and use of high quality 'reference' data sets. The primary U.S. National responsibility for the archive and service of weather and climate data rests with the National Climatic Data Center (NCDC). However, as supercomputers increase the temporal and spatial resolution of both Numerical Weather Prediction (NWP) and GCM models, the volume and varied formats of data presented for archive at NCDC, using current communications technologies and data management techniques is limiting the scientific access of these data. To address this ever expanding need for climate and NWP information, NCDC along with the National Center's for Environmental Prediction (NCEP) have initiated the NOAA Operational Model Archive and Distribution System (NOMADS). NOMADS is a collaboration between the Center for Ocean-Land-Atmosphere studies (COLA); the Geophysical Fluid Dynamics Laboratory (GFDL); the George Mason University (GMU); the National Center for Atmospheric Research (NCAR); the NCDC; NCEP; the Pacific Marine Environmental Laboratory (PMEL); and the University of Washington. The objective of the NOMADS is to preserve and provide retrospective access to GCM's and reference quality long-term observational and high volume three dimensional data as well as NCEP NWP models and re-start and re-analysis information. The creation of the NOMADS features a data distribution, format independent, methodology enabling scientific collaboration between researchers. The NOMADS configuration will allow a researcher to transparently browse, extract and intercompare retrospective observational and model data products from any of the participating centers. NOMADS will provide the ability to easily initialize and compare the results of ongoing climate model assessments and NWP output. Beyond the ingest and access capability soon to be implemented with NOMADS is the challenge of algorithm development for the inter-comparison of large-array data (e.g., satellite and radar) with surface, upper-air, and sub-surface ocean observational data. The implementation of NOMADS should foster the development of new quality control processes by taking advantage of distributed data access.

Long-term active-layer dynamics: results of 22 years of field observations in Northern Hemisphere permafrost regions.

NASA Astrophysics Data System (ADS)

Shiklomanov, N. I.; Nelson, F. E.; Streletskiy, D. A.; Klene, A. E.; Biskaborn, B. K.

2016-12-01

The uppermost layer of seasonal thawing above permafrost (the active layer) is an important regulator of energy and mass fluxes between the surface and the atmosphere in the polar regions. Active layer monitoring is an important component of efforts to assess the effects of global change in permafrost environments. The Circumpolar Active Layer Monitoring (CALM) program, established in the early 1990s, is designed to observe temporal and spatial variability of the active layer and its response to changes and variations in climatic conditions. The CALM network is an integral part of the Global Terrestrial Network for Permafrost (GTN-P), operating under the auspices of the Global Terrestrial Observing System (GTOS) /Global Climate Observing System (GCOS). Standardized thaw depth observations in the Northern Hemisphere are available for more than 200 GTN-P/CALM sites in the Northern Hemisphere. At each of the sites spatially distributed ALT measurements have been conducted annually by mechanical probing. The locations of sites represent generalized surface and subsurface conditions characteristic of broader regions. The data are assimilated and distributed though the CALM (www.gwu.edu/ calm) and GTN-P (gtnpdatabase.org) online databases. In this presentation we use data from approximately 20 years of continuous observations to examine temporal trends in active-layer thickness for several representative Arctic regions. Results indicate substantial interannual fluctuations in active-layer thickness, primarily in response to variations in air temperature. Decadal trends in ALT vary by region. A progressive increase in ALT has been observed in the Nordic countries, the Russian European North, West Siberia, East Siberia, the Russian Far East, and the Interior of Alaska. North American Arctic sites show no apparent thaw depth trend over 22-years of record. However, combined active layer, ground temperature and heave/subsidence observations conducted in northern Alaska demonstrate a complex, non-linear response of the active-layer/upper permafrost system to changes in climatic conditions.

A global validation of ERA-Interim integrated water vapor estimates using ground-based GNSS observations

NASA Astrophysics Data System (ADS)

Ahmed, F.; Dousa, J.; Hunegnaw, A.; Teferle, F. N.; Bingley, R.

2017-12-01

Integrated water vapor (IWV) derived from climate reanalysis models, such as the European Centre for Medium-range Weather Forecasts (ECMWF) ReAnalysis-Interim (ERA-Interim), is widely used in many atmospheric applications. Therefore, it is of interest to assess the quality of this reanalysis product using available observations. Observations from Global Navigation Satellite Systems (GNSS) are, as of now, available for a period of over 2 decades and their global availability makes it possible to validate the IWV obtained from climate reanalysis models in different geographical and climatic regions. In this study, primarily, three 5-year long homogeneously reprocessed GNSS-derived IWV datasets containing over 400 globally distributed ground-based GNSS stations have been used to validate the IWV estimates obtained from the ERA-Interim climate reanalysis model in 25 different climate zones. The IWV from ERA-Interim has been obtained by vertically integrating the specific humidity at all model levels above the locations of GNSS stations. It has been studied how the difference between the ERA-Interim IWV and the GNSS-derived IWV varies with respect to the different climate zones as well as with respect to the difference in the model orography and latitude. The results show a dependence of the ability of ERA-Interim to model the IWV on difference in climate types and latitude. This dependence, however, is dictated by the concentration of water vapor in different climate zones and at different latitudes. Furthermore, as a secondary focus of this study, the weighted mean atmospheric temperature (Tm) obtained from ERA-Interim has been compared to its equivalent obtained using two widely used approximations globally.

University of Rhode Island Regional Earth Systems Center

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

Rothstein, Lewis; Cornillon, P.

The primary objective of this program was to establish the URI Regional Earth System Center (“Center”) that would enhance overall societal wellbeing (health, financial, environmental) by utilizing the best scientific information and technology to achieve optimal policy decisions with maximum stakeholder commitment for energy development, coastal environmental management, water resources protection and human health protection, while accelerating regional economic growth. The Center was to serve to integrate existing URI institutional strengths in energy, coastal environmental management, water resources, and human wellbeing. This integrated research, educational and public/private sector outreach Center was to focus on local, state and regional resources. Themore » centerpiece activity of the Center was in the development and implementation of integrated assessment models (IAMs) that both ‘downscaled’ global observations and interpolated/extrapolated regional observations for analyzing the complexity of interactions among humans and the natural climate system to further our understanding and, ultimately, to predict the future state of our regional earth system. The Center was to begin by first ‘downscaling’ existing global earth systems management tools for studying the causes of local, state and regional climate change and potential social and environmental consequences, with a focus on the regional resources identified above. The Center would ultimately need to address the full feedbacks inherent in the nonlinear earth systems by quantifying the “upscaled” impacts of those regional changes on the global earth system. Through an interacting suite of computer simulations that are informed by observations from the nation’s evolving climate observatories, the Center activities integrates climate science, technology, economics, and social policy into forecasts that will inform solutions to pressing issues in regional climate change science, ‘green economy’ investment and climate policy. These project objectives were designed as part of a 5-year program, which would have constituted the initial phase for the establishment of the Center. Almost immediately (i.e. before receiving even the first year of funding) we were informed that we would not be receiving any funding beyond the initial phase; one year. This seriously impacted our ability to deliver on our objectives and, with that, a re-scoping of the Center priorities was designed to fit the 1-year constraints on funding. It was decided that, given the Center’s emphasis on building IAMs, the best way to proceed was to first focus on one particularly important component of the IAM – a natural sciences model that would be useful for research and forecasting of the circualation/ecology/biogeochemistry of RI’s coastal waters. We have succeeded on that necessarily more limited objective, as we will describe below.« less

Observations, inferences, and mechanisms of the Atlantic Meridional Overturning Circulation: A review

NASA Astrophysics Data System (ADS)

Buckley, Martha W.; Marshall, John

2016-03-01

This is a review about the Atlantic Meridional Overturning Circulation (AMOC), its mean structure, temporal variability, controlling mechanisms, and role in the coupled climate system. The AMOC plays a central role in climate through its heat and freshwater transports. Northward ocean heat transport achieved by the AMOC is responsible for the relative warmth of the Northern Hemisphere compared to the Southern Hemisphere and is thought to play a role in setting the mean position of the Intertropical Convergence Zone north of the equator. The AMOC is a key means by which heat anomalies are sequestered into the ocean's interior and thus modulates the trajectory of climate change. Fluctuations in the AMOC have been linked to low-frequency variability of Atlantic sea surface temperatures with a host of implications for climate variability over surrounding landmasses. On intra-annual timescales, variability in AMOC is large and primarily reflects the response to local wind forcing; meridional coherence of anomalies is limited to that of the wind field. On interannual to decadal timescales, AMOC changes are primarily geostrophic and related to buoyancy anomalies on the western boundary. A pacemaker region for decadal AMOC changes is located in a western "transition zone" along the boundary between the subtropical and subpolar gyres. Decadal AMOC anomalies are communicated meridionally from this region. AMOC observations, as well as the expanded ocean observational network provided by the Argo array and satellite altimetry, are inspiring efforts to develop decadal predictability systems using coupled atmosphere-ocean models initialized by ocean data.

Climatic Variability Leads to Later Seasonal Flowering of Floridian Plants

PubMed Central

Von Holle, Betsy; Wei, Yun; Nickerson, David

2010-01-01

Understanding species responses to global change will help predict shifts in species distributions as well as aid in conservation. Changes in the timing of seasonal activities of organisms over time may be the most responsive and easily observable indicator of environmental changes associated with global climate change. It is unknown how global climate change will affect species distributions and developmental events in subtropical ecosystems or if climate change will differentially favor nonnative species. Contrary to previously observed trends for earlier flowering onset of plant species with increasing spring temperatures from mid and higher latitudes, we document a trend for delayed seasonal flowering among plants in Florida. Additionally, there were few differences in reproductive responses by native and nonnative species to climatic changes. We argue that plants in Florida have different reproductive cues than those from more northern climates. With global change, minimum temperatures have become more variable within the temperate-subtropical zone that occurs across the peninsula and this variation is strongly associated with delayed flowering among Florida plants. Our data suggest that climate change varies by region and season and is not a simple case of species responding to consistently increasing temperatures across the region. Research on climate change impacts need to be extended outside of the heavily studied higher latitudes to include subtropical and tropical systems in order to properly understand the complexity of regional and seasonal differences of climate change on species responses. PMID:20657765

Collaboration pathway(s) using new tools for optimizing `operational' climate monitoring from space

NASA Astrophysics Data System (ADS)

Helmuth, Douglas B.; Selva, Daniel; Dwyer, Morgan M.

