Land cover change or land-use intensification: simulating land system change with a global-scale land change model.

PubMed

van Asselen, Sanneke; Verburg, Peter H

2013-12-01

Land-use change is both a cause and consequence of many biophysical and socioeconomic changes. The CLUMondo model provides an innovative approach for global land-use change modeling to support integrated assessments. Demands for goods and services are, in the model, supplied by a variety of land systems that are characterized by their land cover mosaic, the agricultural management intensity, and livestock. Land system changes are simulated by the model, driven by regional demand for goods and influenced by local factors that either constrain or promote land system conversion. A characteristic of the new model is the endogenous simulation of intensification of agricultural management versus expansion of arable land, and urban versus rural settlements expansion based on land availability in the neighborhood of the location. Model results for the OECD Environmental Outlook scenario show that allocation of increased agricultural production by either management intensification or area expansion varies both among and within world regions, providing useful insight into the land sparing versus land sharing debate. The land system approach allows the inclusion of different types of demand for goods and services from the land system as a driving factor of land system change. Simulation results are compared to observed changes over the 1970-2000 period and projections of other global and regional land change models. © 2013 John Wiley & Sons Ltd.

Space America's commercial space program

NASA Technical Reports Server (NTRS)

Macleod, N. H.

1984-01-01

Space America prepared a private sector land observing space system which includes a sensor system with eight spectral channels configured for stereoscopic data acquisition of four stereo pairs, a spacecraft bus with active three-axis stabilization, a ground station for data acquisition, preprocessing and retransmission. The land observing system is a component of Space America's end-to-end system for Earth resources management, monitoring and exploration. In the context of the Federal Government's program of commercialization of the US land remote sensing program, Space America's space system is characteristic of US industry's use of advanced technology and of commercial, entrepreneurial management. Well before the issuance of the Request for Proposals for Transfer of the United States Land Remote Sensing Program to the Private Sector by the US Department of Commerce, Space Services, Inc., the managing venturer of Space America, used private funds to develop and manage its sub-orbital launch of its Conestoga launch vehicle.

Spectroradiometric considerations for advanced land observing systems

NASA Technical Reports Server (NTRS)

Slater, P. N.

1986-01-01

Research aimed at improving the inflight absolute radiometric calibration of advanced land observing systems was initiated. Emphasis was on the satellite sensor calibration program at White Sands. Topics addressed include: absolute radiometric calibration of advanced remote sensing; atmospheric effects on reflected radiation; inflight radiometric calibration; field radiometric methods for reflectance and atmospheric measurement; and calibration of field relectance radiometers.

Land Surface Precipitation and Hydrology in MERRA-2

NASA Technical Reports Server (NTRS)

Reichle, R.; Koster, R.; Draper, C.; Liu, Q.; Girotto, M.; Mahanama, S.; De Lannoy, G.; Partyka, G.

2017-01-01

The Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), provides global, 1-hourly estimates of land surface conditions for 1980-present at 50-km resolution. Outside of the high latitudes, MERRA-2 uses observations-based precipitation data products to correct the precipitation falling on the land surface. This paper describes the precipitation correction method and evaluates the MERRA-2 land surface precipitation and hydrology. Compared to monthly GPCPv2.2 observations, the corrected MERRA-2 precipitation (M2CORR) is better than the precipitation generated by the atmospheric models within the cyclingMERRA-2 system and the earlier MERRA reanalysis. Compared to 3-hourlyTRMM observations, the M2CORR diurnal cycle has better amplitude but less realistic phasing than MERRA-2 model-generated precipitation. Because correcting the precipitation within the coupled atmosphere-land modeling system allows the MERRA-2 near-surface air temperature and humidity to respond to the improved precipitation forcing, MERRA-2 provides more self-consistent surface meteorological data than were available from the earlier, offline MERRA-Land reanalysis. Overall, MERRA-2 land hydrology estimates are better than those of MERRA-Land and MERRA. A comparison against GRACE satellite observations of terrestrial water storage demonstrates clear improvements in MERRA-2 over MERRA in South America and Africa but also reflects known errors in the observations used to correct the MERRA-2 precipitation. The MERRA-2 and MERRA-Land surface and root zone soil moisture skill vs. in situ measurements is slightly higher than that of ERA-Interim Land and higher than that of MERRA (significantly for surface soil moisture). Snow amounts from MERRA-2 have lower bias and correlate better against reference data than do those of MERRA-Land and MERRA, with MERRA-2 skill roughly matching that of ERA-Interim Land. Seasonal anomaly R values against naturalized stream flow measurements in the United States are, on balance, highest for MERRA-2 and ERA-Interim Land, somewhat lower for MERRA-Land, and lower still for MERRA.

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

Land surface sensitivity of monsoon depressions formed over Bay of Bengal using improved high-resolution land state

NASA Astrophysics Data System (ADS)

Rajesh, P. V.; Pattnaik, S.; Mohanty, U. C.; Rai, D.; Baisya, H.; Pandey, P. C.

2017-12-01

Monsoon depressions (MDs) constitute a large fraction of the total rainfall during the Indian summer monsoon season. In this study, the impact of high-resolution land state is addressed by assessing the evolution of inland moving depressions formed over the Bay of Bengal using a mesoscale modeling system. Improved land state is generated using High Resolution Land Data Assimilation System employing Noah-MP land-surface model. Verification of soil moisture using Soil Moisture and Ocean Salinity (SMOS) and soil temperature using tower observations demonstrate promising results. Incorporating high-resolution land state yielded least root mean squared errors with higher correlation coefficient in the surface and mid tropospheric parameters. Rainfall forecasts reveal that simulations are spatially and quantitatively in accordance with observations and provide better skill scores. The improved land surface characteristics have brought about the realistic evolution of surface, mid-tropospheric parameters, vorticity and moist static energy that facilitates the accurate MDs dynamics in the model. Composite moisture budget analysis reveals that the surface evaporation is negligible compared to moisture flux convergence of water vapor, which supplies moisture into the MDs over land. The temporal relationship between rainfall and moisture convergence show high correlation, suggesting a realistic representation of land state help restructure the moisture inflow into the system through rainfall-moisture convergence feedback.

Multi-Scale Hydrometeorological Modeling, Land Data Assimilation and Parameter Estimation with the Land Information System

NASA Technical Reports Server (NTRS)

Peters-Lidard, Christa D.; Kumar, Sujay V.; Santanello, Joseph A., Jr.; Reichle, Rolf H.

2009-01-01

The Land Information System (LIS; http://lis.gsfc.nasa.gov; Kumar et al., 2006; Peters- Lidard et al.,2007) is a flexible land surface modeling framework that has been developed with the goal of integrating satellite- and ground-based observational data products and advanced land surface modeling techniques to produce optimal fields of land surface states and fluxes. As such, LIS represents a step towards the next generation land component of an integrated Earth system model. In recognition of LIS object-oriented software design, use and impact in the land surface and hydrometeorological modeling community, the LIS software was selected ase co-winner of NASA's 2005 Software of the Year award. LIS facilitates the integration of observations from Earth-observing systems and predictions and forecasts from Earth System and Earth science models into the decision-making processes of partnering agency and national organizations. Due to its flexible software design, LIS can serve both as a Problem Solving Environment (PSE) for hydrologic research to enable accurate global water and energy cycle predictions, and as a Decision Support System (DSS) to generate useful information for application areas including disaster management, water resources management, agricultural management, numerical weather prediction, air quality and military mobility assessment. LIS has evolved from two earlier efforts North American Land Data Assimilation System (NLDAS; Mitchell et al. 2004) and Global Land Data Assimilation System (GLDAS; Rodell al. 2004) that focused primarily on improving numerical weather prediction skills by improving the characterization of the land surface conditions. Both of GLDAS and NLDAS now use specific configurations of the LIS software in their current implementations. In addition, LIS was recently transitioned into operations at the US Air Force Weather Agency (AFWA) to ultimately replace their Agricultural Meteorology (AGRMET) system, and is also used routinely by NOAA's National Centers for Environmental Prediction (NCEP)/Environmental Modeling Center (EMC) for their land data assimilation systems to support weather and climate modeling. LIS not only consolidates the capabilities of these two systems, but also enables a much larger variety of configurations with respect to horizontal spatial resolution, input datasets and choice of land surface model through "plugins,". As described in Kumar et al., 2007, and demonstrated in Case et al., 2008, and Santanello et al., 2009, LIS has been coupled to the Weather Research and Forecasting (WRF) model to support studies of land-atmosphere coupling the enabling ensembles of land surface states to be tested against multiple representations of the atmospheric boundary layer. LIS has also been demonstrated for parameter estimation as described in Peters-Lidard et al. (2008) and Santanello et al. (2007), who showed that the use of sequential remotely sensed soil moisture products can be used to derive soil hydraulic and texture properties given a sufficient dynamic range in the soil moisture retrievals and accurate precipitation inputs. LIS has also recently been demonstrated for multi-model data assimilation (Kumar et al., 2008) using an Ensemble Kalman Filter for sequential assimilation of soil moisture, snow, and temperature. Ongoing work has demonstrated the value of bias correction as part of the filter, and also that of joint calibration and assimilation. Examples and case studies demonstrating the capabilities and impacts of LIS for hydrometeoroogical modeling, assimilation and parameter estimation will be presented as advancements towards the next generation of integrated observation and modeling systems.

The auto-tuned land data assimilation system (ATLAS)

USDA-ARS?s Scientific Manuscript database

Land data assimilation systems are tasked with the merging remotely-sensed soil moisture retrievals with information derived from a soil water balance model driven (principally) by observed rainfall. The performance of such systems is frequently degraded by the imprecise specification of parameters ...

Incorporating JULES into NASA's Land Information System (LIS) and Investigations of Land-Atmosphere Coupling

NASA Technical Reports Server (NTRS)

Santanello, Joseph

2011-01-01

NASA's Land Information System (LIS; lis.gsfc.nasa.gov) is a flexible land surface modeling and data assimilation framework developed over the past decade with the goal of integrating satellite- and ground-based observational data products and advanced land surface modeling techniques to produce optimal fields of land surface states and fluxes. LIS features a high performance and flexible design, and operates on an ensemble of land surface models for extension over user-specified regional or global domains. The extensible interfaces of LIS allow the incorporation of new domains, land surface models (LSMs), land surface parameters, meteorological inputs, data assimilation and optimization algorithms. In addition, LIS has also been demonstrated for parameter estimation and uncertainty estimation, and has been coupled to the Weather Research and Forecasting (WRF) mesoscale model. A visiting fellowship is currently underway to implement JULES into LIS and to undertake some fundamental science on the feedbacks between the land surface and the atmosphere. An overview of the LIS system, features, and sample results will be presented in an effort to engage the community in the potential advantages of LIS-JULES for a range of applications. Ongoing efforts to develop a framework for diagnosing land-atmosphere coupling will also be presented using the suite of LSM and PBL schemes available in LIS and WRF along with observations from the U. S .. Southern Great Plains. This methodology provides a potential pathway to study factors controlling local land-atmosphere coupling (LoCo) using the LIS-WRF system, which will serve as a testbed for future experiments to evaluate coupling diagnostics within the community.

Effect of external disturbances and data rate on the response of an automatic landing system capable of curved trajectories

NASA Technical Reports Server (NTRS)

Sherman, W. L.

1975-01-01

The effects of steady wind, turbulence, data sample rate, and control-actuator natural frequency on the response of a possible automatic landing system were investigated in a nonstatistical study. The results indicate that the system, which interfaces with the microwave landing system, functions well in winds and turbulence as long as the guidance law contains proper compensation for wind. The system response was satisfactory down to five data samples per second, which makes the system compatible with the microwave landing system. No adverse effects were observed when actuator natural frequency was lowered. For limiting cases, those cases where the roll angle goes to zero just as the airplane touches down, the basic method for computing the turn-algorithm gains proved unsatisfactory and unacceptable landings resulted. Revised computation methods gave turn-algorithm gains that resulted in acceptable landings. The gains provided by the new method also improved the touchdown conditions for acceptable landings over those obtained when the gains were determined by the old method.

A Prototype Land Information Sensor Web: Design, Implementation and Implication for the SMAP Mission

NASA Astrophysics Data System (ADS)

Su, H.; Houser, P.; Tian, Y.; Geiger, J. K.; Kumar, S. V.; Gates, L.

2009-12-01

Land Surface Model (LSM) predictions are regular in time and space, but these predictions are influenced by errors in model structure, input variables, parameters and inadequate treatment of sub-grid scale spatial variability. Consequently, LSM predictions are significantly improved through observation constraints made in a data assimilation framework. Several multi-sensor satellites are currently operating which provide multiple global observations of the land surface, and its related near-atmospheric properties. However, these observations are not optimal for addressing current and future land surface environmental problems. To meet future earth system science challenges, NASA will develop constellations of smart satellites in sensor web configurations which provide timely on-demand data and analysis to users, and can be reconfigured based on the changing needs of science and available technology. A sensor web is more than a collection of satellite sensors. That means a sensor web is a system composed of multiple platforms interconnected by a communication network for the purpose of performing specific observations and processing data required to support specific science goals. Sensor webs can eclipse the value of disparate sensor components by reducing response time and increasing scientific value, especially when the two-way interaction between the model and the sensor web is enabled. The study of a prototype Land Information Sensor Web (LISW) is sponsored by NASA, trying to integrate the Land Information System (LIS) in a sensor web framework which allows for optimal 2-way information flow that enhances land surface modeling using sensor web observations, and in turn allows sensor web reconfiguration to minimize overall system uncertainty. This prototype is based on a simulated interactive sensor web, which is then used to exercise and optimize the sensor web modeling interfaces. The Land Information Sensor Web Service-Oriented Architecture (LISW-SOA) has been developed and it is the very first sensor web framework developed especially for the land surface studies. Synthetic experiments based on the LISW-SOA and the virtual sensor web provide a controlled environment in which to examine the end-to-end performance of the prototype, the impact of various sensor web design trade-offs and the eventual value of sensor webs for a particular prediction or decision support. In this paper, the design, implementation of the LISW-SOA and the implication for the Soil Moisture Active and Passive (SMAP) mission is presented. Particular attention is focused on examining the relationship between the economic investment on a sensor web (space and air borne, ground based) and the accuracy of the model predicted soil moisture, which can be achieved by using such sensor observations. The Study of Virtual Land Information Sensor Web (LISW) is expected to provide some necessary a priori knowledge for designing and deploying the next generation Global Earth Observing System of systems (GEOSS).

Benchmarking the performance of a land data assimilation system for agricultural drought monitoring

USDA-ARS?s Scientific Manuscript database

The application of land data assimilation systems to operational agricultural drought monitoring requires the development of (at least) three separate system sub-components: 1) a retrieval model to invert satellite-derived observations into soil moisture estimates, 2) a prognostic soil water balance...