2015-09-01

Consistently collecting the earth's climate signatures remains a priority for world governments and international scientific organizations. Architecting a long term solution requires transforming scientific missions into an optimized robust `operational' constellation that addresses the collective needs of policy makers, scientific communities and global academic users for trusted data. The application of new tools offers pathways for global architecture collaboration. Recent rule-based expert system (RBES) optimization modeling of the intended NPOESS architecture becomes a surrogate for global operational climate monitoring architecture(s). These rulebased systems tools provide valuable insight for global climate architectures, by comparison/evaluation of alternatives and the sheer range of trade space explored. Optimization of climate monitoring architecture(s) for a partial list of ECV (essential climate variables) is explored and described in detail with dialogue on appropriate rule-based valuations. These optimization tool(s) suggest global collaboration advantages and elicit responses from the audience and climate science community. This paper will focus on recent research exploring joint requirement implications of the high profile NPOESS architecture and extends the research and tools to optimization for a climate centric case study. This reflects work from SPIE RS Conferences 2013 and 2014, abridged for simplification30, 32. First, the heavily securitized NPOESS architecture; inspired the recent research question - was Complexity (as a cost/risk factor) overlooked when considering the benefits of aggregating different missions into a single platform. Now years later a complete reversal; should agencies considering Disaggregation as the answer. We'll discuss what some academic research suggests. Second, using the GCOS requirements of earth climate observations via ECV (essential climate variables) many collected from space-based sensors; and accepting their definitions of global coverages intended to ensure the needs of major global and international organizations (UNFCCC and IPCC) are met as a core objective. Consider how new optimization tools like rule-based engines (RBES) offer alternative methods of evaluating collaborative architectures and constellations? What would the trade space of optimized operational climate monitoring architectures of ECV look like? Third, using the RBES tool kit (2014) demonstrate with application to a climate centric rule-based decision engine - optimizing architectural trades of earth observation satellite systems, allowing comparison(s) to existing architectures and gaining insights for global collaborative architectures. How difficult is it to pull together an optimized climate case study - utilizing for example 12 climate based instruments on multiple existing platforms and nominal handful of orbits; for best cost and performance benefits against the collection requirements of representative set of ECV. How much effort and resources would an organization expect to invest to realize these analysis and utility benefits?

Emerging Cyber Infrastructure for NASA's Large-Scale Climate Data Analytics

NASA Astrophysics Data System (ADS)

Duffy, D.; Spear, C.; Bowen, M. K.; Thompson, J. H.; Hu, F.; Yang, C. P.; Pierce, D.

2016-12-01

The resolution of NASA climate and weather simulations have grown dramatically over the past few years with the highest-fidelity models reaching down to 1.5 KM global resolutions. With each doubling of the resolution, the resulting data sets grow by a factor of eight in size. As the climate and weather models push the envelope even further, a new infrastructure to store data and provide large-scale data analytics is necessary. The NASA Center for Climate Simulation (NCCS) has deployed the Data Analytics Storage Service (DASS) that combines scalable storage with the ability to perform in-situ analytics. Within this system, large, commonly used data sets are stored in a POSIX file system (write once/read many); examples of data stored include Landsat, MERRA2, observing system simulation experiments, and high-resolution downscaled reanalysis. The total size of this repository is on the order of 15 petabytes of storage. In addition to the POSIX file system, the NCCS has deployed file system connectors to enable emerging analytics built on top of the Hadoop File System (HDFS) to run on the same storage servers within the DASS. Coupled with a custom spatiotemporal indexing approach, users can now run emerging analytical operations built on MapReduce and Spark on the same data files stored within the POSIX file system without having to make additional copies. This presentation will discuss the architecture of this system and present benchmark performance measurements from traditional TeraSort and Wordcount to large-scale climate analytical operations on NetCDF data.

A seasonal hydrologic ensemble prediction system for water resource management

NASA Astrophysics Data System (ADS)

Luo, L.; Wood, E. F.

2006-12-01

A seasonal hydrologic ensemble prediction system, developed for the Ohio River basin, has been improved and expanded to several other regions including the Eastern U.S., Africa and East Asia. The prediction system adopts the traditional Extended Streamflow Prediction (ESP) approach, utilizing the VIC (Variable Infiltration Capacity) hydrological model as the central tool for producing ensemble prediction of soil moisture, snow and streamflow with lead times up to 6-month. VIC is forced by observed meteorology to estimate the hydrological initial condition prior to the forecast, but during the forecast period the atmospheric forcing comes from statistically downscaled, seasonal forecast from dynamic climate models. The seasonal hydrologic ensemble prediction system is currently producing realtime seasonal hydrologic forecast for these regions on a monthly basis. Using hindcasts from a 19-year period (1981-1999), during which seasonal hindcasts from NCEP Climate Forecast System (CFS) and European Union DEMETER project are available, we evaluate the performance of the forecast system over our forecast regions. The evaluation shows that the prediction system using the current forecast approach is able to produce reliable and accurate precipitation, soil moisture and streamflow predictions. The overall skill is much higher then the traditional ESP. In particular, forecasts based on multiple climate model forecast are more skillful than single model-based forecast. This emphasizes the significant need for producing seasonal climate forecast with multiple climate models for hydrologic applications. Forecast from this system is expected to provide very valuable information about future hydrologic states and associated risks for end users, including water resource management and financial sectors.

Cloud Microphysical Properties in Mesoscale Convective Systems: An Intercomparison of Three Tropical Locations

NASA Astrophysics Data System (ADS)

Fontaine, Emmanuel; Leroy, Delphine; Schwarzenboeck, Alfons; Coutris, Pierre; Delanoë, Julien; Protat, Alain; Dezitter, Fabien; Grandin, Alice; Strapp, John W.; Lilie, Lyle E.

2017-04-01

Mesoscale Convective Systems are complex cloud systems which are primarily the result of specific synoptic conditions associated with mesoscale instabilities leading to the development of cumulonimbus type clouds (Houze, 2004). These systems can last several hours and can affect human societies in various ways. In general, weather and climate models use simplistic schemes to describe ice hydrometeors' properties. However, MCS are complex cloud systems where the dynamic, radiative and precipitation processes depend on spatiotemporal location in the MCS (Houze, 2004). As a consequence, hydrometeor growth processes in MCS vary in space and time, thereby impacting shape and concentration of ice crystals and finally CWC. As a consequence, differences in the representation of ice properties in models (Li et al., 2007, 2005) lead to significant disagreements in the quantification of ice cloud effects on climate evolution (Intergovernmental Panel on Climate Change Fourth Assessment Report). An accurate estimation of the spatiotemporal CWC distribution is therefore a key parameter for evaluating and improving numerical weather prediction (Stephens et al., 2002). The main purpose of this study is to show ice microphysical properties of MCS observed in three different locations in the tropical atmosphere: West-African continent, Indian Ocean, and Northern Australia. An intercomparison study is performed in order to quantify how similar or different are the ice hydrometeors' properties in these three regions related to radar reflectivity factors and temperatures observed in respective MCS.

Phenology at the crossroads?

NASA Astrophysics Data System (ADS)

Menzel, Annette

2014-05-01

Phenology is the study of the timing of natural events such as plant growth or animal migration. Currently nearly 500 papers are published annually that include 'phenolog*' in their title; many are related to anthropogenic change. Since seasonal events are triggered predominantly by climate, phenology has emerged as a key asset in identifying fingerprints of climate change in natural systems, especially since recent warming has been mirrored by significantly advancing spring events. Phenological changes have been reported across continents, habitats and taxa, predominantly as mean temporal changes ('trends') or as relationships to temperature and other drivers ('responses'), and have been summarised in various meta-analyses. However, a considerable variability in observed trends and responses is reported along with mixed messages of the footprint of climate change in nature. Phenology has made considerable advances but is a crossroads of understanding this variability. At the same time a change of emphasis in explanation, prediction and adaptation is emerging, which needs a full acknowledgement of this variability; likely yielding to more plasticity and resilience. In this review, I summarize current knowledge and recent insights into the role of • different observation methods, their accuracy and their target phenophases • observed events, species, traits, ontogenetic effects • species-specific safeguarding strategies, e.g. chilling, photoperiod • additional drivers other than climate, e.g. nutrients, GHG, biotic effects, anthropogenic / agricultural management • seasonal as well as spatio-temporal variation, effects of regional climate changes and analogous climates. This review clearly demonstrated that, comparable to weather and climate ensembles, only a full consideration of variation in responses allows a complete understanding of ecological, cultural and socioeconomic consequences of these phenological changes.

Capturing spatial heterogeneity of soil organic carbon under changing climate

NASA Astrophysics Data System (ADS)

Mishra, U.; Fan, Z.; Jastrow, J. D.; Matamala, R.; Vitharana, U.

2015-12-01

The spatial heterogeneity of the land surface affects water, energy, and greenhouse gas exchanges with the atmosphere. Designing observation networks that capture land surface spatial heterogeneity is a critical scientific challenge. Here, we present a geospatial approach to capture the existing spatial heterogeneity of soil organic carbon (SOC) stocks across Alaska, USA. We used the standard deviation of 556 georeferenced SOC profiles previously compiled in Mishra and Riley (2015, Biogeosciences, 12:3993-4004) to calculate the number of observations that would be needed to reliably estimate Alaskan SOC stocks. This analysis indicated that 906 randomly distributed observation sites would be needed to quantify the mean value of SOC stocks across Alaska at a confidence interval of ± 5 kg m-2. We then used soil-forming factors (climate, topography, land cover types, surficial geology) to identify the locations of appropriately distributed observation sites by using the conditioned Latin hypercube sampling approach. Spatial correlation and variogram analyses demonstrated that the spatial structures of soil-forming factors were adequately represented by these 906 sites. Using the spatial correlation length of existing SOC observations, we identified 484 new observation sites would be needed to provide the best estimate of the present status of SOC stocks in Alaska. We then used average decadal projections (2020-2099) of precipitation, temperature, and length of growing season for three representative concentration pathway (RCP 4.5, 6.0, and 8.5) scenarios of the Intergovernmental Panel on Climate Change to investigate whether the location of identified observation sites will shift/change under future climate. Our results showed 12-41 additional observation sites (depending on emission scenarios) will be required to capture the impact of projected climatic conditions by 2100 on the spatial heterogeneity of Alaskan SOC stocks. Our results represent an ideal distribution of observation sites across Alaska that captures the land surface spatial heterogeneity and can be used in efforts to quantify SOC stocks, monitor greenhouse gas emissions, and benchmark Earth System Model results.

EO based Agro-ecosystem approach for climate change adaptation in enhancing the crop production efficiency in the Indo-gangetic plains of India

NASA Astrophysics Data System (ADS)

Pandey, Suraj

This study develops a spatial mapping of agro-ecological zones based on earth observation model using MODIS regional dataset as a tool to guide key areas of cropping system and targeting to climate change strategies. This tool applies to the Indo-gangetic Plains of north India to target the domains of bio-physical characteristics and socio-economics with respect to changing climate in the region. It derive on secondary data for spatially-explicit variables at the state/district level, which serve as indicators of climate variability based on sustainable livelihood approach, natural, social and human. The study details the methodology used and generates the spatial climate risk maps for composite indicators of livelihood and vulnerability index in the region.

Solving the Global Climate Monitoring Problem in the Atmosphere: Towards SI-tied Climate Records with Integrated Uncertainty Propagation

NASA Astrophysics Data System (ADS)

Kirchengast, G.; Schwaerz, M.; Fritzer, J.; Schwarz, J.; Scherllin-Pirscher, B.; Steiner, A. K.

2013-12-01

Monitoring the atmosphere to gain accurate and long-term stable records of essential climate variables (ECVs) such as temperature and greenhouse gases is the backbone of contemporary atmospheric and climate science. Earth observation from space is the key to obtain such data globally in the atmosphere. Currently, however, not any existing satellite-based atmospheric ECV record can serve as authoritative benchmark over months to decades so that climate variability and change in the atmosphere are not yet reliably monitored. Radio occultation (RO) using Global Navigation Satellite System (GNSS) signals provides a unique opportunity to solve this problem in the free atmosphere (from ~1-2 km altitude upwards) for core ECVs: the thermodynamic variables temperature and pressure, and to some degree water vapor, which are key parameters for tracking climate change. On top of RO we have recently conceived next-generation methods, microwave and infrared-laser occultation and nadir-looking infrared-laser reflectometry. These can monitor a full set of thermo-dynamic ECVs (incl. wind) as well as the greenhouse gases such as carbon dioxide and methane as main drivers of climate change; for the latter we also target the boundary layer for tracking carbon sources and sinks. We briefly introduce to why the atmospheric climate monitoring challenge is unsolved so far and why just the above methods have the capabilities to break through. We then focus on RO, which already provided more than a decade of observations. RO accurately measures time delays from refraction of GNSS signals during atmospheric occultation events. This enables to tie RO-derived ECVs and their uncertainty to fundamental time standards, effectively the SI second, and to their unique long-term stability and narrow uncertainty. However, despite impressive advances since the pioneering RO mission GPS/Met in the mid-1990ties no rigorous trace from fundamental time to the ECVs (duly accounting also for relevant side influences) exists so far. Establishing such a trace first-time in form of the Reference Occultation Processing System rOPS, providing reference RO data for climate science and applications, is therefore a current cornerstone endeavor at the Wegener Center over 2011 to 2015, supported also by colleagues from other key groups at EUMETSAT Darmstadt, UCAR Boulder, DMI Copenhagen, ECMWF Reading, IAP Moscow, AIUB Berne, and RMIT Melbourne. With the rOPS we undertake to process the full chain from the SI-tied raw data to the atmospheric ECVs with integrated uncertainty propagation. We summarize where we currently stand in quantifying RO accuracy and long-term stability and then discuss the concept, development status and initial results from the rOPS, with emphasis on its novel capability to provide SI-tied reference data with integrated uncertainty estimation. We comment how these data can provide ground-breaking support to challenges such as climate model evaluation, anthropogenic change detection and attribution, and calibration of complementary climate observing systems.

Enhancing Famine Early Warning Systems with Improved Forecasts, Satellite Observations and Hydrologic Simulations

NASA Astrophysics Data System (ADS)

Funk, C. C.; Verdin, J.; Thiaw, W. M.; Hoell, A.; Korecha, D.; McNally, A.; Shukla, S.; Arsenault, K. R.; Magadzire, T.; Novella, N.; Peters-Lidard, C. D.; Robjohn, M.; Pomposi, C.; Galu, G.; Rowland, J.; Budde, M. E.; Landsfeld, M. F.; Harrison, L.; Davenport, F.; Husak, G. J.; Endalkachew, E.

2017-12-01

Drought early warning science, in support of famine prevention, is a rapidly advancing field that is helping to save lives and livelihoods. In 2015-2017, a series of extreme droughts afflicted Ethiopia, Southern Africa, Eastern Africa in OND and Eastern Africa in MAM, pushing more than 50 million people into severe food insecurity. Improved drought forecasts and monitoring tools, however, helped motivate and target large and effective humanitarian responses. Here we describe new science being developed by a long-established early warning system - the USAID Famine Early Warning Systems Network (FEWS NET). FEWS NET is a leading provider of early warning and analysis on food insecurity. FEWS NET research is advancing rapidly on several fronts, providing better climate forecasts and more effective drought monitoring tools that are being used to support enhanced famine early warning. We explore the philosophy and science underlying these successes, suggesting that a modal view of climate change can support enhanced seasonal prediction. Under this modal perspective, warming of the tropical oceans may interact with natural modes of variability, like the El Niño-Southern Oscillation, to enhance Indo-Pacific sea surface temperature gradients during both El Niño and La Niña-like climate states. Using empirical data and climate change simulations, we suggest that a sequence of droughts may commence in northern Ethiopia and Southern Africa with the advent of a moderate-to-strong El Niño, and then continue with La Niña/West Pacific related droughts in equatorial eastern East Africa. Scientifically, we show that a new hybrid statistical-dynamic precipitation forecast system, the FEWS NET Integrated Forecast System (FIFS), based on reformulations of the Global Ensemble Forecast System weather forecasts and National Multi-Model Ensemble (NMME) seasonal climate predictions, can effectively anticipate recent East and Southern African drought events. Using cross-validation, we evaluate FIFS' skill and compare it to the NMME and the International Research Institute forecasts. Our study concludes with an overview of the satellite observations provided by FEWS NET partners at NOAA, NASA, USGS, and UC Santa Barbara, and the assimilation of these products within the FEWS NET Land Data Assimilation System (FLDAS).

Unmanned Aerial Systems, Moored Balloons, and the U.S. Department of Energy ARM Facilities in Alaska

NASA Astrophysics Data System (ADS)

Ivey, Mark; Verlinde, Johannes

2014-05-01

The U.S. Department of Energy (DOE), through its scientific user facility, the Atmospheric Radiation Measurement (ARM) Climate Research Facility, provides scientific infrastructure and data to the international Arctic research community via its research sites located on the North Slope of Alaska. Facilities and infrastructure to support operations of unmanned aerial systems for science missions in the Arctic and North Slope of Alaska were established at Oliktok Point Alaska in 2013. Tethered instrumented balloons will be used in the near future to make measurements of clouds in the boundary layer including mixed-phase clouds. The DOE ARM Program has operated an atmospheric measurement facility in Barrow, Alaska, since 1998. Major upgrades to this facility, including scanning radars, were added in 2010. Arctic Observing Networks are essential to meet growing policy, social, commercial, and scientific needs. Calibrated, high-quality arctic geophysical datasets that span ten years or longer are especially important for climate studies, climate model initializations and validations, and for related climate policy activities. For example, atmospheric data and derived atmospheric forcing estimates are critical for sea-ice simulations. International requirements for well-coordinated, long-term, and sustained Arctic Observing Networks and easily-accessible data sets collected by those networks have been recognized by many high-level workshops and reports (Arctic Council Meetings and workshops, National Research Council reports, NSF workshops and others). The recent Sustaining Arctic Observation Network (SAON) initiative sponsored a series of workshops to "develop a set of recommendations on how to achieve long-term Arctic-wide observing activities that provide free, open, and timely access to high-quality data that will realize pan-Arctic and global value-added services and provide societal benefits." This poster will present information on opportunities for members of the arctic research community to make atmospheric measurements using unmanned aerial systems or tethered balloons.

The Staring OBservations of the Atmosphere (SOBA) Mission Concept

NASA Technical Reports Server (NTRS)

Knobelspiesse, Kirk; Johnson, Matthew S.; Chen, Rick; Quincy, Allison; Fladeland, Matthew

2016-01-01

The Staring OBservations of the Atmosphere (SOBA) Mission is a concept that was developed and matured under the guidance of the NASA Ames Project EXellence (APEX) program. If funded, it will provide an unprecedented opportunity to improve ash transport forecasts and climate model simulations associated with volcanic eruptions. NASA and National science objectives require a better understanding of volcanic aerosol and trace gas emissions, transport, chemical transformation, and deposition, since they impact Earth's climate and atmospheric composition, human health, and aviation safety. Natural hazards such as the 2010 eruption of the Eyjafjallajökull volcano in Iceland demonstrated how existing remote-sensing assets were inadequate for individual volcanic event monitoring. During this eruption, available instruments were unable to provide data necessary to initialize volcanic plume transport models so that they could accurately predict the quantity and location of volcanic ash. As a result, thousands of flights around the world were grounded unnecessarily, at great expense. Volcanoes can also play a large role in regulation of the Earth's climate, so SOBA observations will also be used to evaluate and improve volcanic aerosol and trace gas simulation in chemical transport models (CTMs) and global climate models (GCMs). We propose the development of an airborne remote sensing concept and field campaign that will respond to an eruption and provide near real time observations of a volcanic plume, specifically ash injection height, transport, aerosol microphysical physical properties, and the location and concentration of sulfur dioxide (SO2) (sulfate (SO42-) aerosol precursor). This airborne system will utilize a depolarization sensitive, downward looking Light Detection And Ranging (lidar) instrument and an ultraviolet (UV) imaging spectrometer, and will provide data to be ingested by volcanic ash advisory models. Furthermore, the lessons learned in the development of this system could eventually guide regular deployment of similar systems by NASA or other government agencies.