Insights on How NASA's Earth Observing System (EOS) Monitors Our World Environment

NASA Technical Reports Server (NTRS)

King, Michael D.

2000-01-01

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. During this year, four EOS science missions were launched, representing observations of (1) total solar irradiance, (2) Earth radiation budget, (3) land cover and land use change, (4) ocean processes (vector wind, sea surface temperature, and ocean color), (5) atmospheric processes (aerosol and cloud properties, water vapor, and temperature and moisture profiles), and (6) tropospheric chemistry. In succeeding years many more satellites will be launched that will contribute immeasurably to our understanding of the Earth's environment. In this presentation I will describe how scientists are using EOS data to examine land use and natural hazards, environmental air quality, including dust storms over the world's deserts, cloud and radiation properties, sea surface temperature, and winds over the ocean.

The Regional Land Cover Monitoring System: Building regional capacity through innovative land cover mapping approaches

NASA Astrophysics Data System (ADS)

Saah, D.; Tenneson, K.; Hanh, Q. N.; Aekakkararungroj, A.; Aung, K. S.; Goldstein, J.; Cutter, P. G.; Maus, P.; Markert, K. N.; Anderson, E.; Ellenburg, W. L.; Ate, P.; Flores Cordova, A. I.; Vadrevu, K.; Potapov, P.; Phongsapan, K.; Chishtie, F.; Clinton, N.; Ganz, D.

2017-12-01

Earth observation and Geographic Information System (GIS) tools, products, and services are vital to support the environmental decision making by governmental institutions, non-governmental agencies, and the general public. At the heart of environmental decision making is the monitoring land cover and land use change (LCLUC) for land resource planning and for ecosystem services, including biodiversity conservation and resilience to climate change. A major challenge for monitoring LCLUC in developing regions, such as Southeast Asia, is inconsistent data products at inconsistent intervals that have different typologies across the region and are typically made in without stakeholder engagement or input. Here we present the Regional Land Cover Monitoring System (RLCMS), a novel land cover mapping effort for Southeast Asia, implemented by SERVIR-Mekong, a joint NASA-USAID initiative that brings Earth observations to improve environmental decision making in developing countries. The RLCMS focuses on mapping biophysical variables (e.g. canopy cover, tree height, or percent surface water) at an annual interval and in turn using those biophysical variables to develop land cover maps based on stakeholder definitions of land cover classes. This allows for flexible and consistent land cover classifications that can meet the needs of different institutions across the region. Another component of the RLCMS production is the stake-holder engagement through co-development. Institutions that directly benefit from this system have helped drive the development for regional needs leading to services for their specific uses. Examples of services for regional stakeholders include using the RLCMS to develop maps using the IPCC classification scheme for GHG emission reporting and developing custom annual maps as an input to hydrologic modeling/flood forecasting systems. In addition to the implementation of this system and the service stemming from the RLCMS in Southeast Asia, it is planned to replicate the methods presented at the SERVIR-Hindu Kush Himalaya hub serving South Asia. Enhancements to the system will include change detection methods, enhanced biophysical models, and delivery systems.

Validation of the North American Land Data Assimilation System (NLDAS) retrospective forcing over the southern Great Plains

NASA Astrophysics Data System (ADS)

Luo, Lifeng; Robock, Alan; Mitchell, Kenneth E.; Houser, Paul R.; Wood, Eric F.; Schaake, John C.; Lohmann, Dag; Cosgrove, Brian; Wen, Fenghua; Sheffield, Justin; Duan, Qingyun; Higgins, R. Wayne; Pinker, Rachel T.; Tarpley, J. Dan

2003-11-01

Atmospheric forcing used by land surface models is a critical component of the North American Land Data Assimilation System (NLDAS) and its quality crucially affects the final product of NLDAS and our work on model improvement. A three-year (September 1996-September 1999) retrospective forcing data set was created from the Eta Data Assimilation System and observations and used to run the NLDAS land surface models for this period. We compared gridded NLDAS forcing with station observations obtained from networks including the Oklahoma Mesonet and Atmospheric Radiation Measurement/Cloud and Radiation Testbed at the southern Great Plains. Differences in all forcing variables except precipitation between the NLDAS forcing data set and station observations are small at all timescales. While precipitation data do not agree very well at an hourly timescale, they do agree better at longer timescales because of the way NLDAS precipitation forcing is generated. A small high bias in downward solar radiation and a low bias in downward longwave radiation exist in the retrospective forcing. To investigate the impact of these differences on land surface modeling we compared two sets of model simulations, one forced by the standard NLDAS product and one with station-observed meteorology. The differences in the resulting simulations of soil moisture and soil temperature for each model were small, much smaller than the differences between the models and between the models and observations. This indicates that NLDAS retrospective forcing provides an excellent state-of-the-art data set for land surface modeling, at least over the southern Great Plains region.

Validation and Verification of Operational Land Analysis Activities at the Air Force Weather Agency

NASA Technical Reports Server (NTRS)

Shaw, Michael; Kumar, Sujay V.; Peters-Lidard, Christa D.; Cetola, Jeffrey

2012-01-01

The NASA developed Land Information System (LIS) is the Air Force Weather Agency's (AFWA) operational Land Data Assimilation System (LDAS) combining real time precipitation observations and analyses, global forecast model data, vegetation, terrain, and soil parameters with the community Noah land surface model, along with other hydrology module options, to generate profile analyses of global soil moisture, soil temperature, and other important land surface characteristics. (1) A range of satellite data products and surface observations used to generate the land analysis products (2) Global, 1/4 deg spatial resolution (3) Model analysis generated at 3 hours. AFWA recognizes the importance of operational benchmarking and uncertainty characterization for land surface modeling and is developing standard methods, software, and metrics to verify and/or validate LIS output products. To facilitate this and other needs for land analysis activities at AFWA, the Model Evaluation Toolkit (MET) -- a joint product of the National Center for Atmospheric Research Developmental Testbed Center (NCAR DTC), AFWA, and the user community -- and the Land surface Verification Toolkit (LVT), developed at the Goddard Space Flight Center (GSFC), have been adapted to operational benchmarking needs of AFWA's land characterization activities.

A Simplified Land Model (SLM) for use in cloud-resolving models: Formulation and evaluation

NASA Astrophysics Data System (ADS)

Lee, Jungmin M.; Khairoutdinov, Marat

2015-09-01

A Simplified Land Model (SLM) that uses a minimalist set of parameters with a single-layer vegetation and multilevel soil structure has been developed distinguishing canopy and undercanopy energy budgets. The primary motivation has been to design a land model for use in the System for Atmospheric Modeling (SAM) cloud-resolving model to study land-atmosphere interactions with a sufficient level of realism. SLM uses simplified expressions for the transport of heat, moisture, momentum, and radiation in soil-vegetation system. The SLM performance has been evaluated over several land surface types using summertime tower observations of micrometeorological and biophysical data from three AmeriFlux sites, which include grassland, cropland, and deciduous-broadleaf forest. In general, the SLM captures the observed diurnal cycle of surface energy budget and soil temperature reasonably well, although reproducing the evolution of soil moisture, especially after rain events, has been challenging. The SLM coupled to SAM has been applied to the case of summertime shallow cumulus convection over land based on the Atmospheric Radiation Measurements (ARM) Southern Great Plain (SGP) observations. The simulated surface latent and sensible heat fluxes as well as the evolution of thermodynamic profiles in convective boundary layer agree well with the estimates based on the observations. Sensitivity of atmospheric boundary layer development to the soil moisture and different land cover types has been also examined.

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.

Viirs Land Science Investigator-Led Processing System

NASA Astrophysics Data System (ADS)

Devadiga, S.; Mauoka, E.; Roman, M. O.; Wolfe, R. E.; Kalb, V.; Davidson, C. C.; Ye, G.

2015-12-01

The objective of the NASA's Suomi National Polar Orbiting Partnership (S-NPP) Land Science Investigator-led Processing System (Land SIPS), housed at the NASA Goddard Space Flight Center (GSFC), is to produce high quality land products from the Visible Infrared Imaging Radiometer Suite (VIIRS) to extend the Earth System Data Records (ESDRs) developed from NASA's heritage Earth Observing System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the EOS Terra and Aqua satellites. In this paper we will present the functional description and capabilities of the S-NPP Land SIPS, including system development phases and production schedules, timeline for processing, and delivery of land science products based on coordination with the S-NPP Land science team members. The Land SIPS processing stream is expected to be operational by December 2016, generating land products either using the NASA science team delivered algorithms, or the "best-of" science algorithms currently in operation at NASA's Land Product Evaluation and Algorithm Testing Element (PEATE). In addition to generating the standard land science products through processing of the NASA's VIIRS Level 0 data record, the Land SIPS processing system is also used to produce a suite of near-real time products for NASA's application community. Land SIPS will also deliver the standard products, ancillary data sets, software and supporting documentation (ATBDs) to the assigned Distributed Active Archive Centers (DAACs) for archival and distribution. Quality assessment and validation will be an integral part of the Land SIPS processing system; the former being performed at Land Data Operational Product Evaluation (LDOPE) facility, while the latter under the auspices of the CEOS Working Group on Calibration & Validation (WGCV) Land Product Validation (LPV) Subgroup; adopting the best-practices and tools used to assess the quality of heritage EOS-MODIS products generated at the MODIS Adaptive Processing System (MODAPS).

A land data assimilation system for sub-Saharan Africa food and water security applications

PubMed Central

McNally, Amy; Arsenault, Kristi; Kumar, Sujay; Shukla, Shraddhanand; Peterson, Pete; Wang, Shugong; Funk, Chris; Peters-Lidard, Christa D.; Verdin, James P.

2017-01-01

Seasonal agricultural drought monitoring systems, which rely on satellite remote sensing and land surface models (LSMs), are important for disaster risk reduction and famine early warning. These systems require the best available weather inputs, as well as a long-term historical record to contextualize current observations. This article introduces the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS), a custom instance of the NASA Land Information System (LIS) framework. The FLDAS is routinely used to produce multi-model and multi-forcing estimates of hydro-climate states and fluxes over semi-arid, food insecure regions of Africa. These modeled data and derived products, like soil moisture percentiles and water availability, were designed and are currently used to complement FEWS NET’s operational remotely sensed rainfall, evapotranspiration, and vegetation observations. The 30+ years of monthly outputs from the FLDAS simulations are publicly available from the NASA Goddard Earth Science Data and Information Services Center (GES DISC) and recommended for use in hydroclimate studies, early warning applications, and by agro-meteorological scientists in Eastern, Southern, and Western Africa. PMID:28195575

A land data assimilation system for sub-Saharan Africa food and water security applications

USGS Publications Warehouse

McNally, Amy; Arsenault, Kristi; Kumar, Sujay; Shukla, Shraddhanand; Peterson, Pete; Wang, Shugong; Funk, Chris; Peters-Lidard, Christa; Verdin, James

2017-01-01

Seasonal agricultural drought monitoring systems, which rely on satellite remote sensing and land surface models (LSMs), are important for disaster risk reduction and famine early warning. These systems require the best available weather inputs, as well as a long-term historical record to contextualize current observations. This article introduces the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS), a custom instance of the NASA Land Information System (LIS) framework. The FLDAS is routinely used to produce multi-model and multi-forcing estimates of hydro-climate states and fluxes over semi-arid, food insecure regions of Africa. These modeled data and derived products, like soil moisture percentiles and water availability, were designed and are currently used to complement FEWS NET’s operational remotely sensed rainfall, evapotranspiration, and vegetation observations. The 30+ years of monthly outputs from the FLDAS simulations are publicly available from the NASA Goddard Earth Science Data and Information Services Center (GES DISC) and recommended for use in hydroclimate studies, early warning applications, and by agro-meteorological scientists in Eastern, Southern, and Western Africa.

A land data assimilation system for sub-Saharan Africa food and water security applications.

PubMed

McNally, Amy; Arsenault, Kristi; Kumar, Sujay; Shukla, Shraddhanand; Peterson, Pete; Wang, Shugong; Funk, Chris; Peters-Lidard, Christa D; Verdin, James P

2017-02-14

Seasonal agricultural drought monitoring systems, which rely on satellite remote sensing and land surface models (LSMs), are important for disaster risk reduction and famine early warning. These systems require the best available weather inputs, as well as a long-term historical record to contextualize current observations. This article introduces the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS), a custom instance of the NASA Land Information System (LIS) framework. The FLDAS is routinely used to produce multi-model and multi-forcing estimates of hydro-climate states and fluxes over semi-arid, food insecure regions of Africa. These modeled data and derived products, like soil moisture percentiles and water availability, were designed and are currently used to complement FEWS NET's operational remotely sensed rainfall, evapotranspiration, and vegetation observations. The 30+ years of monthly outputs from the FLDAS simulations are publicly available from the NASA Goddard Earth Science Data and Information Services Center (GES DISC) and recommended for use in hydroclimate studies, early warning applications, and by agro-meteorological scientists in Eastern, Southern, and Western Africa.

Data Descriptor: A Land Data Assimilation System for Sub-Saharan Africa Food and Water Security Applications

NASA Technical Reports Server (NTRS)

McNally, Amy; Arsenault, Krist; Kumar, Sujay; Shukla, Shraddhanand; Peter, Pete; Wang, Shugong; Funk, Chris; Peters-Lidard, Christa D.; Verdin, James

2017-01-01

Seasonal agricultural drought monitoring systems, which rely on satellite remote sensing and land surface models (LSMs), are important for disaster risk reduction and famine early warning. These systems require the best available weather inputs, as well as a long-term historical record to contextualize current observations. This article introduces the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS), a custom instance of the NASA Land Information System (LIS) framework. The FLDAS is routinely used to produce multi-model and multi-forcing estimates of hydro-climate states and fluxes over semi-arid, food insecure regions of Africa. These modeled data and derived products, like soil moisture percentiles and water availability, were designed and are currently used to complement FEWSNETs operational remotely sensed rainfall, evapotranspiration, and vegetation observations. The 30+ years of monthly outputs from the FLDAS simulations are publicly available from the NASA Goddard Earth Science Data and Information Services Center (GES DISC) and recommended for use in hydroclimate studies, early warning applications, and by agro-meteorological scientists in Eastern, Southern, and Western Africa.

A land data assimilation system for sub-Saharan Africa food and water security applications

NASA Astrophysics Data System (ADS)

McNally, Amy; Arsenault, Kristi; Kumar, Sujay; Shukla, Shraddhanand; Peterson, Pete; Wang, Shugong; Funk, Chris; Peters-Lidard, Christa D.; Verdin, James P.

2017-02-01

Seasonal agricultural drought monitoring systems, which rely on satellite remote sensing and land surface models (LSMs), are important for disaster risk reduction and famine early warning. These systems require the best available weather inputs, as well as a long-term historical record to contextualize current observations. This article introduces the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS), a custom instance of the NASA Land Information System (LIS) framework. The FLDAS is routinely used to produce multi-model and multi-forcing estimates of hydro-climate states and fluxes over semi-arid, food insecure regions of Africa. These modeled data and derived products, like soil moisture percentiles and water availability, were designed and are currently used to complement FEWS NET's operational remotely sensed rainfall, evapotranspiration, and vegetation observations. The 30+ years of monthly outputs from the FLDAS simulations are publicly available from the NASA Goddard Earth Science Data and Information Services Center (GES DISC) and recommended for use in hydroclimate studies, early warning applications, and by agro-meteorological scientists in Eastern, Southern, and Western Africa.

Modeling and Observational Framework for Diagnosing Local Land-Atmosphere Coupling on Diurnal Time Scales

NASA Technical Reports Server (NTRS)

Santanello, Joseph A., Jr.; Peters-Lidard, Christa D.; Kumar, Sujay V.; Alonge, Charles; Tao, Wei-Kuo

2009-01-01

Land-atmosphere interactions play a critical role in determining the diurnal evolution of both planetary boundary layer (PBL) and land surface temperature and moisture states. The degree of coupling between the land surface and PBL in numerical weather prediction and climate models remains largely unexplored and undiagnosed due to the complex interactions and feedbacks present across a range of scales. Further, uncoupled systems or experiments (e.g., the Project for Intercomparison of Land Parameterization Schemes, PILPS) may lead to inaccurate water and energy cycle process understanding by neglecting feedback processes such as PBL-top entrainment. In this study, a framework for diagnosing local land-atmosphere coupling is presented using a coupled mesoscale model with a suite of PBL and land surface model (LSM) options along with observations during field experiments in the U. S. Southern Great Plains. Specifically, the Weather Research and Forecasting (WRF) model has been coupled to the Land Information System (LIS), which provides a flexible and high-resolution representation and initialization of land surface physics and states. Within this framework, the coupling established by each pairing of the available PBL schemes in WRF with the LSMs in LIS is evaluated in terms of the diurnal temperature and humidity evolution in the mixed layer. The co-evolution of these variables and the convective PBL is sensitive to and, in fact, integrative of the dominant processes that govern the PBL budget, which are synthesized through the use of mixing diagrams. Results show how the sensitivity of land-atmosphere interactions to the specific choice of PBL scheme and LSM varies across surface moisture regimes and can be quantified and evaluated against observations. As such, this methodology provides a potential pathway to study factors controlling local land-atmosphere coupling (LoCo) using the LIS-WRF system, which will serve as a testbed for future experiments to evaluate coupling diagnostics within the community.

Collaborative Point Paper on Border Surveillance Technology

DTIC Science & Technology

2007-12-01

including; Unmanned Aerial Vehicles, Airships, and/or Aerostats, (RF, Electro-Optical, Infrared, Video) • Land- based Sensor Systems (Attended...warning. These ground- based systems are primarily short-range, up to around 500 meters. • Observation towers extend surveillance capabilities many...Foreign Companies Applicable Environment(s Foreign Companies Air Land Maritime Technology 25. BAE Systems PLC (BAE Systems Inc. is a US subsidiary

Systemic change increases forecast uncertainty of land use change models

NASA Astrophysics Data System (ADS)

Verstegen, J. A.; Karssenberg, D.; van der Hilst, F.; Faaij, A.

2013-12-01

Cellular Automaton (CA) models of land use change are based on the assumption that the relationship between land use change and its explanatory processes is stationary. This means that model structure and parameterization are usually kept constant over time, ignoring potential systemic changes in this relationship resulting from societal changes, thereby overlooking a source of uncertainty. Evaluation of the stationarity of the relationship between land use and a set of spatial attributes has been done by others (e.g., Bakker and Veldkamp, 2012). These studies, however, use logistic regression, separate from the land use change model. Therefore, they do not gain information on how to implement the spatial attributes into the model. In addition, they often compare observations for only two points in time and do not check whether the change is statistically significant. To overcome these restrictions, we assimilate a time series of observations of real land use into a land use change CA (Verstegen et al., 2012), using a Bayesian data assimilation technique, the particle filter. The particle filter was used to update the prior knowledge about the parameterization and model structure, i.e. the selection and relative importance of the drivers of location of land use change. In a case study of sugar cane expansion in Brazil, optimal model structure and parameterization were determined for each point in time for which observations were available (all years from 2004 to 2012). A systemic change, i.e. a statistically significant deviation in model structure, was detected for the period 2006 to 2008. In this period the influence on the location of sugar cane expansion of the driver sugar cane in the neighborhood doubled, while the influence of slope and potential yield decreased by 75% and 25% respectively. Allowing these systemic changes to occur in our CA in the future (up to 2022) resulted in an increase in model forecast uncertainty by a factor two compared to the assumption of a stationary system. This means that the assumption of a constant model structure is not adequate and largely underestimates uncertainty in the forecast. Non-stationarity in land use change projections is challenging to model, because it is difficult to determine when the system will change and how. We believe that, in sight of these findings, land use change modelers should be more aware, and communicate more clearly, that what they try to project is at the limits, and perhaps beyond the limits, of what is still projectable. References Bakker, M., Veldkamp, A., 2012. Changing relationships between land use and environmental characteristics and their consequences for spatially explicit land-use change prediction. Journal of Land Use Science 7, 407-424. Verstegen, J.A., Karssenberg, D., van der Hilst, F., Faaij, A.P.C., 2012. Spatio-Temporal Uncertainty in Spatial Decision Support Systems: a Case Study of Changing Land Availability for Bioenergy Crops in Mozambique. Computers , Environment and Urban Systems 36, 30-42.

Evaluation of the AMSR-E Data Calibration Over Land

NASA Technical Reports Server (NTRS)

Njoku, E.; Chan, T.; Crosson, W.; Limaye, A.

2004-01-01

Land observations by the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E), particularly of soil and vegetation moisture changes, have numerous applications in hydrology, ecology and climate. Quantitative retrieval of soil and vegetation parameters relies on accurate calibration of the brightness temperature measurements. Analyses of the spectral and polarization characteristics of early versions of the AMSR-E data revealed significant calibration biases over land at 6.9 GHz. The biases were estimated and removed in the current archived version of the data Radiofrequency interference (RFI) observed at 6.9 GHz is more difficult to quanti@ however. A calibration analysis of AMSR-E data over land is presented in this paper for a complete annual cycle from June 2002 through September 2003. The analysis indicates the general high quality of the data for land applications (except for RFI), and illustrates seasonal trends of the data for different land surface types and regions.

Cross-site comparison of land-use decision-making and its consequences across land systems with a generalized agent-based model.

PubMed

Magliocca, Nicholas R; Brown, Daniel G; Ellis, Erle C

2014-01-01

Local changes in land use result from the decisions and actions of land-users within land systems, which are structured by local and global environmental, economic, political, and cultural contexts. Such cross-scale causation presents a major challenge for developing a general understanding of how local decision-making shapes land-use changes at the global scale. This paper implements a generalized agent-based model (ABM) as a virtual laboratory to explore how global and local processes influence the land-use and livelihood decisions of local land-users, operationalized as settlement-level agents, across the landscapes of six real-world test sites. Test sites were chosen in USA, Laos, and China to capture globally-significant variation in population density, market influence, and environmental conditions, with land systems ranging from swidden to commercial agriculture. Publicly available global data were integrated into the ABM to model cross-scale effects of economic globalization on local land-use decisions. A suite of statistics was developed to assess the accuracy of model-predicted land-use outcomes relative to observed and random (i.e. null model) landscapes. At four of six sites, where environmental and demographic forces were important constraints on land-use choices, modeled land-use outcomes were more similar to those observed across sites than the null model. At the two sites in which market forces significantly influenced land-use and livelihood decisions, the model was a poorer predictor of land-use outcomes than the null model. Model successes and failures in simulating real-world land-use patterns enabled the testing of hypotheses on land-use decision-making and yielded insights on the importance of missing mechanisms. The virtual laboratory approach provides a practical framework for systematic improvement of both theory and predictive skill in land change science based on a continual process of experimentation and model enhancement.

Cross-Site Comparison of Land-Use Decision-Making and Its Consequences across Land Systems with a Generalized Agent-Based Model

PubMed Central

Magliocca, Nicholas R.; Brown, Daniel G.; Ellis, Erle C.

2014-01-01

Local changes in land use result from the decisions and actions of land-users within land systems, which are structured by local and global environmental, economic, political, and cultural contexts. Such cross-scale causation presents a major challenge for developing a general understanding of how local decision-making shapes land-use changes at the global scale. This paper implements a generalized agent-based model (ABM) as a virtual laboratory to explore how global and local processes influence the land-use and livelihood decisions of local land-users, operationalized as settlement-level agents, across the landscapes of six real-world test sites. Test sites were chosen in USA, Laos, and China to capture globally-significant variation in population density, market influence, and environmental conditions, with land systems ranging from swidden to commercial agriculture. Publicly available global data were integrated into the ABM to model cross-scale effects of economic globalization on local land-use decisions. A suite of statistics was developed to assess the accuracy of model-predicted land-use outcomes relative to observed and random (i.e. null model) landscapes. At four of six sites, where environmental and demographic forces were important constraints on land-use choices, modeled land-use outcomes were more similar to those observed across sites than the null model. At the two sites in which market forces significantly influenced land-use and livelihood decisions, the model was a poorer predictor of land-use outcomes than the null model. Model successes and failures in simulating real-world land-use patterns enabled the testing of hypotheses on land-use decision-making and yielded insights on the importance of missing mechanisms. The virtual laboratory approach provides a practical framework for systematic improvement of both theory and predictive skill in land change science based on a continual process of experimentation and model enhancement. PMID:24489696

Land Surface Model Biases and their Impacts on the Assimilation of Snow-related Observations

NASA Astrophysics Data System (ADS)

Arsenault, K. R.; Kumar, S.; Hunter, S. M.; Aman, R.; Houser, P. R.; Toll, D.; Engman, T.; Nigro, J.

2007-12-01

Some recent snow modeling studies have employed a wide range of assimilation methods to incorporate snow cover or other snow-related observations into different hydrological or land surface models. These methods often include taking both model and observation biases into account throughout the model integration. This study focuses more on diagnosing the model biases and presenting their subsequent impacts on assimilating snow observations and modeled snowmelt processes. In this study, the land surface model, the Community Land Model (CLM), is used within the Land Information System (LIS) modeling framework to show how such biases impact the assimilation of MODIS snow cover observations. Alternative in-situ and satellite-based observations are used to help guide the CLM LSM in better predicting snowpack conditions and more realistic timing of snowmelt for a western US mountainous region. Also, MODIS snow cover observation biases will be discussed, and validation results will be provided. The issues faced with inserting or assimilating MODIS snow cover at moderate spatial resolutions (like 1km or less) will be addressed, and the impacts on CLM will be presented.

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

Improving the Fit of a Land-Surface Model to Data Using its Adjoint

NASA Astrophysics Data System (ADS)

Raoult, N.; Jupp, T. E.; Cox, P. M.; Luke, C.

2015-12-01

Land-surface models (LSMs) are of growing importance in the world of climate prediction. They are crucial components of larger Earth system models that are aimed at understanding the effects of land surface processes on the global carbon cycle. The Joint UK Land Environment Simulator (JULES) is the land-surface model used by the UK Met Office. It has been automatically differentiated using commercial software from FastOpt, resulting in an analytical gradient, or 'adjoint', of the model. Using this adjoint, the adJULES parameter estimation system has been developed, to search for locally optimum parameter sets by calibrating against observations. adJULES presents an opportunity to confront JULES with many different observations, and make improvements to the model parameterisation. In the newest version of adJULES, multiple sites can be used in the calibration, to giving a generic set of parameters that can be generalised over plant functional types. We present an introduction to the adJULES system and its applications to data from a variety of flux tower sites. We show that calculation of the 2nd derivative of JULES allows us to produce posterior probability density functions of the parameters and how knowledge of parameter values is constrained by observations.

An Observing System Simulation Experiment of assimilating leaf area index and soil moisture over cropland

NASA Astrophysics Data System (ADS)

Lafont, Sebastien; Barbu, Alina; Calvet, Jean-Christophe

2013-04-01

A Land Data Assimilation System (LDAS) is an off-line data assimilation system featuring uncoupled land surface model which is driven by observation-based atmospheric forcing. In this study the experiments were conducted with a surface externalized (SURFEX) modelling platform developed at Météo-France. It encompasses the land surface model ISBA-A-gs that simulates photosynthesis and plant growth. The photosynthetic activity depends on the vegetation types. The input soil and vegetation parameters are provided by the ECOCLIMAP II global database which assigns the ecosystem classes in several plant functional types as grassland, crops, deciduous forest and coniferous forest. New versions of the model have been recently developed in order to better describe the agricultural plant functional types. We present a set of observing system simulation experiments (OSSE) which asses leaf area index (LAI) and soil moisture assimilation for improving the land surface estimates in a controlled synthetic environment. Synthetic data were assimilated into ISBA-A-gs using an Extended Kalman Filter (EKF). This allows for an understanding of model responses to an augmentation of the number of crop types and different parameters associated to this modification. In addition, the interactions between uncertainties in the model and in the observations were investigated. This study represents the first step of a process that envisages the extension of LDAS to the new versions of the ISBA-A-gs model in order to assimilate remote sensing observations.

Towards Improved High-Resolution Land Surface Hydrologic Reanalysis Using a Physically-Based Hydrologic Model and Data Assimilation

NASA Astrophysics Data System (ADS)

Shi, Y.; Davis, K. J.; Zhang, F.; Duffy, C.; Yu, X.

2014-12-01

A coupled physically based land surface hydrologic model, Flux-PIHM, has been developed by incorporating a land surface scheme into the Penn State Integrated Hydrologic Model (PIHM). The land surface scheme is adapted from the Noah land surface model. Flux-PIHM has been implemented and manually calibrated at the Shale Hills watershed (0.08 km2) in central Pennsylvania. Model predictions of discharge, point soil moisture, point water table depth, sensible and latent heat fluxes, and soil temperature show good agreement with observations. When calibrated only using discharge, and soil moisture and water table depth at one point, Flux-PIHM is able to resolve the observed 101 m scale soil moisture pattern at the Shale Hills watershed when an appropriate map of soil hydraulic properties is provided. A Flux-PIHM data assimilation system has been developed by incorporating EnKF for model parameter and state estimation. Both synthetic and real data assimilation experiments have been performed at the Shale Hills watershed. Synthetic experiment results show that the data assimilation system is able to simultaneously provide accurate estimates of multiple parameters. In the real data experiment, the EnKF estimated parameters and manually calibrated parameters yield similar model performances, but the EnKF method significantly decreases the time and labor required for calibration. The data requirements for accurate Flux-PIHM parameter estimation via data assimilation using synthetic observations have been tested. Results show that by assimilating only in situ outlet discharge, soil water content at one point, and the land surface temperature averaged over the whole watershed, the data assimilation system can provide an accurate representation of watershed hydrology. Observations of these key variables are available with national and even global spatial coverage (e.g., MODIS surface temperature, SMAP soil moisture, and the USGS gauging stations). National atmospheric reanalysis products, soil databases and land cover databases (e.g., NLDAS-2, SSURGO, NLCD) can provide high resolution forcing and input data. Therefore the Flux-PIHM data assimilation system could be readily expanded to other watersheds to provide regional scale land surface and hydrologic reanalysis with high spatial temporal resolution.