The role of declining summer sea ice extent in increasing Arctic winter precipitation

NASA Astrophysics Data System (ADS)

Hamman, J.; Roberts, A.; Cassano, J. J.; Nijssen, B.

2016-12-01

In the past three decades, the Arctic has experienced large declines in summer sea ice cover, permafrost extent, and spring snow cover, and increases in winter precipitation. This study explores the relationship between declining Arctic sea ice extent (IE) and winter precipitation (WP) across the Arctic land masses. The first part of this presentation presents the observed relationship between IE and WP. Using satellite estimates of IE and WP data based on a combination of in-situ observations and global reanalyses, we show that WP is negatively correlated with summer IE and that this relationship is strongest before the year 2000. After 2000, around the time IE minima began to decline most rapidly, the relationship between IE and WP degenerates. This indicates that other processes are driving changes in IE and WP. We hypothesize that positive anomalies in poleward moisture transport have historically driven anomalously low IE and high WP, and that since the significant decline in IE, moisture divergence from the central Arctic has been a larger contributor to WP over land. To better understand the physical mechanisms driving the observed changes in the Arctic climate system and the sensitivity of the Arctic climate system to declining sea ice, we have used the fully-coupled Regional Arctic System Model (RASM) to simulate two distinct sea ice climates. The first climate represents normal IE, while the second includes reduced summer IE. The second portion of this presentation analyzes these two RASM simulations, in conjunction with our observation-based analysis, to understand the coupled relationship between poleward moisture transport, IE, evaporation from the Arctic Ocean, and precipitation. We will present the RASM-simulated Arctic water budget and demonstrate the role of IE in driving WP anomalies. Finally, a spatial correlation analysis identifies characteristic patterns in IE, ocean evaporation, and polar cap convergence that contribute to anomalies in WP.

Chapter 3: Photovoltaic Module Stability and Reliability

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

Jordan, Dirk; Kurtz, Sarah

2017-01-01

Profits realized from investment in photovoltaic will benefit from decades of reliable operation. Service life prediction through accelerated tests is only possible if indoor tests duplicate power loss and failure modes observed in fielded systems. Therefore, detailing and quantifying power loss and failure modes is imperative. In the first section, we examine recent trends in degradation rates, the gradual power loss observed for different technologies, climates and other significant factors. In the second section, we provide a summary of the most commonly observed failure modes in fielded systems.

The Climate Science Special Report: Detection and Attribution

NASA Astrophysics Data System (ADS)

Wehner, M. F.

2017-12-01

The Climate Science Special Report reiterates previous findings about the human influence on global mean surface air temperature with the statement "…it is extremely likely that human activities, especially emissions of greenhouse gases, are the dominant cause of the observed warming since the mid 20th century. For the warming over the last century, there is no convincing alternative explanation supported by the extent of the observational evidence." This is a statement made with high confidence and supported by multiple lines of evidence. The report also assesses the latest developments in the field of probabilistic extreme event attribution—the quantification of the influence of anthropogenic climate change on individual extreme weather events—with a focus on those recent events within the United States that have been analyzed. Thirty different events within the US are reported on including heat waves, cold snaps, wet seasons, individual storms and droughts. Most but not all of the individual US events studied revealed an influence from human induced changes to the climate system.

A dataset mapping the potential biophysical effects of vegetation cover change

NASA Astrophysics Data System (ADS)

Duveiller, Gregory; Hooker, Josh; Cescatti, Alessandro

2018-02-01

Changing the vegetation cover of the Earth has impacts on the biophysical properties of the surface and ultimately on the local climate. Depending on the specific type of vegetation change and on the background climate, the resulting competing biophysical processes can have a net warming or cooling effect, which can further vary both spatially and seasonally. Due to uncertain climate impacts and the lack of robust observations, biophysical effects are not yet considered in land-based climate policies. Here we present a dataset based on satellite remote sensing observations that provides the potential changes i) of the full surface energy balance, ii) at global scale, and iii) for multiple vegetation transitions, as would now be required for the comprehensive evaluation of land based mitigation plans. We anticipate that this dataset will provide valuable information to benchmark Earth system models, to assess future scenarios of land cover change and to develop the monitoring, reporting and verification guidelines required for the implementation of mitigation plans that account for biophysical land processes.

A dataset mapping the potential biophysical effects of vegetation cover change

PubMed Central

Duveiller, Gregory; Hooker, Josh; Cescatti, Alessandro

2018-01-01

Changing the vegetation cover of the Earth has impacts on the biophysical properties of the surface and ultimately on the local climate. Depending on the specific type of vegetation change and on the background climate, the resulting competing biophysical processes can have a net warming or cooling effect, which can further vary both spatially and seasonally. Due to uncertain climate impacts and the lack of robust observations, biophysical effects are not yet considered in land-based climate policies. Here we present a dataset based on satellite remote sensing observations that provides the potential changes i) of the full surface energy balance, ii) at global scale, and iii) for multiple vegetation transitions, as would now be required for the comprehensive evaluation of land based mitigation plans. We anticipate that this dataset will provide valuable information to benchmark Earth system models, to assess future scenarios of land cover change and to develop the monitoring, reporting and verification guidelines required for the implementation of mitigation plans that account for biophysical land processes. PMID:29461538

Toward Process-resolving Synthesis and Prediction of Arctic Climate Change Using the Regional Arctic System Model

NASA Astrophysics Data System (ADS)

Maslowski, W.

2017-12-01

The Regional Arctic System Model (RASM) has been developed to better understand the operation of Arctic System at process scale and to improve prediction of its change at a spectrum of time scales. RASM is a pan-Arctic, fully coupled ice-ocean-atmosphere-land model with marine biogeochemistry extension to the ocean and sea ice models. The main goal of our research is to advance a system-level understanding of critical processes and feedbacks in the Arctic and their links with the Earth System. The secondary, an equally important objective, is to identify model needs for new or additional observations to better understand such processes and to help constrain models. Finally, RASM has been used to produce sea ice forecasts for September 2016 and 2017, in contribution to the Sea Ice Outlook of the Sea Ice Prediction Network. Future RASM forecasts, are likely to include increased resolution for model components and ecosystem predictions. Such research is in direct support of the US environmental assessment and prediction needs, including those of the U.S. Navy, Department of Defense, and the recent IARPC Arctic Research Plan 2017-2021. In addition to an overview of RASM technical details, selected model results are presented from a hierarchy of climate models together with available observations in the region to better understand potential oceanic contributions to polar amplification. RASM simulations are analyzed to evaluate model skill in representing seasonal climatology as well as interannual and multi-decadal climate variability and predictions. Selected physical processes and resulting feedbacks are discussed to emphasize the need for fully coupled climate model simulations, high model resolution and sensitivity of simulated sea ice states to scale dependent model parameterizations controlling ice dynamics, thermodynamics and coupling with the atmosphere and ocean.

A Seamless Framework for Global Water Cycle Monitoring and Prediction

NASA Astrophysics Data System (ADS)

Sheffield, J.; Wood, E. F.; Chaney, N.; Fisher, C. K.; Caylor, K. K.

2013-12-01

The Global Earth Observation System of Systems (GEOSS) Water Strategy ('From Observations to Decisions') recognizes that 'water is essential for ensuring food and energy security, for facilitating poverty reduction and health security, and for the maintenance of ecosystems and biodiversity', and that water cycle data and observations are critical for improved water management and water security - especially in less developed regions. The GEOSS Water Strategy has articulated a number of goals for improved water management, including flood and drought preparedness, that include: (i) facilitating the use of Earth Observations for water cycle observations; (ii) facilitating the acquisition, processing, and distribution of data products needed for effective management; (iii) providing expertise, information systems, and datasets to the global, regional, and national water communities. There are several challenges that must be met to advance our capability to provide near real-time water cycle monitoring, early warning of hydrological hazards (floods and droughts) and risk assessment under climate change, regionally and globally. Current approaches to monitoring and predicting hydrological hazards are limited in many parts of the world, and especially in developing countries where national capacity is limited and monitoring networks are inadequate. This presentation describes the development of a seamless monitoring and prediction framework at all time scales that allows for consistent assessment of water variability from historic to current conditions, and from seasonal and decadal predictions to climate change projections. At the center of the framework is an experimental, global water cycle monitoring and seasonal forecast system that has evolved out of regional and continental systems for the US and Africa. The system is based on land surface hydrological modeling that is driven by satellite remote sensing precipitation to predict current hydrological conditions, flood potential and the state of drought. Seasonal climate model forecasts are downscaled and bias-corrected to drive the land surface model to provide hydrological forecasts and drought products out 6-9 months. The system relies on historic reconstructions of water variability over the 20th century, which forms the background climatology to which current conditions can be assessed. Future changes in water availability and drought risk are quantified based on bias-corrected and downscaled climate model projections that are used to drive the land surface models. For regions with lack of on-the-ground data we are field-testing low-cost environmental sensors and along with new satellite products for terrestrial hydrology and vegetation, integrating these into the system for improved monitoring and prediction. We provide an overview of the system and some examples of real-world applications to flood and drought events, with a focus on Africa.

Assessing Portuguese Guadiana Basin water management impacts under climate change and paleoclimate variability

NASA Astrophysics Data System (ADS)

Maia, Rodrigo; Oliveira, Bruno; Ramos, Vanessa; Brekke, Levi

2014-05-01

The water balance in each reservoir and the subsequent, related, water resource management decisions are, presently, highly information dependent and are therefore often limited to a reactive response (even if aimed towards preventing future issues regarding the water system). Taking advantage of the availability of scenarios for climate projections, it is now possible to estimate the likely future evolution of climate which represents an important stepping stone towards proactive, adaptative, water resource management. The purpose of the present study was to assess the potential effects of climate change in terms of temperature, precipitation, runoff and water availability/scarcity for application in water resource management decisions. The analysis here presented was applied to the Portuguese portion of the Guadiana River Basin, using a combination of observed climate and runoff data and the results of the Global Climate Models. The Guadiana River Basin was represented by its reservoirs on the Portuguese portion of the basin and, for the future period, an estimated value of the inflows originating in the Spanish part of the Basin. The change in climate was determined in terms of relative and absolute variations of climate (precipitation and temperature) and hydrology (runoff and water balance related information). Apart from the previously referred data, an hydrological model and a water management model were applied so as to obtain an extended range of data regarding runoff generation (calibrated to observed data) and water balance in the reservoirs (considering the climate change impacts in the inflows, outflows and water consumption). The water management model was defined in order to represent the reservoirs interaction including upstream to downstream discharges and water transfers. Under the present climate change context, decision-makers and stakeholders are ever more vulnerable to the uncertainties of climate. Projected climate in the Guadiana basin indicates an increase in temperatures and a reduction of the precipitation values which go well beyond the observed values and, therefore, must be forcefully included in any realistic proactive water resource management decision. Using the results of this study it is possible to estimate future water availability and consumption satisfaction allowing for the elaboration of informed management decisions. In this study, the CMIP 3 Global Climate Models were considered for the definition of the effects of climate change, using the median and extreme tendencies based on the range of variation of the multiple climate projection scenarios. The observed climate variability, along with these model-derived tendencies, were used to inform the hydrology and water management models for the historical and future periods, respectively. Additionally, for a more comprehensive analysis on climate variability, a stochastic model was implemented based on the paleoclimate variability obtained from tree-ring records.

The ARM Climate Research Facility - New Capabilities and the Expected Impacts on Climate Science and Modeling

NASA Astrophysics Data System (ADS)

Voyles, J.; Mather, J. H.

2010-12-01

The ARM Climate Research Facility is a Department of Energy national scientific user facility. Research sites include fixed and mobile facilities, which collect research quality data for climate research. Through the American Recovery and Reinvestment Act of 2009, the U.S. Department of Energy’s Office of Science allocated $60 million to the ARM Climate Research Facility for the purchase of instruments and improvement of research sites. With these funds, ARM is in the process of deploying a broad variety of new instruments that will greatly enhance the measurement capabilities of the facility. New instruments being purchased include dual-frequency scanning cloud radars, scanning precipitation radars, Doppler lidars, a mobile Aerosol Observing System and many others. A list of instruments being purchased is available at http://www.arm.gov/about/recovery-act. Orders for all instruments have now been placed and activities are underway to integrate these new systems with our research sites. The overarching goal is to provide instantaneous and statistical measurements of the climate that can be used to advance the physical understanding and predictive performance of climate models. The Recovery Act investments enable the ARM Climate Research Facility to enhance existing and add new measurements, which enable a more complete understanding of the 3-dimensional evolution of cloud processes and related atmospheric properties. Understanding cloud processes are important globally, to reduce climate-modeling uncertainties and help improve our nation’s ability to manage climate impacts. Domer Plot of W-Band Reflectivity

Knowledge Discovery from Climate Data using Graph-Based Methods

NASA Astrophysics Data System (ADS)

Steinhaeuser, K.

2012-04-01

Climate and Earth sciences have recently experienced a rapid transformation from a historically data-poor to a data-rich environment, thus bringing them into the realm of the Fourth Paradigm of scientific discovery - a term coined by the late Jim Gray (Hey et al. 2009), the other three being theory, experimentation and computer simulation. In particular, climate-related observations from remote sensors on satellites and weather radars, in situ sensors and sensor networks, as well as outputs of climate or Earth system models from large-scale simulations, provide terabytes of spatio-temporal data. These massive and information-rich datasets offer a significant opportunity for advancing climate science and our understanding of the global climate system, yet current analysis techniques are not able to fully realize their potential benefits. We describe a class of computational approaches, specifically from the data mining and machine learning domains, which may be novel to the climate science domain and can assist in the analysis process. Computer scientists have developed spatial and spatio-temporal analysis techniques for a number of years now, and many of them may be applicable and/or adaptable to problems in climate science. We describe a large-scale, NSF-funded project aimed at addressing climate science question using computational analysis methods; team members include computer scientists, statisticians, and climate scientists from various backgrounds. One of the major thrusts is in the development of graph-based methods, and several illustrative examples of recent work in this area will be presented.

The CESM Large Ensemble Project: Inspiring New Ideas and Understanding

NASA Astrophysics Data System (ADS)

Kay, J. E.; Deser, C.

2016-12-01

While internal climate variability is known to affect climate projections, its influence is often underappreciated and confused with model error. Why? In general, modeling centers contribute a small number of realizations to international climate model assessments [e.g., phase 5 of the Coupled Model Intercomparison Project (CMIP5)]. As a result, model error and internal climate variability are difficult, and at times impossible, to disentangle. In response, the Community Earth System Model (CESM) community designed the CESM Large Ensemble (CESM-LE) with the explicit goal of enabling assessment of climate change in the presence of internal climate variability. All CESM-LE simulations use a single CMIP5 model (CESM with the Community Atmosphere Model, version 5). The core simulations replay the twenty to twenty-first century (1920-2100) 40+ times under historical and representative concentration pathway 8.5 external forcing with small initial condition differences. Two companion 2000+-yr-long preindustrial control simulations (fully coupled, prognostic atmosphere and land only) allow assessment of internal climate variability in the absence of climate change. Comprehensive outputs, including many daily fields, are available as single-variable time series on the Earth System Grid for anyone to use. Examples of scientists and stakeholders that are using the CESM-LE outputs to help interpret the observational record, to understand projection spread and to plan for a range of possible futures influenced by both internal climate variability and forced climate change will be highlighted the presentation.

NASA Soil Moisture Data Products and Their Incorporation in DREAM

NASA Technical Reports Server (NTRS)

Blonski, Slawomir; Holland, Donald; Henderson, Vaneshette

2005-01-01

NASA provides soil moisture data products that include observations from the Advanced Microwave Scanning Radiometer on the Earth Observing System Aqua satellite, field measurements from the Soil Moisture Experiment campaigns, and model predictions from the Land Information System and the Goddard Earth Observing System Data Assimilation System. Incorporation of the NASA soil moisture products in the Dust Regional Atmospheric Model is possible through use of the satellite observations of soil moisture to set initial conditions for the dust simulations. An additional comparison of satellite soil moisture observations with mesoscale atmospheric dynamics modeling is recommended. Such a comparison would validate the use of NASA soil moisture data in applications and support acceptance of satellite soil moisture data assimilation in weather and climate modeling.

FOREWORD: Satellite Remote Sensing Beyond 2015

NASA Technical Reports Server (NTRS)

Tucker, Compton J.

2017-01-01

Satellite remote sensing has progressed tremendously since the first Landsat was launched on June 23, 1972. Since the 1970s, satellite remote sensing and associated airborne and in situ measurements have resulted in vital and indispensable observations for understanding our planet through time. These observations have also led to dramatic improvements in numerical simulation models of the coupled atmosphere-land-ocean systems at increasing accuracies and predictive capability. The same observations document the Earth's climate and are driving the consensus that Homo sapiens is changing our climate through greenhouse gas emissions. These accomplishments are the combined work of many scientists from many countries and a dedicated cadre of engineers who build the instruments and satellites that collect Earth observation data from satellites, all working toward the goal of improving our understanding of the Earth. This edition of the Remote Sensing Handbook (Vol. I, II, and III) is a compendium of information for many research areas of our Planet that have contributed to our substantial progress since the 1970s. Remote sensing community is now using multiple sources of satellite and in situ data to advance our studies, what ever they might be. In the following paragraphs, I will illustrate how valuable and pivotal role satellite remote sensing has played in climate system study over last five decades, The Chapters in the Remote Sensing Handbook (Vol. I, II, and III) provides many other specific studies on land, water, and other applications using EO data of last five decades, The Landsat system of Earth-observing satellites has led the way in pioneering sustained observations of our planet. From 1972 to the present, at least one and sometimes two Landsat satellites have been in operation. Starting with the launch of the first NOAA-NASA Polar Orbiting Environmental Satellites NOAA-6 in 1978, improved imaging of land, clouds, and oceans and atmospheric soundings of temperature were accomplished. The NOAA system of polar-orbiting meteorological satellites has continued uninterrupted since that time, providing vital observations for numerical weather prediction. These same satellites are also responsible for the remarkable records of sea surface temperature and land vegetation index from the Advanced Very High Resolution Radiometers (AVHRR) that now span more than 33 years, although no one anticipated these valuable climate records from this instrument before the launch of NOAA-7 in 1981. The success of data from the AVHRR led to the design of the MODIS instruments on NASA's Earth Observing System of satellite platforms that improved substantially upon the AVHRR. The first of the EOS platforms, Terra, was launched in 2000 and the second of these platforms, Aqua, was launched in 2002.

Greenland ice sheet beyond 2100: Simulating its evolution and influence using the coupled climate-ice sheet model EC-Earth - PISM

NASA Astrophysics Data System (ADS)

Yang, S.; Christensen, J. H.; Madsen, M. S.; Ringgaard, I. M.; Petersen, R. A.; Langen, P. P.