Land observation from geosynchronous earth orbit (LOGEO): Mission concept and preliminary engineering analysis

NASA Astrophysics Data System (ADS)

Román-Colón, Miguel O.; Strahler, Alan H.

2007-06-01

We propose an Earth-observation mission Land Observation from Geosynchronous Earth Orbit (LOGEO) to place two spin-scan-stabilized 500-m resolution 9-band VNIR-SWIR imagers in a near-geosynchronous inclined orbit, allowing 15 min observations with a full range of daily sun angles and 30∘ variations in view angle. LOGEO drifts westward at about 4∘ per day, providing geostationary-style coverage for all points on the globe eight times per year. This unique imaging geometry allows accurate retrievals of daily changes in surface bidirectional reflectance, which in turn enhances direct retrieval of biophysical properties, as well as long term and consistent land surface parameters for modeling studies that seek to understand the Earth system and its interactions. For studies of climate and environmental dynamics, LOGEO provides accurate observations of atmospheric aerosols, clouds, as well as other atmospheric constituents across a diverse number of spatial and temporal scales. This collection of land, atmospheric, and climate data products are directly applicable to seven of the nine GEOSS societal benefits areas, providing great opportunities for international collaboration. We also present an overview of LOGEO's systems architecture, as well as top-level design-trade studies and orbital scenarios.

Terrestrial essential climate variables (ECVs) at a glance

USGS Publications Warehouse

Stitt, Susan; Dwyer, John; Dye, Dennis; Josberger, Edward

2011-01-01

The Global Terrestrial Observing System, Global Climate Observing System, World Meteorological Organization, and Committee on Earth Observation Satellites all support consistent global land observations and measurements. To accomplish this goal, the Global Terrestrial Observing System defined 'essential climate variables' as measurements of atmosphere, oceans, and land that are technically and economically feasible for systematic observation and that are needed to meet the United Nations Framework Convention on Climate Change and requirements of the Intergovernmental Panel on Climate Change. The following are the climate variables defined by the Global Terrestrial Observing System that relate to terrestrial measurements. Several of them are currently measured most appropriately by in-place observations, whereas others are suitable for measurement by remote sensing technologies. The U.S. Geological Survey is the steward of the Landsat archive, satellite imagery collected from 1972 to the present, that provides a potential basis for deriving long-term, global-scale, accurate, timely and consistent measurements of many of these essential climate variables.

Evaluating the Utility of Satellite Soil Moisture Retrievals over Irrigated Areas and the Ability of Land Data Assimilation Methods to Correct for Unmodeled Processes

NASA Technical Reports Server (NTRS)

Kumar, S. V.; Peters-Lidard, C. D.; Santanello, J. A.; Reichle, R. H.; Draper, C. S.; Koster, R. D.; Nearing, G.; Jasinski, M. F.

2015-01-01

Earth's land surface is characterized by tremendous natural heterogeneity and human-engineered modifications, both of which are challenging to represent in land surface models. Satellite remote sensing is often the most practical and effective method to observe the land surface over large geographical areas. Agricultural irrigation is an important human-induced modification to natural land surface processes, as it is pervasive across the world and because of its significant influence on the regional and global water budgets. In this article, irrigation is used as an example of a human-engineered, often unmodeled land surface process, and the utility of satellite soil moisture retrievals over irrigated areas in the continental US is examined. Such retrievals are based on passive or active microwave observations from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E), the Advanced Microwave Scanning Radiometer 2 (AMSR2), the Soil Moisture Ocean Salinity (SMOS) mission, WindSat and the Advanced Scatterometer (ASCAT). The analysis suggests that the skill of these retrievals for representing irrigation effects is mixed, with ASCAT-based products somewhat more skillful than SMOS and AMSR2 products. The article then examines the suitability of typical bias correction strategies in current land data assimilation systems when unmodeled processes dominate the bias between the model and the observations. Using a suite of synthetic experiments that includes bias correction strategies such as quantile mapping and trained forward modeling, it is demonstrated that the bias correction practices lead to the exclusion of the signals from unmodeled processes, if these processes are the major source of the biases. It is further shown that new methods are needed to preserve the observational information about unmodeled processes during data assimilation.

Observed Land Impacts on Clouds, Water Vapor, and Rainfall at Continental Scales

NASA Technical Reports Server (NTRS)

Jin, Menglin; King, Michael D.

2005-01-01

How do the continents affect large-scale hydrological cycles? How important can one continent be to the climate system? To address these questions, 4-years of National Aeronautics and Space Administration (NASA) Terra Moderate Resolution Imaging Spectroradiometer (MODIS) observations, Tropical Rainfall Measuring Mission (TRMM) observations, and the Global Precipitation Climatology Project (GPCP) global precipitation analysis, were used to assess the land impacts on clouds, rainfall, and water vapor at continental scales. At these scales, the observations illustrate that continents are integrated regions that enhance the seasonality of atmospheric and surface hydrological parameters. Specifically, the continents of Eurasia and North America enhance the seasonality of cloud optical thickness, cirrus fraction, rainfall, and water vapor. Over land, both liquid water and ice cloud effective radii are smaller than over oceans primarily because land has more aerosol particles. In addition, different continents have similar impacts on hydrological variables in terms of seasonality, but differ in magnitude. For example, in winter, North America and Eurasia increase cloud optical thickness to 17.5 and 16, respectively, while in summer, Eurasia has much smaller cloud optical thicknesses than North America. Such different land impacts are determined by each continent s geographical condition, land cover, and land use. These new understandings help further address the land-ocean contrasts on global climate, help validate global climate model simulated land-atmosphere interactions, and help interpret climate change over land.

Rapid prototyping of soil moisture estimates using the NASA Land Information System

NASA Astrophysics Data System (ADS)

Anantharaj, V.; Mostovoy, G.; Li, B.; Peters-Lidard, C.; Houser, P.; Moorhead, R.; Kumar, S.

2007-12-01

The Land Information System (LIS), developed at the NASA Goddard Space Flight Center, is a functional Land Data Assimilation System (LDAS) that incorporates a suite of land models in an interoperable computational framework. LIS has been integrated into a computational Rapid Prototyping Capabilities (RPC) infrastructure. LIS consists of a core, a number of community land models, data servers, and visualization systems - integrated in a high-performance computing environment. The land surface models (LSM) in LIS incorporate surface and atmospheric parameters of temperature, snow/water, vegetation, albedo, soil conditions, topography, and radiation. Many of these parameters are available from in-situ observations, numerical model analysis, and from NASA, NOAA, and other remote sensing satellite platforms at various spatial and temporal resolutions. The computational resources, available to LIS via the RPC infrastructure, support e- Science experiments involving the global modeling of land-atmosphere studies at 1km spatial resolutions as well as regional studies at finer resolutions. The Noah Land Surface Model, available with-in the LIS is being used to rapidly prototype soil moisture estimates in order to evaluate the viability of other science applications for decision making purposes. For example, LIS has been used to further extend the utility of the USDA Soil Climate Analysis Network of in-situ soil moisture observations. In addition, LIS also supports data assimilation capabilities that are used to assimilate remotely sensed soil moisture retrievals from the AMSR-E instrument onboard the Aqua satellite. The rapid prototyping of soil moisture estimates using LIS and their applications will be illustrated during the presentation.

Decision analysis and risk models for land development affecting infrastructure systems.

PubMed

Thekdi, Shital A; Lambert, James H

2012-07-01

Coordination and layering of models to identify risks in complex systems such as large-scale infrastructure of energy, water, and transportation is of current interest across application domains. Such infrastructures are increasingly vulnerable to adjacent commercial and residential land development. Land development can compromise the performance of essential infrastructure systems and increase the costs of maintaining or increasing performance. A risk-informed approach to this topic would be useful to avoid surprise, regret, and the need for costly remedies. This article develops a layering and coordination of models for risk management of land development affecting infrastructure systems. The layers are: system identification, expert elicitation, predictive modeling, comparison of investment alternatives, and implications of current decisions for future options. The modeling layers share a focus on observable factors that most contribute to volatility of land development and land use. The relevant data and expert evidence include current and forecasted growth in population and employment, conservation and preservation rules, land topography and geometries, real estate assessments, market and economic conditions, and other factors. The approach integrates to a decision framework of strategic considerations based on assessing risk, cost, and opportunity in order to prioritize needs and potential remedies that mitigate impacts of land development to the infrastructure systems. The approach is demonstrated for a 5,700-mile multimodal transportation system adjacent to 60,000 tracts of potential land development. © 2011 Society for Risk Analysis.

The NASA-Goddard Multi-Scale Modeling Framework - Land Information System: Global Land/atmosphere Interaction with Resolved Convection

NASA Technical Reports Server (NTRS)

Mohr, Karen Irene; Tao, Wei-Kuo; Chern, Jiun-Dar; Kumar, Sujay V.; Peters-Lidard, Christa D.

2013-01-01

The present generation of general circulation models (GCM) use parameterized cumulus schemes and run at hydrostatic grid resolutions. To improve the representation of cloud-scale moist processes and landeatmosphere interactions, a global, Multi-scale Modeling Framework (MMF) coupled to the Land Information System (LIS) has been developed at NASA-Goddard Space Flight Center. The MMFeLIS has three components, a finite-volume (fv) GCM (Goddard Earth Observing System Ver. 4, GEOS-4), a 2D cloud-resolving model (Goddard Cumulus Ensemble, GCE), and the LIS, representing the large-scale atmospheric circulation, cloud processes, and land surface processes, respectively. The non-hydrostatic GCE model replaces the single-column cumulus parameterization of fvGCM. The model grid is composed of an array of fvGCM gridcells each with a series of embedded GCE models. A horizontal coupling strategy, GCE4fvGCM4Coupler4LIS, offered significant computational efficiency, with the scalability and I/O capabilities of LIS permitting landeatmosphere interactions at cloud-scale. Global simulations of 2007e2008 and comparisons to observations and reanalysis products were conducted. Using two different versions of the same land surface model but the same initial conditions, divergence in regional, synoptic-scale surface pressure patterns emerged within two weeks. The sensitivity of largescale circulations to land surface model physics revealed significant functional value to using a scalable, multi-model land surface modeling system in global weather and climate prediction.

Mapping urban land cover from space: Some observations for future progress

NASA Technical Reports Server (NTRS)

Gaydos, L.

1982-01-01

The multilevel classification system adopted by the USGS for operational mapping of land use and land cover at levels 1 and 2 is discussed and the successes and failures of mapping land cover from LANDSAT digital data are reviewed. Techniques used for image interpretation and their relationships to sensor parameters are examined. The requirements for mapping levels 2 and 3 classes are considered.

Exploring the effects of drastic institutional and socio-economic changes on land system dynamics in Germany between 1883 and 2007

PubMed Central

Niedertscheider, Maria; Kuemmerle, Tobias; Müller, Daniel; Erb, Karl-Heinz

2014-01-01

Long-term studies of land system change can help providing insights into the relative importance of underlying drivers of change. Here, we analyze land system change in Germany for the period 1883–2007 to trace the effect of drastic socio-economic and institutional changes on land system dynamics. Germany is an especially interesting case study due to fundamentally changing economic and institutional conditions: the two World Wars, the separation into East and West Germany, the accession to the European Union, and Germany's reunification. We employed the Human Appropriation of Net Primary Production (HANPP) framework to comprehensively study long-term land system dynamics in the context of these events. HANPP quantifies biomass harvests and land-use-related changes in ecosystem productivity. By comparing these flows to the potential productivity of ecosystems, HANPP allows to consistently assess land cover changes as well as changes in land use intensity. Our results show that biomass harvest steadily increased while productivity losses declined from 1883 to 2007, leading to a decline in HANPP from around 75%–65% of the potential productivity. At the same time, decreasing agricultural areas allowed for forest regrowth. Overall, land system change in Germany was surprisingly gradual, indicating high resilience to the drastic socio-economic and institutional shifts that occurred during the last 125 years. We found strikingly similar land system trajectories in East and West Germany during the time of separation (1945–1989), despite the contrasting institutional settings and economic paradigms. Conversely, the German reunification sparked a fundamental and rapid shift in former East Germany's land system, leading to altered levels of production, land use intensity and land use efficiency. Gradual and continuous land use intensification, a result of industrialization and economic optimization of land use, was the dominant trend throughout the observed period, apparently overruling socio-economic framework conditions and land use policies. PMID:25844027

Extreme Rock Distributions on Mars and Implications for Landing Safety

NASA Technical Reports Server (NTRS)

Golombek, M. P.

2001-01-01

Prior to the landing of Mars Pathfinder, the size-frequency distribution of rocks from the two Viking landing sites and Earth analog surfaces was used to derive a size-frequency model, for nomimal rock distributions on Mars. This work, coupled with extensive testing of the Pathfinder airbag landing system, allowed an estimate of what total rock abundances derived from thermal differencing techniques could be considered safe for landing. Predictions based on this model proved largely correct at predicting the size-frequency distribution of rocks at the Mars Pathfinder site and the fraction of potentially hazardous rocks. In this abstract, extreme rock distributions observed in Mars Orbiter Camera (MOC) images are compared with those observed at the three landing sites and model distributions as an additional constraint on potentially hazardous surfaces on Mars.

eFarm: A Tool for Better Observing Agricultural Land Systems

PubMed Central

Yu, Qiangyi; Shi, Yun; Tang, Huajun; Yang, Peng; Xie, Ankun; Liu, Bin; Wu, Wenbin

2017-01-01

Currently, observations of an agricultural land system (ALS) largely depend on remotely-sensed images, focusing on its biophysical features. While social surveys capture the socioeconomic features, the information was inadequately integrated with the biophysical features of an ALS and the applications are limited due to the issues of cost and efficiency to carry out such detailed and comparable social surveys at a large spatial coverage. In this paper, we introduce a smartphone-based app, called eFarm: a crowdsourcing and human sensing tool to collect the geotagged ALS information at the land parcel level, based on the high resolution remotely-sensed images. We illustrate its main functionalities, including map visualization, data management, and data sensing. Results of the trial test suggest the system works well. We believe the tool is able to acquire the human–land integrated information which is broadly-covered and timely-updated, thus presenting great potential for improving sensing, mapping, and modeling of ALS studies. PMID:28245554

Retrieval of land parameters by multi-sensor information using the Earth Observation Land Data Assimilation System

NASA Astrophysics Data System (ADS)

Chernetskiy, Maxim; Gobron, Nadine; Gomez-Dans, Jose; Disney, Mathias

2016-07-01

Upcoming satellite constellations will substantially increase the amount of Earth Observation (EO) data, and presents us with the challenge of consistently using all these available information to infer the state of the land surface, parameterised through Essential Climate Variables (ECVs). A promising approach to this problem is the use of physically based models that describe the processes that generate the images, using e.g. radiative transfer (RT) theory. However, these models need to be inverted to infer the land surface parameters from the observations, and there is often not enough information in the EO data to satisfactorily achieve this. Data assimilation (DA) approaches supplement the EO data with prior information in the form of models or prior parameter distributions, and have the potential for solving the inversion problem. These methods however are computationally expensive. In this study, we show the use of fast surrogate models of the RT codes (emulators) based on Gaussian Processes (Gomez-Dans et al, 2016) embedded with the Earth Observation Land Data Assimilation System (EO-LDAS) framework (Lewis et al 2012) in order to estimate the surface of the land surface from a heterogeneous set of optical observations. The study uses time series of moderate spatial resolution observations from MODIS (250 m), MERIS (300 m) and MISR (275 m) over one site to infer the temporal evolution of a number of land surface parameters (and associated uncertainties) related to vegetation: leaf area index (LAI), leaf chlorophyll content, etc. These parameter estimates are then used as input to an RT model (semidiscrete or PROSAIL, for example) to calculate fluxes such as broad band albedo or fAPAR. The study demonstrates that blending different sensors in a consistent way using physical models results in a rich and coherent set of land surface parameters retrieved, with quantified uncertainties. The use of RT models also allows for the consistent prediction of fluxes, with a simple mechanism for propagating the uncertainty in the land surface parameters to the flux estimates.

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.

Surface Hydrology in Global River Basins in the Off-Line Land-Surface GEOS Assimilation (OLGA) System

NASA Technical Reports Server (NTRS)

Bosilovich, Michael G.; Yang, Runhua; Houser, Paul R.

1998-01-01

Land surface hydrology for the Off-line Land-surface GEOS Analysis (OLGA) system and Goddard Earth Observing System (GEOS-1) Data Assimilation System (DAS) has been examined using a river routing model. The GEOS-1 DAS land-surface parameterization is very simple, using an energy balance prediction of surface temperature and prescribed soil water. OLGA uses near-surface atmospheric data from the GEOS-1 DAS to drive a more comprehensive parameterization of the land-surface physics. The two global systems are evaluated using a global river routing model. The river routing model uses climatologic surface runoff from each system to simulate the river discharge from global river basins, which can be compared to climatologic river discharge. Due to the soil hydrology, the OLGA system shows a general improvement in the simulation of river discharge compared to the GEOS-1 DAS. Snowmelt processes included in OLGA also have a positive effect on the annual cycle of river discharge and source runoff. Preliminary tests of a coupled land-atmosphere model indicate improvements to the hydrologic cycle compared to the uncoupled system. The river routing model has provided a useful tool in the evaluation of the GCM hydrologic cycle, and has helped quantify the influence of the more advanced land surface model.

Method and Early Results of Applying the Global Land Data Assimilation System (GLDAS) in the Third Global Reanalysis of NCEP

NASA Astrophysics Data System (ADS)

Meng, J.; Mitchell, K.; Wei, H.; Yang, R.; Kumar, S.; Geiger, J.; Xie, P.

2008-05-01

Over the past several years, the Environmental Modeling Center (EMC) of the National Centers for Environmental Prediction (NCEP) of the U.S. National Weather Service has developed a Global Land Data Assimilation System (GLDAS). For its computational infrastructure, the GLDAS applies the NASA Land Information System (LIS), developed by the Hydrological Science Branch of NASA Goddard Space Flight Center. The land model utilized in the NCEP GLDAS is the NCEP Noah Land Surface Model (Noah LSM). This presentation will 1) describe how the GLDAS component has been included in the development of NCEP's third global reanalysis (with special attention to the input sources of global precipitation), and 2) will present results from the GLDAS component of pilot tests of the new NCEP global reanalysis. Unlike NCEP's past two global reanalysis projects, this new NCEP global reanalysis includes both a global land data assimilation system (GLDAS) and a global ocean data assimilation system (GODAS). The new global reanalysis will span 30-years (1979-2008) and will include a companion realtime operational component. The atmospheric, ocean, and land states of this global reanalysis will provide the initial conditions for NCEP's 3rd- generation global coupled Climate Forecast System (CFS). NCEP is now preparing to launch a 28-year seasonal reforecast project with its new CFS, to provide the reforecast foundation for operational NCEP seasonal climate forecasts using the new CFS. Together, the new global reanalysis and companion CFS reforecasts constitute what NCEP calls the Climate Forecast System Reanalysis and Reforecast (CFSRR) project. Compared to the previous two generations of NCEP global reanalysis, the hallmark of the GLDAS component of CFSRR is GLDAS use of global analyses of observed precipitation to drive the land surface component of the reanalysis (rather than the typical reanalysis approach of using precipitation from the assimilating background atmospheric model). Specifically, the GLDAS merges two global analyses of observed precipitation produced by the Climate Prediction Center (CPC) of NCEP, as follows: 1) a new CPC daily gauge-only land-only global precipitation analysis at 0.5-degree resolution and 2) the well-known CPC CMAP global 2.0 x 2.5 degree 5-day precipitation analysis, which utilizes satellite estimates of precipitation, as well as some gauge observations. The presentation will describe how these two analyses are merged with latitude-dependent weights that favor the gauge-only analysis in mid-latitudes and the satellite-dominated CMAP analysis in tropical latitudes. Finally, we will show some impacts of using GLDAS to initialize the land states of seasonal CFS reforecasts, versus using the previous generation of NCEP global reanalysis as the source for CFS initial land states.

Nutrient cycle benchmarks for earth system land model

NASA Astrophysics Data System (ADS)

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

2017-12-01

Projecting future biosphere-climate feedbacks using Earth system models (ESMs) relies heavily on robust modeling of land surface carbon dynamics. More importantly, soil nutrient (particularly, nitrogen (N) and phosphorus (P)) dynamics strongly modulate carbon dynamics, such as plant sequestration of atmospheric CO2. Prevailing ESM land models all consider nitrogen as a potentially limiting nutrient, and several consider phosphorus. However, including nutrient cycle processes in ESM land models potentially introduces large uncertainties that could be identified and addressed by improved observational constraints. We describe the development of two nutrient cycle benchmarks for ESM land models: (1) nutrient partitioning between plants and soil microbes inferred from 15N and 33P tracers studies and (2) nutrient limitation effects on carbon cycle informed by long-term fertilization experiments. We used these benchmarks to evaluate critical hypotheses regarding nutrient cycling and their representation in ESMs. We found that a mechanistic representation of plant-microbe nutrient competition based on relevant functional traits best reproduced observed plant-microbe nutrient partitioning. We also found that for multiple-nutrient models (i.e., N and P), application of Liebig's law of the minimum is often inaccurate. Rather, the Multiple Nutrient Limitation (MNL) concept better reproduces observed carbon-nutrient interactions.

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.

An Integrated High Resolution Hydrometeorological Modeling Testbed using LIS and WRF

NASA Technical Reports Server (NTRS)

Kumar, Sujay V.; Peters-Lidard, Christa D.; Eastman, Joseph L.; Tao, Wei-Kuo

2007-01-01

Scientists have made great strides in modeling physical processes that represent various weather and climate phenomena. Many modeling systems that represent the major earth system components (the atmosphere, land surface, and ocean) have been developed over the years. However, developing advanced Earth system applications that integrates these independently developed modeling systems have remained a daunting task due to limitations in computer hardware and software. Recently, efforts such as the Earth System Modeling Ramework (ESMF) and Assistance for Land Modeling Activities (ALMA) have focused on developing standards, guidelines, and computational support for coupling earth system model components. In this article, the development of a coupled land-atmosphere hydrometeorological modeling system that adopts these community interoperability standards, is described. The land component is represented by the Land Information System (LIS), developed by scientists at the NASA Goddard Space Flight Center. The Weather Research and Forecasting (WRF) model, a mesoscale numerical weather prediction system, is used as the atmospheric component. LIS includes several community land surface models that can be executed at spatial scales as fine as 1km. The data management capabilities in LIS enable the direct use of high resolution satellite and observation data for modeling. Similarly, WRF includes several parameterizations and schemes for modeling radiation, microphysics, PBL and other processes. Thus the integrated LIS-WRF system facilitates several multi-model studies of land-atmosphere coupling that can be used to advance earth system studies.

DasPy – Open Source Multivariate Land Data Assimilation Framework with High Performance Computing

NASA Astrophysics Data System (ADS)

Han, Xujun; Li, Xin; Montzka, Carsten; Kollet, Stefan; Vereecken, Harry; Hendricks Franssen, Harrie-Jan

2015-04-01

Data assimilation has become a popular method to integrate observations from multiple sources with land surface models to improve predictions of the water and energy cycles of the soil-vegetation-atmosphere continuum. In recent years, several land data assimilation systems have been developed in different research agencies. Because of the software availability or adaptability, these systems are not easy to apply for the purpose of multivariate land data assimilation research. Multivariate data assimilation refers to the simultaneous assimilation of observation data for multiple model state variables into a simulation model. Our main motivation was to develop an open source multivariate land data assimilation framework (DasPy) which is implemented using the Python script language mixed with C++ and Fortran language. This system has been evaluated in several soil moisture, L-band brightness temperature and land surface temperature assimilation studies. The implementation allows also parameter estimation (soil properties and/or leaf area index) on the basis of the joint state and parameter estimation approach. LETKF (Local Ensemble Transform Kalman Filter) is implemented as the main data assimilation algorithm, and uncertainties in the data assimilation can be represented by perturbed atmospheric forcings, perturbed soil and vegetation properties and model initial conditions. The CLM4.5 (Community Land Model) was integrated as the model operator. The CMEM (Community Microwave Emission Modelling Platform), COSMIC (COsmic-ray Soil Moisture Interaction Code) and the two source formulation were integrated as observation operators for assimilation of L-band passive microwave, cosmic-ray soil moisture probe and land surface temperature measurements, respectively. DasPy is parallelized using the hybrid MPI (Message Passing Interface) and OpenMP (Open Multi-Processing) techniques. All the input and output data flow is organized efficiently using the commonly used NetCDF file format. Online 1D and 2D visualization of data assimilation results is also implemented to facilitate the post simulation analysis. In summary, DasPy is a ready to use open source parallel multivariate land data assimilation framework.

An Overview of Future NASA Missions, Concepts, and Technologies Related to Imaging of the World's Land Areas

NASA Technical Reports Server (NTRS)

Salomonson, Vincent V.

1999-01-01

In the near term NASA is entering into the peak activity period of the Earth Observing System (EOS). The EOS AM-1 /"Terra" spacecraft is nearing launch and operation to be followed soon by the New Millennium Program (NMP) Earth Observing (EO-1) mission. Other missions related to land imaging and studies include EOS PM-1 mission, the Earth System Sciences Program (ESSP) Vegetation Canopy Lidar (VCL) mission, the EOS/IceSat mission. These missions involve clear advances in technologies and observational capability including improvements in multispectral imaging and other observing strategies, for example, "formation flying". Plans are underway to define the next era of EOS missions, commonly called "EOS Follow-on" or EOS II. The programmatic planning includes concepts that represent advances over the present Landsat-7 mission that concomitantly recognize the advances being made in land imaging within the private sector. The National Polar Orbiting Environmental Satellite Series (NPOESS) Preparatory Project (NPP) is an effort that will help to transition EOS medium resolution (herein meaning spatial resolutions near 500 meters), multispectral measurement capabilities such as represented by the EOS Moderate Resolution Imaging Spectroradiometer (MODIS) into the NPOESS operational series of satellites. Developments in Synthetic Aperture Radar (SAR) and passive microwave land observing capabilities are also proceeding. Beyond these efforts the Earth Science Enterprise Technology Strategy is embarking efforts to advance technologies in several basic areas: instruments, flight systems and operational capability, and information systems. In the case of instruments architectures will be examined that offer significant reductions in mass, volume, power and observational flexibility. For flight systems and operational capability, formation flying including calibration and data fusion, systems operation autonomy, and mechanical and electronic innovations that can reduce spacecraft and subsystem resource requirements. The efforts in information systems will include better approaches for linking multiple data sets, extracting and visualizing information, and improvements in collecting, compressing, transmitting, processing, distributing and archiving data from multiple platforms. Overall concepts such as sensor webs, constellations of observing systems, and rapid and tailored data availability and delivery to multiple users comprise and notions Earth Science Vision for the future.

Evaluation of various LandFlux evapotranspiration algorithms using the LandFlux-EVAL synthesis benchmark products and observational data

NASA Astrophysics Data System (ADS)

Michel, Dominik; Hirschi, Martin; Jimenez, Carlos; McCabe, Mathew; Miralles, Diego; Wood, Eric; Seneviratne, Sonia

2014-05-01

Research on climate variations and the development of predictive capabilities largely rely on globally available reference data series of the different components of the energy and water cycles. Several efforts aimed at producing large-scale and long-term reference data sets of these components, e.g. based on in situ observations and remote sensing, in order to allow for diagnostic analyses of the drivers of temporal variations in the climate system. Evapotranspiration (ET) is an essential component of the energy and water cycle, which can not be monitored directly on a global scale by remote sensing techniques. In recent years, several global multi-year ET data sets have been derived from remote sensing-based estimates, observation-driven land surface model simulations or atmospheric reanalyses. The LandFlux-EVAL initiative presented an ensemble-evaluation of these data sets over the time periods 1989-1995 and 1989-2005 (Mueller et al. 2013). Currently, a multi-decadal global reference heat flux data set for ET at the land surface is being developed within the LandFlux initiative of the Global Energy and Water Cycle Experiment (GEWEX). This LandFlux v0 ET data set comprises four ET algorithms forced with a common radiation and surface meteorology. In order to estimate the agreement of this LandFlux v0 ET data with existing data sets, it is compared to the recently available LandFlux-EVAL synthesis benchmark product. Additional evaluation of the LandFlux v0 ET data set is based on a comparison to in situ observations of a weighing lysimeter from the hydrological research site Rietholzbach in Switzerland. These analyses serve as a test bed for similar evaluation procedures that are envisaged for ESA's WACMOS-ET initiative (http://wacmoset.estellus.eu). Reference: Mueller, B., Hirschi, M., Jimenez, C., Ciais, P., Dirmeyer, P. A., Dolman, A. J., Fisher, J. B., Jung, M., Ludwig, F., Maignan, F., Miralles, D. G., McCabe, M. F., Reichstein, M., Sheffield, J., Wang, K., Wood, E. F., Zhang, Y., and Seneviratne, S. I. (2013). Benchmark products for land evapotranspiration: LandFlux-EVAL multi-data set synthesis. Hydrology and Earth System Sciences, 17(10): 3707-3720.