2017-12-01

Greenland ice sheet (GrIS) is observed undergoing a rapid change in the recent decades, with an increasing area of surface melting and ablation and a speeding mass loss. Predicting the GrIS changes and their climate consequences relies on the understanding of the interaction of the GrIS with the climate system on both global and local scales, and requires climate model systems incorporating with an explicit and physically consistent ice sheet module. In this work we study the GrIS evolution and its interaction with the climate system using a fully coupled global climate model with a dynamical ice sheet model for the GrIS. The coupled model system, EC-EARTH - PISM, consisting of the atmosphere-ocean-sea ice model system EC-EARTH, and the Parallel Ice Sheet Model (PISM), has been employed for a 1400-year simulation forced by CMIP5 historical forcing from 1850 to 2005 and continued along an extended RCP8.5 scenario with the forcing peaking at 2200 and stabilized hereafter. The simulation reveals that, following the anthropogenic forcing increase, the global mean surface temperature rapidly rises about 10 °C in the 21st and 22nd century. After the forcing stops increasing after 2200, the temperature change slows down and eventually stabilizes at about 12.5 °C above the preindustrial level. In response to the climate warming, the GrIS starts losing mass slowly in the 21st century, but the ice retreat accelerates substantially after 2100 and ice mass loss continues hereafter at a constant rate of approximately 0.5 m sea level rise equivalence per 100 years, even as the warming rate gradually levels off. Ultimately the volume and extent of GrIS reduce to less than half of its preindustrial value. To understand the interaction of GrIS with the climate system, the characteristics of atmospheric and oceanic circulation in the warm climate are analyzed. The circulation patterns associated with the negative surface mass balance that leads to GrIS retreat are investigated. The impact of the simulated surface warming on the ice flow and ice dynamics is explored.

Diagnosis of boreal summer intraseasonal oscillation in high resolution NCEP climate forecast system

NASA Astrophysics Data System (ADS)

Abhik, S.; Mukhopadhyay, P.; Krishna, R. P. M.; Salunke, Kiran D.; Dhakate, Ashish R.; Rao, Suryachandra A.

2016-05-01

The present study examines the ability of high resolution (T382) National Centers for Environmental Prediction coupled atmosphere-ocean climate forecast system version 2 (CFS T382) in simulating the salient spatio-temporal characteristics of the boreal summertime mean climate and the intraseasonal variability. The shortcomings of the model are identified based on the observation and compared with earlier reported biases of the coarser resolution of CFS (CFS T126). It is found that the CFS T382 reasonably mimics the observed features of basic state climate during boreal summer. But some prominent biases are noted in simulating the precipitation, tropospheric temperature (TT) and sea surface temperature (SST) over the global tropics. Although CFS T382 primarily reproduces the observed distribution of the intraseasonal variability over the Indian summer monsoon region, some difficulty remains in simulating the boreal summer intraseasonal oscillation (BSISO) characteristics. The simulated eastward propagation of BSISO decays rapidly across the Maritime Continent, while the northward propagation appears to be slightly slower than observation. However, the northward propagating BSISO convection propagates smoothly from the equatorial region to the northern latitudes with observed magnitude. Moreover, the observed northwest-southeast tilted rain band is not well reproduced in CFS T382. The warm mean SST bias and inadequate simulation of high frequency modes appear to be responsible for the weak simulation of eastward propagating BSISO. Unlike CFS T126, the simulated mean SST and TT exhibit warm biases, although the mean precipitation and simulated BSISO characteristics are largely similar in both the resolutions of CFS. Further analysis of the convectively coupled equatorial waves (CCEWs) indicates that model overestimates the gravest equatorial Rossby waves and underestimates the Kelvin and mixed Rossby-gravity waves. Based on analysis of CCEWs, the study further explains the possible reasons behind the realistic simulation of northward propagating BSISO in CFS T382, even though the model shows substantial biases in simulating mean state and other BSISO modes.

The long-range correlation and evolution law of centennial-scale temperatures in Northeast China.

PubMed

Zheng, Xiaohui; Lian, Yi; Wang, Qiguang

2018-01-01

This paper applies the detrended fluctuation analysis (DFA) method to investigate the long-range correlation of monthly mean temperatures from three typical measurement stations at Harbin, Changchun, and Shenyang in Northeast China from 1909 to 2014. The results reveal the memory characteristics of the climate system in this region. By comparing the temperatures from different time periods and investigating the variations of its scaling exponents at the three stations during these different time periods, we found that the monthly mean temperature has long-range correlation, which indicates that the temperature in Northeast China has long-term memory and good predictability. The monthly time series of temperatures over the past 106 years also shows good long-range correlation characteristics. These characteristics are also obviously observed in the annual mean temperature time series. Finally, we separated the centennial-length temperature time series into two time periods. These results reveal that the long-range correlations at the Harbin station over these two time periods have large variations, whereas no obvious variations are observed at the other two stations. This indicates that warming affects the regional climate system's predictability differently at different time periods. The research results can provide a quantitative reference point for regional climate predictability assessment and future climate model evaluation.

Probabilistic hindcasts and projections of the coupled climate, carbon cycle and Atlantic meridional overturning circulation system: a Bayesian fusion of century-scale observations with a simple model

NASA Astrophysics Data System (ADS)

Urban, Nathan M.; Keller, Klaus

2010-10-01

How has the Atlantic Meridional Overturning Circulation (AMOC) varied over the past centuries and what is the risk of an anthropogenic AMOC collapse? We report probabilistic projections of the future climate which improve on previous AMOC projection studies by (i) greatly expanding the considered observational constraints and (ii) carefully sampling the tail areas of the parameter probability distribution function (pdf). We use a Bayesian inversion to constrain a simple model of the coupled climate, carbon cycle and AMOC systems using observations to derive multicentury hindcasts and projections. Our hindcasts show considerable skill in representing the observational constraints. We show that robust AMOC risk estimates can require carefully sampling the parameter pdfs. We find a low probability of experiencing an AMOC collapse within the 21st century for a business-as-usual emissions scenario. The probability of experiencing an AMOC collapse within two centuries is 1/10. The probability of crossing a forcing threshold and triggering a future AMOC collapse (by 2300) is approximately 1/30 in the 21st century and over 1/3 in the 22nd. Given the simplicity of the model structure and uncertainty in the forcing assumptions, our analysis should be considered a proof of concept and the quantitative conclusions subject to severe caveats.

The Community Land Model and Its Climate Statistics as a Component of the Community Climate System Model

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

Dickinson, Robert E.; Oleson, Keith; Bonan, Gordon

2006-01-01

Several multidecadal simulations have been carried out with the new version of the Community Climate System Model (CCSM). This paper reports an analysis of the land component of these simulations. Global annual averages over land appear to be within the uncertainty of observational datasets, but the seasonal cycle over land of temperature and precipitation appears to be too weak. These departures from observations appear to be primarily a consequence of deficiencies in the simulation of the atmospheric model rather than of the land processes. High latitudes of northern winter are biased sufficiently warm to have a significant impact on themore » simulated value of global land temperature. The precipitation is approximately doubled from what it should be at some locations, and the snowpack and spring runoff are also excessive. The winter precipitation over Tibet is larger than observed. About two-thirds of this precipitation is sublimated during the winter, but what remains still produces a snowpack that is very large compared to that observed with correspondingly excessive spring runoff. A large cold anomaly over the Sahara Desert and Sahel also appears to be a consequence of a large anomaly in downward longwave radiation; low column water vapor appears to be most responsible. The modeled precipitation over the Amazon basin is low compared to that observed, the soil becomes too dry, and the temperature is too warm during the dry season.« less

Toward a Climate OSSE for NASA Earth Sciences

NASA Astrophysics Data System (ADS)

Leroy, S. S.; Collins, W. D.; Feldman, D.; Field, R. D.; Ming, Y.; Pawson, S.; Sanderson, B.; Schmidt, G. A.

2016-12-01

In the Continuity Study, the National Academy of Sciences advised that future space missions be rated according to five categories: the importance of a well-defined scientific objective, the utility of the observation in addressing the scientific objective, the quality with which the observation can be made, the probability of the mission's success, and the mission's affordability. The importance, probability, and affordability are evaluated subjectively by scientific consensus, by engineering review panels, and by cost models; however, the utility and quality can be evaluated objectively by a climate observation system simulation experiment (COSSE). A discussion of the philosophical underpinnings of a COSSE for NASA Earth Sciences will be presented. A COSSE is built upon a perturbed physics ensemble of a sophisticated climate model that can simulate a mission's prospective observations and its well-defined quantitative scientific objective and that can capture the uncertainty associated with each. A strong correlation between observation and scientific objective after consideration of physical uncertainty leads to a high quality. Persistence of a high correlation after inclusion of the proposed measurement error leads to a high utility. There are five criteria that govern that nature of a particular COSSE: (1) whether the mission's scientific objective is one of hypothesis testing or climate prediction, (2) whether the mission is empirical or inferential, (3) whether the core climate model captures essential physical uncertainties, (4) the level of detail of the simulated observations, and (5) whether complementarity or redundancy of information is to be valued. Computation of the quality and utility is done using Bayesian statistics, as has been done previously for multi-decadal climate prediction conditioned on existing data. We advocate for a new program within NASA Earth Sciences to establish a COSSE capability. Creation of a COSSE program within NASA Earth Sciences will require answers from the climate research community to basic questions, such as whether a COSSE capability should be centralized or de-centralized. Most importantly, the quantified scientific objective of a proposed mission must be defined with extreme specificity for a COSSE to be applied.

Projected Applications of a ``Climate in a Box'' Computing System at the NASA Short-term Prediction Research and Transition (SPoRT) Center

NASA Astrophysics Data System (ADS)

Jedlovec, G.; Molthan, A.; Zavodsky, B.; Case, J.; Lafontaine, F.