Evaluation of snow modeling with Noah and Noah-MP land surface models in NCEP GFS/CFS system

NASA Astrophysics Data System (ADS)

Dong, J.; Ek, M. B.; Wei, H.; Meng, J.

2017-12-01

Land surface serves as lower boundary forcing in global forecast system (GFS) and climate forecast system (CFS), simulating interactions between land and the atmosphere. Understanding the underlying land model physics is a key to improving weather and seasonal prediction skills. With the upgrades in land model physics (e.g., release of newer versions of a land model), different land initializations, changes in parameterization schemes used in the land model (e.g., land physical parametrization options), and how the land impact is handled (e.g., physics ensemble approach), it always prompts the necessity that climate prediction experiments need to be re-conducted to examine its impact. The current NASA LIS (version 7) integrates NOAA operational land surface and hydrological models (NCEP's Noah, versions from 2.7.1 to 3.6 and the future Noah-MP), high-resolution satellite and observational data, and land DA tools. The newer versions of the Noah LSM used in operational models have a variety of enhancements compared to older versions, where the Noah-MP allows for different physics parameterization options and the choice could have large impact on physical processes underlying seasonal predictions. These impacts need to be reexamined before implemented into NCEP operational systems. A set of offline numerical experiments driven by the GFS forecast forcing have been conducted to evaluate the impact of snow modeling with daily Global Historical Climatology Network (GHCN).

Soil Moisture Active Passive (SMAP) Mission Level 4 Carbon (L4_C) Product Specification Document

NASA Technical Reports Server (NTRS)

Glassy, Joe; Kimball, John S.; Jones, Lucas; Reichle, Rolf H.; Ardizzone, Joseph V.; Kim, Gi-Kong; Lucchesi, Robert A.; Smith, Edmond B.; Weiss, Barry H.

2015-01-01

This is the Product Specification Document (PSD) for Level 4 Surface and Root Zone Soil Moisture (L4_SM) data for the Science Data System (SDS) of the Soil Moisture Active Passive (SMAP) project. The L4_SM data product provides estimates of land surface conditions based on the assimilation of SMAP observations into a customized version of the NASA Goddard Earth Observing System, Version 5 (GEOS-5) land data assimilation system (LDAS). This document applies to any standard L4_SM data product generated by the SMAP Project.

Estimates of Soil Moisture Using the Land Information System for Land Surface Water Storage: Case Study for the Western States Water Mission

NASA Astrophysics Data System (ADS)

Liu, P. W.; Famiglietti, J. S.; Levoe, S.; Reager, J. T., II; David, C. H.; Kumar, S.; Li, B.; Peters-Lidard, C. D.

2017-12-01

Soil moisture is one of the critical factors in terrestrial hydrology. Accurate soil moisture information improves estimation of terrestrial water storage and fluxes, that is essential for water resource management including sustainable groundwater pumping and agricultural irrigation practices. It is particularly important during dry periods when water stress is high. The Western States Water Mission (WSWM), a multiyear mission project of NASA's Jet Propulsion Laboratory, is operated to understand and estimate quantities of the water availability in the western United States by integrating observations and measurements from in-situ and remote sensing sensors, and hydrological models. WSWM data products have been used to assess and explore the adverse impacts of the California drought (2011-2016) and provide decision-makers information for water use planning. Although the observations are often more accurate, simulations using land surface models can provide water availability estimates at desired spatio-temporal scales. The Land Information System (LIS), developed by NASA's Goddard Space Flight Center, integrates developed land surface models and data processing and management tools, that enables to utilize the measurements and observations from various platforms as forcings in the high performance computing environment to forecast the hydrologic conditions. The goal of this study is to implement the LIS in the western United States for estimates of soil moisture. We will implement the NOAH-MP model at the 12km North America Land Data Assimilation System grid and compare to other land surface models included in the LIS. Findings will provide insight into the differences between model estimates and model physics. Outputs from a multi-model ensemble from LIS can also be used to enhance estimated reliability and provide quantification of uncertainty. We will compare the LIS-based soil moisture estimates to the SMAP enhanced 9 km soil moisture product to understand the mechanistic differences between the model and observation. These outcomes will contribute to the WSWM for providing robust products.

Potential impacts on Colorado Rocky Mountain weather due to land use changes on the adjacent Great Plains

USGS Publications Warehouse

Chase, T.N.; Pielke, R.A.; Kittel, T.G.F.; Baron, Jill S.; Stohlgren, T.J.

1999-01-01

Evidence from both meteorological stations and vegetational successional studies suggests that summer temperatures are decreasing in the mountain-plain system in northeast Colorado, particularly since the early 1980s. These trends are coincident with large changes in regional land cover. Trends in global, Northern Hemisphere and continental surface temperatures over the same period are insignificant. These observations suggest that changes in the climate of this mountain-plain system may be, in some part, a result of localized forcing mechanisms. In this study the effects of land use change on the northern Colorado plains, where large regions of grasslands have been transformed into both dry and irrigated agricultural lands, on regional weather is examined in an effort to understand this local deviation from larger-scale trends. We find with high-resolution numerical simulations of a 3-day summer period using a regional atmospheric-land surface model that replacing grasslands with irrigated and dry farmland can have impacts on regional weather and therefore climate which are not limited to regions of direct forcing. Higher elevations remote from regions of land use change are affected as well. Specifically, cases with altered landcover had cooler, moister boundary layers, and diminished low-level upslope winds over portions of the plains. At higher elevations, temperatures also were lower as was low-level convergence. Precipitation and cloud cover were substantially affected in mountain regions. We advance the hypothesis that observed land use changes may have already had a role in explaining part of the observed climate record in the northern Colorado mountain-plain system. Copyright 1999 by the American Geophysical Union.

Ground displacements caused by aquifer-system water-level variations observed using interferometric synthetic aperture radar near Albuquerque, New Mexico

USGS Publications Warehouse

Heywood, Charles E.; Galloway, Devin L.; Stork, Sylvia V.

2002-01-01

Six synthetic aperture radar (SAR) images were processed to form five unwrapped interferometric (InSAR) images of the greater metropolitan area in the Albuquerque Basin. Most interference patterns in the images were caused by range displacements resulting from changes in land-surface elevation. Loci of land- surface elevation changes correlate with changes in aquifer-system water levels and largely result from the elastic response of the aquifer-system skeletal material to changes in pore-fluid pressure. The magnitude of the observed land-surface subsidence and rebound suggests that aquifer-system deformation resulting from ground-water withdrawals in the Albuquerque area has probably remained in the elastic (recoverable) range from July 1993 through September 1999. Evidence of inelastic (permanent) land subsidence in the Rio Rancho area exists, but its relation to compaction of the aquifer system is inconclusive because of insufficient water-level data. Patterns of elastic deformation in both Albuquerque and Rio Rancho suggest that intrabasin faults impede ground- water-pressure diffusion at seasonal time scales and that these faults are probably important in controlling patterns of regional ground-water flow.

NASA's Earth Observing System (EOS): Observing the Atmosphere, Land, Oceans, and Ice from Space

NASA Technical Reports Server (NTRS)

King, Michael D.

2004-01-01

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. During this year, the last of the first series of EOS missions, Aura, was launched. Aura is designed exclusively to conduct research on the composition, chemistry, and dynamics of the Earth's upper and lower atmosphere, employing multiple instruments on a single spacecraft. Aura is the third in a series of major Earth observing satellites to study the environment and climate change and is part of NASA's Earth Science Enterprise. The first and second missions, Terra and Aqua, are designed to study the land, oceans, atmospheric constituents (aerosols, clouds, temperature, and water vapor), and the Earth's radiation budget. The other seven EOS spacecraft include satellites to study (i) land cover & land use change, (ii) solar irradiance and solar spectral variation, (iii) ice volume, (iv) ocean processes (vector wind and sea surface topography), and (v) vertical variations of clouds, water vapor, and aerosols up to and including the stratosphere. Aura's chemistry measurements will also follow up on measurements that began with NASA's Upper Atmosphere Research Satellite and continue the record of satellite ozone data collected from the TOMS missions. In this presentation I will describe how scientists are using EOS data to examine the health of the earth's atmosphere, including atmospheric chemistry, aerosol properties, and cloud properties, with a special but not exclusive look at the latest earth observing mission, Aura.

NASA's Earth Observing System (EOS): Observing the Atmosphere, Land, Oceans, and Ice from Space

NASA Technical Reports Server (NTRS)

King, Michael D.

2005-01-01

The Earth Observing System (EOS) is a space-based observing system comprised of a series of satellite sensors by whch 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. During this year, the last of the first series of EOS missions, Aura, was launched. Aura is designed exclusively to conduct research on the composition, chemistry, and dynamics of the Earth's upper and lower atmosphere, employing multiple instruments on a single spacecraft. Aura is the third in a series of major Earth observing satellites to study the environment and climate change and is part of NASA's Earth Science Enterprise. The first and second missions, Terra and Aqua, are designed to study the land, oceans, atmospheric constituents (aerosols, clouds, temperature, and water vapor), and the Earth's radiation budget. The other seven EOS spacecraft include satellites to study (i) land cover & land use change, (ii) solar irradiance and solar spectral variation, (iii) ice volume, (iv) ocean processes (vector wind and sea surface topography), and (v) vertical variations of clouds, water vapor, and aerosols up to and including the stratosphere. Aura's chemistry measurements will also follow up on measurements that began with NASA's Upper Atmosphere Research Satellite and continue the record of satellite ozone data collected from the TOMS missions. In this presentation I will describe how scientists are using EOS data to examine the health of the earth's atmosphere, including atmospheric chemistry, aerosol properties, and cloud properties, with a special look at the latest earth observing mission, Aura.

Urban Dynamics: Analyzing Land Use Change in Urban Environments

NASA Technical Reports Server (NTRS)

Acevedo, William; Richards, Lora R.; Buchanan, Janis T.; Wegener, Whitney R.

2000-01-01

In FY99, the Earth Resource Observation System (EROS) staff at Ames continued managing the U.S. Geological Survey's (USGS) Urban Dynamics Research program, which has mapping and analysis activities at five USGS mapping centers. Historic land use reconstruction work continued while activities in geographic analysis and modeling were expanded. Retrospective geographic information system (GIS) development - the spatial reconstruction of a region's urban land-use history - focused on the Detroit River Corridor, California's Central Valley, and the city of Sioux Falls, South Dakota.

Evaluation of remote hydrologic data-acquisition systems, west-central Florida

USGS Publications Warehouse

Turner, J.F.; Woodham, W.M.

1980-01-01

The study provides an evaluation of the hydrologic applications of a land-line and two satellite data-relay systems operated during 1977-78 in the Southwest Florida Water Management District. These systems were tested to evaluate operational and reliability characteristics. Telephone lines were used to relay data in the land-line system, and the Geostationary Operational Environmental Satellite (GOES) and Land satellite (Landsat) were used in the satellite system. The land-line system was tested for 15 months at a streamflow site. Accurate data were obtained 94% of the time during the test period. Data losses were attributed to telephone-line interference, low-battery voltage, and vandalism. The GOES system was tested at a rainfall site for 17 months. During this period, 79% of the transmissions received from the station were relayed by the GOES system to the U.S. Geological Survey computer, resulting in successful processing of 88% of all possible rainfall observations. On the average, seven data transmissions were completed each day. The Landsat system was tested at a rainfall site for about 17 months and for about 8 months at a streamflow site. During these periods of operation, only about 2% of all data observations for the stations were successfully relayed by the Landsat system to the U.S. Geological Survey computer. An average of about three data transmissions was completed each day for each site. (USGS).

Human Planetary Landing System (HPLS) Capability Roadmap NRC Progress Review

NASA Technical Reports Server (NTRS)

Manning, Rob; Schmitt, Harrison H.; Graves, Claude

2005-01-01

Capability Roadmap Team. Capability Description, Scope and Capability Breakdown Structure. Benefits of the HPLS. Roadmap Process and Approach. Current State-of-the-Art, Assumptions and Key Requirements. Top Level HPLS Roadmap. Capability Presentations by Leads. Mission Drivers Requirements. "AEDL" System Engineering. Communication & Navigation Systems. Hypersonic Systems. Super to Subsonic Decelerator Systems. Terminal Descent and Landing Systems. A Priori In-Situ Mars Observations. AEDL Analysis, Test and Validation Infrastructure. Capability Technical Challenges. Capability Connection Points to other Roadmaps/Crosswalks. Summary of Top Level Capability. Forward Work.

Model Meets Data: Challenges and Opportunities to Implement Land Management in Earth System Models

NASA Astrophysics Data System (ADS)

Pongratz, J.; Dolman, A. J.; Don, A.; Erb, K. H.; Fuchs, R.; Herold, M.; Jones, C.; Luyssaert, S.; Kuemmerle, T.; Meyfroidt, P.

2016-12-01

Land-based demand for food and fibre is projected to increase in the future. In light of global sustainability challenges only part of this increase will be met by expansion of land use into relatively untouched regions. Additional demand will have to be fulfilled by intensification and other adjustments in management of land that already is under agricultural and forestry use. Such land management today occurs on about half of the ice-free land surface, as compared to only about one quarter that has undergone a change in land cover. As the number of studies revealing substantial biogeophysical and biogeochemical effects of land management is increasing, moving beyond land cover change towards including land management has become a key focus for Earth system modeling. However, a basis for prioritizing land management activities for implementation in models is lacking. We lay this basis for prioritization in a collaborative project across the disciplines of Earth system modeling, land system science, and Earth observation. We first assess the status and plans of implementing land management in Earth system and dynamic global vegetation models. A clear trend towards higher complexity of land use representation is visible. We then assess five criteria for prioritizing the implementation of land management activities: (1) spatial extent, (2) evidence for substantial effects on the Earth system, (3) process understanding, (4) possibility to link the management activity to existing concepts and structures of models, (5) availability of data required as model input. While the first three criteria have been assessed by an earlier study for ten common management activities, we review strategies for implementation in models and the availability of required datasets. We can thus evaluate the management activities for their performance in terms of importance for the Earth system, possibility of technical implementation in models, and data availability. This synthesis reveals some "low-hanging" fruits for model implementation, but also challenges for the assessment of land management effects by modeling. The identified gaps can guide prioritization within the data community from the Earth system and Earth system modeling perspective.

Model meets data: Challenges and opportunities to implement land management in Earth System Models

NASA Astrophysics Data System (ADS)

Pongratz, Julia; Dolman, Han; Don, Axel; Erb, Karl-Heinz; Fuchs, Richard; Herold, Martin; Jones, Chris; Luyssaert, Sebastiaan; Kuemmerle, Tobias; Meyfroidt, Patrick; Naudts, Kim

2017-04-01

Land-based demand for food and fibre is projected to increase in the future. In light of global sustainability challenges only part of this increase will be met by expansion of land use into relatively untouched regions. Additional demand will have to be fulfilled by intensification and other adjustments in management of land that already is under agricultural and forestry use. Such land management today occurs on about half of the ice-free land surface, as compared to only about one quarter that has undergone a change in land cover. As the number of studies revealing substantial biogeophysical and biogeochemical effects of land management is increasing, moving beyond land cover change towards including land management has become a key focus for Earth system modeling. However, a basis for prioritizing land management activities for implementation in models is lacking. We lay this basis for prioritization in a collaborative project across the disciplines of Earth system modeling, land system science, and Earth observation. We first assess the status and plans of implementing land management in Earth system and dynamic global vegetation models. A clear trend towards higher complexity of land use representation is visible. We then assess five criteria for prioritizing the implementation of land management activities: (1) spatial extent, (2) evidence for substantial effects on the Earth system, (3) process understanding, (4) possibility to link the management activity to existing concepts and structures of models, (5) availability of data required as model input. While the first three criteria have been assessed by an earlier study for ten common management activities, we review strategies for implementation in models and the availability of required datasets. We can thus evaluate the management activities for their performance in terms of importance for the Earth system, possibility of technical implementation in models, and data availability. This synthesis reveals some "low-hanging" fruits for model implementation, but also challenges for the assessment of land management effects by modeling. The identified gaps can guide prioritization within the data community from the Earth system and Earth system modeling perspective.

Inferring Land Surface Model Parameters for the Assimilation of Satellite-Based L-Band Brightness Temperature Observations into a Soil Moisture Analysis System

NASA Technical Reports Server (NTRS)

Reichle, Rolf H.; De Lannoy, Gabrielle J. M.

2012-01-01

The Soil Moisture and Ocean Salinity (SMOS) satellite mission provides global measurements of L-band brightness temperatures at horizontal and vertical polarization and a variety of incidence angles that are sensitive to moisture and temperature conditions in the top few centimeters of the soil. These L-band observations can therefore be assimilated into a land surface model to obtain surface and root zone soil moisture estimates. As part of the observation operator, such an assimilation system requires a radiative transfer model (RTM) that converts geophysical fields (including soil moisture and soil temperature) into modeled L-band brightness temperatures. At the global scale, the RTM parameters and the climatological soil moisture conditions are still poorly known. Using look-up tables from the literature to estimate the RTM parameters usually results in modeled L-band brightness temperatures that are strongly biased against the SMOS observations, with biases varying regionally and seasonally. Such biases must be addressed within the land data assimilation system. In this presentation, the estimation of the RTM parameters is discussed for the NASA GEOS-5 land data assimilation system, which is based on the ensemble Kalman filter (EnKF) and the Catchment land surface model. In the GEOS-5 land data assimilation system, soil moisture and brightness temperature biases are addressed in three stages. First, the global soil properties and soil hydraulic parameters that are used in the Catchment model were revised to minimize the bias in the modeled soil moisture, as verified against available in situ soil moisture measurements. Second, key parameters of the "tau-omega" RTM were calibrated prior to data assimilation using an objective function that minimizes the climatological differences between the modeled L-band brightness temperatures and the corresponding SMOS observations. Calibrated parameters include soil roughness parameters, vegetation structure parameters, and the single scattering albedo. After this climatological calibration, the modeling system can provide L-band brightness temperatures with a global mean absolute bias of less than 10K against SMOS observations, across multiple incidence angles and for horizontal and vertical polarization. Third, seasonal and regional variations in the residual biases are addressed by estimating the vegetation optical depth through state augmentation during the assimilation of the L-band brightness temperatures. This strategy, tested here with SMOS data, is part of the baseline approach for the Level 4 Surface and Root Zone Soil Moisture data product from the planned Soil Moisture Active Passive (SMAP) satellite mission.

Viking site selection and certification

NASA Technical Reports Server (NTRS)

Masursky, H.; Crabill, N. L.

1981-01-01

The landing site selection and certification effort for the Viking mission to Mars is reviewed from the premission phase through the acquisition of data and decisions during mission operations and the immediate postlanding evaluation. The utility and limitations of the orbital television and infrared data and ground based radar observation of candidate and actual landing sites are evaluated. Additional instruments and types of observations which would have been useful include higher resolution cameras, radar altimeters, and terrain hazard avoidance capability in the landing system. Suggestions based on this experience that might be applied to future missions are included.

Enhancing Global Land Surface Hydrology Estimates from the NASA MERRA Reanalysis Using Precipitation Observations and Model Parameter Adjustments

NASA Technical Reports Server (NTRS)

Reichle, Rolf; Koster, Randal; DeLannoy, Gabrielle; Forman, Barton; Liu, Qing; Mahanama, Sarith; Toure, Ally

2011-01-01

The Modern-Era Retrospective analysis for Research and Applications (MERRA) is a state-of-the-art reanalysis that provides. in addition to atmospheric fields. global estimates of soil moisture, latent heat flux. snow. and runoff for J 979-present. This study introduces a supplemental and improved set of land surface hydrological fields ('MERRA-Land') generated by replaying a revised version of the land component of the MERRA system. Specifically. the MERRA-Land estimates benefit from corrections to the precipitation forcing with the Global Precipitation Climatology Project pentad product (version 2.1) and from revised parameters in the rainfall interception model, changes that effectively correct for known limitations in the MERRA land surface meteorological forcings. The skill (defined as the correlation coefficient of the anomaly time series) in land surface hydrological fields from MERRA and MERRA-Land is assessed here against observations and compared to the skill of the state-of-the-art ERA-Interim reanalysis. MERRA-Land and ERA-Interim root zone soil moisture skills (against in situ observations at 85 US stations) are comparable and significantly greater than that of MERRA. Throughout the northern hemisphere, MERRA and MERRA-Land agree reasonably well with in situ snow depth measurements (from 583 stations) and with snow water equivalent from an independent analysis. Runoff skill (against naturalized stream flow observations from 15 basins in the western US) of MERRA and MERRA-Land is typically higher than that of ERA-Interim. With a few exceptions. the MERRA-Land data appear more accurate than the original MERRA estimates and are thus recommended for those interested in using '\\-tERRA output for land surface hydrological studies.

The evaluation of ASOS for the Kennedy Space Center's Shuttle Landing Facility

NASA Technical Reports Server (NTRS)

Yersavich, Ann; Wheeler, Mark; Taylor, Gregory; Schumann, Robin; Manobianco, John

1994-01-01

This report documents the Applied Meteorology Unit's (AMU) evaluation of the effectiveness and utility of the Automated Surface Observing System (ASOS) in terms of spaceflight operations and user requirements. In particular, the evaluation determines which of the Shuttle Landing Facility (SLF) observation requirements can be satisfied by ASOS. This report also includes a summary of ASOS' background, current configuration and specifications, system performance, and the possible concepts of operations for use of ASOS at the SLF. This evaluation stems from a desire by the Air Force to determine if ASOS units could be used to reduce the cost of SLF meteorological observations.

Supporting users through integrated retrieval, processing, and distribution systems at the Land Processes Distributed Active Archive Center

USGS Publications Warehouse

Kalvelage, Thomas A.; Willems, Jennifer

2005-01-01

The US Geological Survey's EROS Data Center (EDC) hosts the Land Processes Distributed Active Archive Center (LP DAAC). The LP DAAC supports NASA's Earth Observing System (EOS), which is a series of polar-orbiting and low inclination satellites for long-term global observations of the land surface, biosphere, solid Earth, atmosphere, and oceans. The EOS Data and Information Systems (EOSDIS) was designed to acquire, archive, manage and distribute Earth observation data to the broadest possible user community.The LP DAAC is one of four DAACs that utilize the EOSDIS Core System (ECS) to manage and archive their data. Since the ECS was originally designed, significant changes have taken place in technology, user expectations, and user requirements. Therefore the LP DAAC has implemented additional systems to meet the evolving needs of scientific users, tailored to an integrated working environment. These systems provide a wide variety of services to improve data access and to enhance data usability through subsampling, reformatting, and reprojection. These systems also support the wide breadth of products that are handled by the LP DAAC.The LP DAAC is the primary archive for the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) data; it is the only facility in the United States that archives, processes, and distributes data from the Advanced Spaceborne Thermal Emission/Reflection Radiometer (ASTER) on NASA's Terra spacecraft; and it is responsible for the archive and distribution of “land products” generated from data acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA's Terra and Aqua satellites.

The Earth Observing System. [instrument investigations for flight on EOS-A satellite

NASA Technical Reports Server (NTRS)

Wilson, Stan; Dozier, Jeff

1991-01-01

The Earth Observing System (EOS), the centerpiece of NASA's Mission to Planet Earth, is to study the interactions of the atmosphere, land, oceans, and living organisms, using the perspective of space to observe the earth as a global environmental system. To better understand the role of clouds in global change, EOS will measure incoming and emitted radiation at the top of the atmosphere. Then, to study characteristics of the atmosphere that influence radiation transfer between the top of the atmosphere and the surface, EOS wil observe clouds, water vapor and cloud water, aerosols, temperature and humidity, and directional effects. To elucidate the role of anthropogenic greenhouse gas and terrestrial and marine plants as a source or sink for carbon, EOS will observe the biological productivity of lands and oceans. EOS will also study surface properties that affect biological productivity at high resolution spatially and spectrally.

Evaluation of the North American Land Data Assimilation System over the Southern Great Plains during the warm season

NASA Astrophysics Data System (ADS)

Robock, A.; Luo, L.; Wood, E. F.; Wen, F.; Mitchell, K. E.; Houser, P. R.; Schaake, J. C.; Nldas Team

2003-04-01

To conduct land data assimilation, validated land surface models are needed. The first step in the North American Land Data Assimilation System (NLDAS) is to evaluate four such state-of-the-art models. These models (VIC, Noah, Mosaic, and Sacramento) have been run for a retrospective period forced by atmospheric observations from the Eta analysis and actual precipitation and downward solar radiation (on a 1/8 degree North American grid) to calculate land hydrology. First we show that the forcing data set agrees very well with local observations and that simulations forced with local observations differ little from those forced with the NLDAS forcing data set. Then we evaluated the simulations using in situ observations over the Southern Great Plains for the periods of May-September of 1998 and 1999 by comparing the model outputs with surface latent, sensible, and ground heat fluxes at 24 Atmospheric Radiation Measurement/Cloud and Radiation Testbed stations and with soil temperature and soil moisture observations at 72 Oklahoma Mesonet stations. The standard NLDAS models do a fairly good job but with differences in the surface energy partition and in soil moisture between models and observations and among models during the summer, while they agree quite well on the soil temperature simulations. To investigate why, we performed a series of experiments accounting for differences between model-specified soil types and vegetation and those observed at the stations, and differences in model treatment of different soil types, vegetation properties, canopy resistance, soil column depth, rooting depth, root density, snow-free albedo, infiltration, aerodynamic resistance, and soil thermal diffusivity. The diagnosis and model enhancements demonstrate how the models can be improved so that they can be used in actual data assimilation mode.

Updating representation of land surface-atmosphere feedbacks in airborne campaign modeling analysis

NASA Astrophysics Data System (ADS)

Huang, M.; Carmichael, G. R.; Crawford, J. H.; Chan, S.; Xu, X.; Fisher, J. A.

2017-12-01

An updated modeling system to support airborne field campaigns is being built at NASA Ames Pleiades, with focus on adjusting the representation of land surface-atmosphere feedbacks. The main updates, referring to previous experiences with ARCTAS-CARB and CalNex in the western US to study air pollution inflows, include: 1) migrating the WRF (Weather Research and Forecasting) coupled land surface model from Noah to improved/more complex models especially Noah-MP and Rapid Update Cycle; 2) enabling the WRF land initialization with suitably spun-up land model output; 3) incorporating satellite land cover, vegetation dynamics, and soil moisture data (i.e., assimilating Soil Moisture Active Passive data using the ensemble Kalman filter approach) into WRF. Examples are given of comparing the model fields with available aircraft observations during spring-summer 2016 field campaigns taken place at the eastern side of continents (KORUS-AQ in South Korea and ACT-America in the eastern US), the air pollution export regions. Under fair weather and stormy conditions, air pollution vertical distributions and column amounts, as well as the impact from land surface, are compared. These help identify challenges and opportunities for LEO/GEO satellite remote sensing and modeling of air quality in the northern hemisphere. Finally, we briefly show applications of this system on simulating Australian conditions, which would explore the needs for further development of the observing system in the southern hemisphere and inform the Clean Air and Urban Landscapes (https://www.nespurban.edu.au) modelers.

In-situ formation compaction monitoring in deep reservoirs by use of fiber optics

NASA Astrophysics Data System (ADS)

Murai, Daisuke; Kunisue, Shoji; Higuchi, Tomoyuki; Kokubo, Tatsuo

2013-04-01

1. Background The Southern Kanto gas field, the largest field of natural gas dissolved in water in Japan, is located primarily under the Chiba Prefecture. In this field 8 companies produce 460*10^6m3/y of natural gas. In addition, the concentration of the iodine in the brine is almost 2000 times that in seawater and the iodine as well as natural gas is collected from the brine. Iodine is industrially useful and essential for the human body. About 30% of world production is produced in this area in recent years. On the other hand, the land subsidence has become the big problem since 1965 and more than 10cm/mm of land subsidence was observed by leveling in 1972. The natural gas and iodine producers in this area have made a land subsidence prevention agreement with the local government and made effort to prevent and control land subsidence. Although their pumping brine for the gas and the iodine production is inferred to be the main cause of land subsidence from that time, the ratio of the formation compaction caused by pumping brine in the total land subsidence hasn't been well known. Therefore, the measurement of the actual formation compaction has become an important technological issue for the companies and they jointly have developed a new monitoring system for the formation compaction. 2. Contents (1) By using fiber optics technology, we have developed a world's first monitoring system which measures each of the in-situ formation compactions continuously without running tools into the well. (2) In order to check a reliability of this system and the problems when construction, we carried out the preliminary test. We installed the prototype system in the shallow observation well with a depth of 80 m and measured the actual formation compaction. The water well was drilled at the 10m away from the observation well and the formation was artificially compacted by pumping groundwater from it. (3) We installed the monitoring system in the deep observation well with a depth of about 800m, and have been measuring the formation compaction of the natural gas reservoir now. 3. Conclusions (1) We succeeded in installing the monitoring system into the observation well and measure the each of 6 formation compactions in the gas reservoir. (2) As a result of the preliminary test we confirmed that the monitoring system run without big problems even in the field. The formation compacted/expanded with the groundwater level fallen/risen according to the pump rate. (3) We improved the monitoring system based on the knowledge acquired by the demonstration test and installed it into the deep observation well. We are carrying out the long term observation now. 4. Acknowledgements This research was carried out by the support for application of new technologies and technical studies program which Japan Oil, Gas and Metals National Corporation (JOGMEC) undertook.