2010-12-01

The NASA Short-term Prediction Research and Transition (SPoRT) Center focuses on the transition of unique observations and research capabilities to the operational weather community, with a goal of improving short-term forecasts on a regional scale. Advances in research computing have lead to “Climate in a Box” systems, with hardware configurations capable of producing high resolution, near real-time weather forecasts, but with footprints, power, and cooling requirements that are comparable to desktop systems. The SPoRT Center has developed several capabilities for incorporating unique NASA research capabilities and observations with real-time weather forecasts. Planned utilization includes the development of a fully-cycled data assimilation system used to drive 36-48 hour forecasts produced by the NASA Unified version of the Weather Research and Forecasting (WRF) model (NU-WRF). The horsepower provided by the “Climate in a Box” system is expected to facilitate the assimilation of vertical profiles of temperature and moisture provided by the Atmospheric Infrared Sounder (AIRS) aboard the NASA Aqua satellite. In addition, the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments aboard NASA’s Aqua and Terra satellites provide high-resolution sea surface temperatures and vegetation characteristics. The development of MODIS normalized difference vegetation index (NVDI) composites for use within the NASA Land Information System (LIS) will assist in the characterization of vegetation, and subsequently the surface albedo and processes related to soil moisture. Through application of satellite simulators, NASA satellite instruments can be used to examine forecast model errors in cloud cover and other characteristics. Through the aforementioned application of the “Climate in a Box” system and NU-WRF capabilities, an end goal is the establishment of a real-time forecast system that fully integrates modeling and analysis capabilities developed within the NASA SPoRT Center, with benefits provided to the operational forecasting community.

Projected Applications of a "Climate in a Box" Computing System at the NASA Short-Term Prediction Research and Transition (SPoRT) Center

NASA Technical Reports Server (NTRS)

Jedlovec, Gary J.; Molthan, Andrew L.; Zavodsky, Bradley; Case, Jonathan L.; LaFontaine, Frank J.

2010-01-01

The NASA Short-term Prediction Research and Transition (SPoRT) Center focuses on the transition of unique observations and research capabilities to the operational weather community, with a goal of improving short-term forecasts on a regional scale. Advances in research computing have lead to "Climate in a Box" systems, with hardware configurations capable of producing high resolution, near real-time weather forecasts, but with footprints, power, and cooling requirements that are comparable to desktop systems. The SPoRT Center has developed several capabilities for incorporating unique NASA research capabilities and observations with real-time weather forecasts. Planned utilization includes the development of a fully-cycled data assimilation system used to drive 36-48 hour forecasts produced by the NASA Unified version of the Weather Research and Forecasting (WRF) model (NU-WRF). The horsepower provided by the "Climate in a Box" system is expected to facilitate the assimilation of vertical profiles of temperature and moisture provided by the Atmospheric Infrared Sounder (AIRS) aboard the NASA Aqua satellite. In addition, the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments aboard NASA s Aqua and Terra satellites provide high-resolution sea surface temperatures and vegetation characteristics. The development of MODIS normalized difference vegetation index (NVDI) composites for use within the NASA Land Information System (LIS) will assist in the characterization of vegetation, and subsequently the surface albedo and processes related to soil moisture. Through application of satellite simulators, NASA satellite instruments can be used to examine forecast model errors in cloud cover and other characteristics. Through the aforementioned application of the "Climate in a Box" system and NU-WRF capabilities, an end goal is the establishment of a real-time forecast system that fully integrates modeling and analysis capabilities developed within the NASA SPoRT Center, with benefits provided to the operational forecasting community.

Observation of Upper and Middle Tropospheric Clouds

NASA Technical Reports Server (NTRS)

Cox, Stephen K.

1996-01-01

The goal of this research has been to identify and describe the properties of climatically important cloud systems critically important to understanding their effects upon satellite remote sensing and the global climate. These goals have been pursued along several different but complementary lines of investigation: the design, construction, testing and application of instrumentation; the collection of data sets during Intensive Field Observation periods; the reduction and analysis of data collected during IFO's; and completion of research projects specifically designed to address important and timely research objectives. In the first year covered by this research proposal, three papers were authored in the refereed literature which reported completed analyses of FIRE 1 IFO studies initiated under the previous NASA funding of this topic area. microphysical and radiative properties of marine stratocumulus cloud systems deduced from tethered balloon observations were reported from the San Nicolas Island site of the first FIRE marine stratocumulus experiment. Likewise, in situ observations of radiation and dynamic properties of a cirrus cloud layer were reported from first FIRE cirrus IFO based from Madison, Wisconsin. In addition, application techniques were under development for monitoring cirrus cloud systems using a 403 MHz Doppler wind profiler system adapted with a RASS (Radio Acoustic Sounding System) and an infrared interferometer system; these instrument systems were used in subsequent deployments for the FIRE 2 Parsons, Kansas and FIRE 2 Porto Santo, ASTEX expeditions. In November 1991 and in June 1992, these two systems along with a complete complement of surface radiation and meteorology measurements were deployed to the two sites noted above as anchor points for the respective IFO'S. Subsequent research activity concentrated on the interpretation and integration of the IFO analyses in the context of the radiative properties of cloud systems and our ability to remotely observe radiative, thermodynamic and dynamic properties of these cloud systems.

Analysis of meteorological variables in the Australasian region using ground- and space-based GPS techniques

NASA Astrophysics Data System (ADS)

Kuleshov, Yuriy; Choy, Suelynn; Fu, Erjiang Frank; Chane-Ming, Fabrice; Liou, Yuei-An; Pavelyev, Alexander G.

2016-07-01

Results of analysis of meteorological variables (temperature and moisture) in the Australasian region using the global positioning system (GPS) radio occultation (RO) and GPS ground-based observations verified with in situ radiosonde (RS) data are presented. The potential of using ground-based GPS observations for retrieving column integrated precipitable water vapour (PWV) over the Australian continent has been demonstrated using the Australian ground-based GPS reference stations network. Using data from the 15 ground-based GPS stations, the state of the atmosphere over Victoria during a significant weather event, the March 2010 Melbourne storm, has been investigated, and it has been shown that the GPS observations has potential for monitoring the movement of a weather front that has sharp moisture contrast. Temperature and moisture variability in the atmosphere over various climatic regions (the Indian and the Pacific Oceans, the Antarctic and Australia) has been examined using satellite-based GPS RO and in situ RS observations. Investigating recent atmospheric temperature trends over Antarctica, the time series of the collocated GPS RO and RS data were examined, and strong cooling in the lower stratosphere and warming through the troposphere over Antarctica has been identified, in agreement with outputs of climate models. With further expansion of the Global Navigation Satellite Systems (GNSS) system, it is expected that GNSS satellite- and ground-based measurements would be able to provide an order of magnitude larger amount of data which in turn could significantly advance weather forecasting services, climate monitoring and analysis in the Australasian region.

Adaptation des systèmes de production agricole au changement climatiqueAdaptation of agricultural production systems to climatic change

NASA Astrophysics Data System (ADS)

Seguin, Bernard

2003-06-01

The adaptation of agricultural production systems to climatic change needs to firstly consider the predictable impact upon vegetal production, using the available knowledge on crop ecophysiology applied for simulating the effects of climate scenarios, including the increase of atmospheric CO 2. The predicted consequences are firstly presented in general terms. They are thereafter detailed for each main type of production in France (annual crops, pastures and perennial crops), taking into account recent observations about the evolution of climate and related consequences on crop phenology (especially fruit trees and vine). They lead to identify the main lines for the adaptation at the level of present cropping systems, considered as geographically stable. However, this level needs to be completed by a second one, corresponding to a possible shift in latitude or altitude, as well as the introduction of new crops. Ultimately, a third level of adaptation will correspond to the evolution of territories and land use, whose determinants will be discussed in the conclusion. To cite this article: B. Seguin, C. R. Geoscience 335 (2003).

Developing services for climate impact and adaptation baseline information and methodologies for the Andes

NASA Astrophysics Data System (ADS)

Huggel, C.

2012-04-01

Impacts of climate change are observed and projected across a range of ecosystems and economic sectors, and mountain regions thereby rank among the hotspots of climate change. The Andes are considered particularly vulnerable to climate change, not only due to fragile ecosystems but also due to the high vulnerability of the population. Natural resources such as water systems play a critical role and are observed and projected to be seriously affected. Adaptation to climate change impacts is therefore crucial to contain the negative effects on the population. Adaptation projects require information on the climate and affected socio-environmental systems. There is, however, generally a lack of methodological guidelines how to generate the necessary scientific information and how to communicate to implementing governmental and non-governmental institutions. This is particularly important in view of the international funds for adaptation such as the Green Climate Fund established and set into process at the UNFCCC Conferences of the Parties in Cancun 2010 and Durban 2011. To facilitate this process international and regional organizations (World Bank and Andean Community) and a consortium of research institutions have joined forces to develop and define comprehensive methodologies for baseline and climate change impact assessments for the Andes, with an application potential to other mountain regions (AndesPlus project). Considered are the climatological baseline of a region, and the assessment of trends based on ground meteorological stations, reanalysis data, and satellite information. A challenge is the scarcity of climate information in the Andes, and the complex climatology of the mountain terrain. A climate data platform has been developed for the southern Peruvian Andes and is a key element for climate data service and exchange. Water resources are among the key livelihood components for the Andean population, and local and national economy, in particular for agriculture and hydropower. The retreat of glaciers as one of the clearest signal of climate change represents a problem for water supply during the long dry season. Hydrological modeling, using data from the few gauging stations and complemented by satellite precipitation data, is needed to generate baseline and climate impact information. Food security is often considered threatened due to climate change impacts, in the Andes for instance by droughts and cold spells that seriously affect high-elevation food systems. Eventually, methodologies are compiled and developed for analyzing risks from natural hazards and disasters. The vulnerabilities and risks for all types of climate impacts need to be reflected by analyzing the local and regional social, cultural, political and economic context. To provide the necessary references and information the project AndesPlus has developed a web-based knowledge and information platform. The highly interdisciplinary process of the project should contribute to climate impact and adaptation information services, needed to meet the challenges of adaptation.

ERCA 2008 - From the Human Dimensions of Global Environmental Change to the Observation of the Earth from Space

NASA Astrophysics Data System (ADS)

Boutron, Claude

2009-02-01

This book is the eighth volume in the series of books published within the framework of the European Research Course on Atmospheres ("ERCA"). ERCA was initiated in 1993 by the University Joseph Fourier of Grenoble, in order to provide PhD students and scientists from Europe and the rest of the world with a multidisciplinary course, which covers especially: the climate system and climate change; the physics and chemistry of the Earth's atmosphere; the human dimensions of environmental change; the other planets and satellites in the solar system and beyond. Since 1993, sixteen sessions have been attended by more 800 participants from 50 countries. The seventeenth session will take place from 12 January to 13 February 2009. This new volume contains twenty two chapters dealing with a wide range of topics. The following subjects are covered: the human dimensions of global environmental change; climate change and cryospheric evolution in China; the projections of twenty-first century climate over Europe; the understanding of the health impacts of air pollutants; air quality and human welfare; photocatalytic self-cleaning materials; radiative transfer in the cloudy atmosphere; laboratory modelling of atmospheric dynamical processes; stratospheric ozone; the applications of stable isotope analysis to atmospheric trace gas budgets; nitrogen oxides in the troposphere; the observation of the solid Earth, the oceans and land waters; the surface mass balance of the Greenland ice sheet; sea surface salinity reconstruction as seen with foraminifera shells; sources markers in aerosols, oceanic particles and sediments; the nucleation of atmospheric particles; the characterization of atmospheric aerosol episodes in China; the solar magnetic activity; the present and past climates of planet Mars; the outer solar system; Titan as an analog of Earth's past and future; the detection and characterization of extrasolar planets.

Future potential distribution of the emerging amphibian chytrid fungus under anthropogenic climate change.

PubMed

Rödder, Dennis; Kielgast, Jos; Lötters, Stefan

2010-11-01

Anthropogenic climate change poses a major threat to global biodiversity with a potential to alter biological interactions at all spatial scales. Amphibians are the most threatened vertebrates and have been subject to increasing conservation attention over the past decade. A particular concern is the pandemic emergence of the parasitic chytrid fungus Batrachochytrium dendrobatidis, which has been identified as the cause of extremely rapid large-scale declines and species extinctions. Experimental and observational studies have demonstrated that the host-pathogen system is strongly influenced by climatic parameters and thereby potentially affected by climate change. Herein we project a species distribution model of the pathogen onto future climatic scenarios generated by the IPCC to examine their potential implications on the pandemic. Results suggest that predicted anthropogenic climate change may reduce the geographic range of B. dendrobatidis and its potential influence on amphibian biodiversity.

Is it feasible to estimate radiosonde biases from interlaced measurements?

NASA Astrophysics Data System (ADS)

Kremser, Stefanie; Tradowsky, Jordis S.; Rust, Henning W.; Bodeker, Greg E.

2018-05-01

Upper-air measurements of essential climate variables (ECVs), such as temperature, are crucial for climate monitoring and climate change detection. Because of the internal variability of the climate system, many decades of measurements are typically required to robustly detect any trend in the climate data record. It is imperative for the records to be temporally homogeneous over many decades to confidently estimate any trend. Historically, records of upper-air measurements were primarily made for short-term weather forecasts and as such are seldom suitable for studying long-term climate change as they lack the required continuity and homogeneity. Recognizing this, the Global Climate Observing System (GCOS) Reference Upper-Air Network (GRUAN) has been established to provide reference-quality measurements of climate variables, such as temperature, pressure, and humidity, together with well-characterized and traceable estimates of the measurement uncertainty. To ensure that GRUAN data products are suitable to detect climate change, a scientifically robust instrument replacement strategy must always be adopted whenever there is a change in instrumentation. By fully characterizing any systematic differences between the old and new measurement system a temporally homogeneous data series can be created. One strategy is to operate both the old and new instruments in tandem for some overlap period to characterize any inter-instrument biases. However, this strategy can be prohibitively expensive at measurement sites operated by national weather services or research institutes. An alternative strategy that has been proposed is to alternate between the old and new instruments, so-called interlacing, and then statistically derive the systematic biases between the two instruments. Here we investigate the feasibility of such an approach specifically for radiosondes, i.e. flying the old and new instruments on alternating days. Synthetic data sets are used to explore the applicability of this statistical approach to radiosonde change management.

Ice_Sheets_CCI: Essential Climate Variables for the Greenland Ice Sheet

NASA Astrophysics Data System (ADS)

Forsberg, R.; Sørensen, L. S.; Khan, A.; Aas, C.; Evansberget, D.; Adalsteinsdottir, G.; Mottram, R.; Andersen, S. B.; Ahlstrøm, A.; Dall, J.; Kusk, A.; Merryman, J.; Hvidberg, C.; Khvorostovsky, K.; Nagler, T.; Rott, H.; Scharrer, M.; Shepard, A.; Ticconi, F.; Engdahl, M.

2012-04-01

As part of the ESA Climate Change Initiative (www.esa-cci.org) a long-term project "ice_sheets_cci" started January 1, 2012, in addition to the existing 11 projects already generating Essential Climate Variables (ECV) for the Global Climate Observing System (GCOS). The "ice_sheets_cci" goal is to generate a consistent, long-term and timely set of key climate parameters for the Greenland ice sheet, to maximize the impact of European satellite data on climate research, from missions such as ERS, Envisat and the future Sentinel satellites. The climate parameters to be provided, at first in a research context, and in the longer perspective by a routine production system, would be grids of Greenland ice sheet elevation changes from radar altimetry, ice velocity from repeat-pass SAR data, as well as time series of marine-terminating glacier calving front locations and grounding lines for floating-front glaciers. The ice_sheets_cci project will involve a broad interaction of the relevant cryosphere and climate communities, first through user consultations and specifications, and later in 2012 optional participation in "best" algorithm selection activities, where prototype climate parameter variables for selected regions and time frames will be produced and validated using an objective set of criteria ("Round-Robin intercomparison"). This comparative algorithm selection activity will be completely open, and we invite all interested scientific groups with relevant experience to participate. The results of the "Round Robin" exercise will form the algorithmic basis for the future ECV production system. First prototype results will be generated and validated by early 2014. The poster will show the planned outline of the project and some early prototype results.

Uncertainty Quantification in Climate Modeling and Projection

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

Qian, Yun; Jackson, Charles; Giorgi, Filippo

The projection of future climate is one of the most complex problems undertaken by the scientific community. Although scientists have been striving to better understand the physical basis of the climate system and to improve climate models, the overall uncertainty in projections of future climate has not been significantly reduced (e.g., from the IPCC AR4 to AR5). With the rapid increase of complexity in Earth system models, reducing uncertainties in climate projections becomes extremely challenging. Since uncertainties always exist in climate models, interpreting the strengths and limitations of future climate projections is key to evaluating risks, and climate change informationmore » for use in Vulnerability, Impact, and Adaptation (VIA) studies should be provided with both well-characterized and well-quantified uncertainty. The workshop aimed at providing participants, many of them from developing countries, information on strategies to quantify the uncertainty in climate model projections and assess the reliability of climate change information for decision-making. The program included a mixture of lectures on fundamental concepts in Bayesian inference and sampling, applications, and hands-on computer laboratory exercises employing software packages for Bayesian inference, Markov Chain Monte Carlo methods, and global sensitivity analyses. The lectures covered a range of scientific issues underlying the evaluation of uncertainties in climate projections, such as the effects of uncertain initial and boundary conditions, uncertain physics, and limitations of observational records. Progress in quantitatively estimating uncertainties in hydrologic, land surface, and atmospheric models at both regional and global scales was also reviewed. The application of Uncertainty Quantification (UQ) concepts to coupled climate system models is still in its infancy. The Coupled Model Intercomparison Project (CMIP) multi-model ensemble currently represents the primary data for assessing reliability and uncertainties of climate change information. An alternative approach is to generate similar ensembles by perturbing parameters within a single-model framework. One of workshop’s objectives was to give participants a deeper understanding of these approaches within a Bayesian statistical framework. However, there remain significant challenges still to be resolved before UQ can be applied in a convincing way to climate models and their projections.« less

Check-Up of Planet Earth at the Turn of the Millennium Anticipated New Phase in Earth Sciences

NASA Technical Reports Server (NTRS)

Kaufman, Yoram

1999-01-01

Langley's remarkable solar and lunar spectra collected from mt. Whitney inspired Arrhenius to develop the first quantitative climate model in 1896. In 1999, NASA's Earth Observing AM Satellite named recently "Terra" (by Ms. Sasha Jones, a 17 year old student in St. Louis, MO) will repeat Langley's experiment, but for the entire planet, thus pioneering calibrated spectral observations from space. Conceived in response to real environmental problems, EOS-AM, in conjunction with other international satellite efforts, will fill a major gap in current efforts by providing quantitative global data sets with a resolution of few kilometers on the physical, chemical and biological elements of the earth system. Thus, like Langley's data, EOS-AM can revolutionize climate research by inspiring a new generation of climate system models and enable us to assess the human impact on the environment. In this talk I shall a give a historical perspective for the need for this expensive mission, give examples of the science that we anticipate to achieve using Terra measurements and describe this exciting mission.

The importance of deep, basinwide measurements in optimized Atlantic Meridional Overturning Circulation observing arrays

NASA Astrophysics Data System (ADS)

McCarthy, G. D.; Menary, M. B.; Mecking, J. V.; Moat, B. I.; Johns, W. E.; Andrews, M. B.; Rayner, D.; Smeed, D. A.

2017-03-01

The Atlantic Meridional Overturning Circulation (AMOC) is a key process in the global redistribution of heat. The AMOC is defined as the maximum of the overturning stream function, which typically occurs near 30°N in the North Atlantic. The RAPID mooring array has provided full-depth, basinwide, continuous estimates of this quantity since 2004. Motivated by both the need to deliver near real-time data and optimization of the array to reduce costs, we consider alternative configurations of the mooring array. Results suggest that the variability observed since 2004 could be reproduced by a single tall mooring on the western boundary and a mooring to 1500 m on the eastern boundary. We consider the potential future evolution of the AMOC in two generations of the Hadley Centre climate models and a suite of additional CMIP5 models. The modeling studies show that deep, basinwide measurements are essential to capture correctly the future decline of the AMOC. We conclude that, while a reduced array could be useful for estimates of the AMOC on subseasonal to decadal time scales as part of a near real-time data delivery system, extreme caution must be applied to avoid the potential misinterpretation or absence of a climate time scale AMOC decline that is a key motivation for the maintenance of these observations.