Failed landings after laying hen flight in a commercial aviary over two flock cycles.

PubMed

Campbell, D L M; Goodwin, S L; Makagon, M M; Swanson, J C; Siegford, J M

2016-01-01

Many egg producers are adopting alternative housing systems such as aviaries that provide hens a tiered cage and a litter-covered open floor area. This larger, more complex environment permits expression of behaviors not seen in space-limited cages, such as flight. Flight is an exercise important for strengthening bones; but domestic hens might display imperfect flight landings due to poor flight control. To assess the potential implications of open space, we evaluated the landing success of Lohmann white laying hens in a commercial aviary. Video recordings of hens were taken from 4 aviary sections at peak lay, mid lay and end lay across two flock cycles. Observations were made in each focal section of all flights throughout the day noting flight origin and landing location (outer perch or litter) and landing success or failure. In Flock 1, 9.1% of all flights failed and 21% failed in Flock 2. The number of flights decreased across the laying cycle for both flocks. Proportionally more failed landings were observed in the double row sections in Flock 2. Collisions with other hens were more common than slipping on the ground or colliding with aviary structures across sections and flocks. More hens slipped on the ground and collided with physical structures at peak lay for Flock 2 than at other time points. More collisions with other hens were seen at mid and end lay than at peak lay for Flock 2. Landings ending on perches failed more often than landings on litter. These results indicate potential for flight-related hen injuries in aviary systems resulting from failed landings, which may have implications for hen welfare and optimal system design and management.

Assimilation of Freeze - Thaw Observations into the NASA Catchment Land Surface Model

NASA Technical Reports Server (NTRS)

Farhadi, Leila; Reichle, Rolf H.; DeLannoy, Gabrielle J. M.; Kimball, John S.

2014-01-01

The land surface freeze-thaw (F-T) state plays a key role in the hydrological and carbon cycles and thus affects water and energy exchanges and vegetation productivity at the land surface. In this study, we developed an F-T assimilation algorithm for the NASA Goddard Earth Observing System, version 5 (GEOS-5) modeling and assimilation framework. The algorithm includes a newly developed observation operator that diagnoses the landscape F-T state in the GEOS-5 Catchment land surface model. The F-T analysis is a rule-based approach that adjusts Catchment model state variables in response to binary F-T observations, while also considering forecast and observation errors. A regional observing system simulation experiment was conducted using synthetically generated F-T observations. The assimilation of perfect (error-free) F-T observations reduced the root-mean-square errors (RMSE) of surface temperature and soil temperature by 0.206 C and 0.061 C, respectively, when compared to model estimates (equivalent to a relative RMSE reduction of 6.7 percent and 3.1 percent, respectively). For a maximum classification error (CEmax) of 10 percent in the synthetic F-T observations, the F-T assimilation reduced the RMSE of surface temperature and soil temperature by 0.178 C and 0.036 C, respectively. For CEmax=20 percent, the F-T assimilation still reduces the RMSE of model surface temperature estimates by 0.149 C but yields no improvement over the model soil temperature estimates. The F-T assimilation scheme is being developed to exploit planned operational F-T products from the NASA Soil Moisture Active Passive (SMAP) mission.

Video Guidance, Landing, and Imaging system (VGLIS) for space missions

NASA Technical Reports Server (NTRS)

Schappell, R. T.; Knickerbocker, R. L.; Tietz, J. C.; Grant, C.; Flemming, J. C.

1975-01-01

The feasibility of an autonomous video guidance system that is capable of observing a planetary surface during terminal descent and selecting the most acceptable landing site was demonstrated. The system was breadboarded and "flown" on a physical simulator consisting of a control panel and monitor, a dynamic simulator, and a PDP-9 computer. The breadboard VGLIS consisted of an image dissector camera and the appropriate processing logic. Results are reported.

78 FR 55063 - U.S. Integrated Ocean Observing System (IOOS®) Advisory Committee

Federal Register 2010, 2011, 2012, 2013, 2014

2013-09-09

... Observation System Act, part of the Omnibus Public Land Management Act of 2009 (Public Law 111-11). The... Committee for review and advice. The Committee will provide advice on: (a) administration, operation, management, and maintenance of the System; (b) expansion and periodic modernization and upgrade of technology...

Constraining a land-surface model with multiple observations by application of the MPI-Carbon Cycle Data Assimilation System V1.0

NASA Astrophysics Data System (ADS)

Schürmann, Gregor J.; Kaminski, Thomas; Köstler, Christoph; Carvalhais, Nuno; Voßbeck, Michael; Kattge, Jens; Giering, Ralf; Rödenbeck, Christian; Heimann, Martin; Zaehle, Sönke

2016-09-01

We describe the Max Planck Institute Carbon Cycle Data Assimilation System (MPI-CCDAS) built around the tangent-linear version of the JSBACH land-surface scheme, which is part of the MPI-Earth System Model v1. The simulated phenology and net land carbon balance were constrained by globally distributed observations of the fraction of absorbed photosynthetically active radiation (FAPAR, using the TIP-FAPAR product) and atmospheric CO2 at a global set of monitoring stations for the years 2005 to 2009. When constrained by FAPAR observations alone, the system successfully, and computationally efficiently, improved simulated growing-season average FAPAR, as well as its seasonality in the northern extra-tropics. When constrained by atmospheric CO2 observations alone, global net and gross carbon fluxes were improved, despite a tendency of the system to underestimate tropical productivity. Assimilating both data streams jointly allowed the MPI-CCDAS to match both observations (TIP-FAPAR and atmospheric CO2) equally well as the single data stream assimilation cases, thereby increasing the overall appropriateness of the simulated biosphere dynamics and underlying parameter values. Our study thus demonstrates the value of multiple-data-stream assimilation for the simulation of terrestrial biosphere dynamics. It further highlights the potential role of remote sensing data, here the TIP-FAPAR product, in stabilising the strongly underdetermined atmospheric inversion problem posed by atmospheric transport and CO2 observations alone. Notwithstanding these advances, the constraint of the observations on regional gross and net CO2 flux patterns on the MPI-CCDAS is limited through the coarse-scale parametrisation of the biosphere model. We expect improvement through a refined initialisation strategy and inclusion of further biosphere observations as constraints.

The relation between land use and subsidence in the Vietnamese Mekong delta.

PubMed

Minderhoud, P S J; Coumou, L; Erban, L E; Middelkoop, H; Stouthamer, E; Addink, E A

2018-09-01

The Vietnamese Mekong delta is subsiding due to a combination of natural and human-induced causes. Over the past several decades, large-scale anthropogenic land-use changes have taken place as a result of increased agricultural production, population growth and urbanization in the delta. Land-use changes can alter the hydrological system or increase loading of the delta surface, amplifying natural subsidence processes or creating new anthropogenic subsidence. The relationships between land use histories and current rates of land subsidence have so far not been studied in the Mekong delta. We quantified InSAR-derived subsidence rates for the various land-use classes and past land-use changes using a new, optical remote sensing-based, 20-year time series of land use. Lowest mean subsidence rates were found for undeveloped land-use classes, like marshland and wetland forest (~6-7mmyr -1 ), and highest rates for areas with mixed-crop agriculture and cities (~18-20mmyr -1 ). We assessed the relationship strength between current land use, land-use history and subsidence by predicting subsidence rates during the measurement period solely based on land-use history. After initial training of all land-use sequences with InSAR-derived subsidence rates, the land-use-based approach predicted 65-92% of the spatially varying subsidence rates within the measurement error range of the InSAR observations (RMSE=5.8mm). As a result, the spatial patterns visible in the observed subsidence can largely be explained by land use. We discuss in detail the dominant land-use change pathways and their indirect, causal relationships with subsidence. Our spatially explicit evaluation of these pathways provides valuable insights for policymakers concerned with land-use planning in both subsiding and currently stable areas of the Mekong delta and similar systems. Copyright © 2018 Elsevier B.V. All rights reserved.

Assessment of Land Degradation and Greening in Ken River Basin of Central India

NASA Astrophysics Data System (ADS)

Pandey, Ashish; Palmate, Santosh S.

2017-04-01

Natural systems have significant impact of land degradation on biodiversity loss, food and water insecurity. To achieve the sustainable development goals, advances in remote sensing and geographical information systems (GIS) are progressively utilized to combat climate change, land degradation and poverty issues of developing country. The Ken River Basin (KRB) has dominating land cover pattern of agriculture and forest area. Nowadays, this pattern is affected due to climate change and anthropogenic activity like deforestation. In this study, land degradation and greening status of KRB of Central India during the years 2001 to 2013 have been assessed using MODIS land cover (MCD12Q1) data sets. International Geosphere Biosphere Programme (IGBP) land cover data has been extracted from the MCD12Q1 data product. Multiple rasters of MODIS landcover were analyzed and compared for assigning unique combination of land cover dynamics employing ArcGIS software. Result reveals that 14.38% natural vegetation was degraded, and crop land and woody savannas were greened by 9.68% to 6.94% respectively. Natural vegetation degradation have been observed in the upper KRB area, and resulted to increase in crop land (3418.87 km2) and woody savannas (1242.23 km2) area. Due to transition of 1043.6 km2 area of deciduous broadleaf forest to woody savannas greening was also observed. Moreover, both crop land and woody savannas showed inter-transitions of 669.31 km2 into crop land to woody savannas, and 874.09 km2 into woody savannas to crop land. The present analysis reveals that natural vegetation has more land conversions into woody savannas and crop land in the KRB area. Further, Spatial change analysis shows that land degradation and greening has occurred mostly in the upper part of the KRB. The study reveals that the land transition information can be useful for proper planning and management of natural resources.

A Generalized Deforestation and Land-Use Change Scenario Generator for Use in Climate Modelling Studies

PubMed Central

Tompkins, Adrian Mark; Caporaso, Luca; Biondi, Riccardo; Bell, Jean Pierre

2015-01-01

A new deforestation and land-use change scenario generator model (FOREST-SAGE) is presented that is designed to interface directly with dynamic vegetation models used in latest generation earth system models. The model requires a regional-scale scenario for aggregate land-use change that may be time-dependent, provided by observational studies or by regional land-use change/economic models for future projections. These land-use categories of the observations/economic model are first translated into equivalent plant function types used by the particular vegetation model, and then FOREST-SAGE disaggregates the regional-scale scenario to the local grid-scale of the earth system model using a set of risk-rules based on factors such as proximity to transport networks, distance weighted population density, forest fragmentation and presence of protected areas and logging concessions. These rules presently focus on the conversion of forest to agriculture and pasture use, but could be generalized to other land use change conversions. After introducing the model, an evaluation of its performance is shown for the land-cover changes that have occurred in the Central African Basin from 2001–2010 using retrievals from MODerate Resolution Imaging Spectroradiometer Vegetation Continuous Field data. The model is able to broadly reproduce the spatial patterns of forest cover change observed by MODIS, and the use of the local-scale risk factors enables FOREST-SAGE to improve land use change patterns considerably relative to benchmark scenarios used in the latest Coupled Model Intercomparison Project integrations. The uncertainty to the various risk factors is investigated using an ensemble of investigations, and it is shown that the model is sensitive to the population density, forest fragmentation and reforestation factors specified. PMID:26394392

The Impact of Land Use/Land Cover Changes on Land Degradation Dynamics: A Mediterranean Case Study

NASA Astrophysics Data System (ADS)

Bajocco, S.; De Angelis, A.; Perini, L.; Ferrara, A.; Salvati, L.

2012-05-01

In the last decades, due to climate changes, soil deterioration, and Land Use/Land Cover Changes (LULCCs), land degradation risk has become one of the most important ecological issues at the global level. Land degradation involves two interlocking systems: the natural ecosystem and the socio-economic system. The complexity of land degradation processes should be addressed using a multidisciplinary approach. Therefore, the aim of this work is to assess diachronically land degradation dynamics under changing land covers. This paper analyzes LULCCs and the parallel increase in the level of land sensitivity to degradation along the coastal belt of Sardinia (Italy), a typical Mediterranean region where human pressure affects the landscape characteristics through fires, intensive agricultural practices, land abandonment, urban sprawl, and tourism concentration. Results reveal that two factors mainly affect the level of land sensitivity to degradation in the study area: (i) land abandonment and (ii) unsustainable use of rural and peri-urban areas. Taken together, these factors represent the primary cause of the LULCCs observed in coastal Sardinia. By linking the structural features of the Mediterranean landscape with its functional land degradation dynamics over time, these results contribute to orienting policies for sustainable land management in Mediterranean coastal areas.

The impact of land use/land cover changes on land degradation dynamics: a Mediterranean case study.

PubMed

Bajocco, S; De Angelis, A; Perini, L; Ferrara, A; Salvati, L

2012-05-01

In the last decades, due to climate changes, soil deterioration, and Land Use/Land Cover Changes (LULCCs), land degradation risk has become one of the most important ecological issues at the global level. Land degradation involves two interlocking systems: the natural ecosystem and the socio-economic system. The complexity of land degradation processes should be addressed using a multidisciplinary approach. Therefore, the aim of this work is to assess diachronically land degradation dynamics under changing land covers. This paper analyzes LULCCs and the parallel increase in the level of land sensitivity to degradation along the coastal belt of Sardinia (Italy), a typical Mediterranean region where human pressure affects the landscape characteristics through fires, intensive agricultural practices, land abandonment, urban sprawl, and tourism concentration. Results reveal that two factors mainly affect the level of land sensitivity to degradation in the study area: (i) land abandonment and (ii) unsustainable use of rural and peri-urban areas. Taken together, these factors represent the primary cause of the LULCCs observed in coastal Sardinia. By linking the structural features of the Mediterranean landscape with its functional land degradation dynamics over time, these results contribute to orienting policies for sustainable land management in Mediterranean coastal areas.

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.

Reconciling Land-Ocean Moisture Transport Variability in Reanalyses with P-ET in Observationally-Driven Land Surface Models

NASA Technical Reports Server (NTRS)

Robertson, Franklin R.; Bosilovich, Michael G.; Roberts, Jason B.

2016-01-01

Vertically integrated atmospheric moisture transport from ocean to land [vertically integrated atmospheric moisture flux convergence (VMFC)] is a dynamic component of the global climate system but remains problematic in atmospheric reanalyses, with current estimates having significant multidecadal global trends differing even in sign. Continual evolution of the global observing system, particularly stepwise improvements in satellite observations, has introduced discrete changes in the ability of data assimilation to correct systematic model biases, manifesting as nonphysical variability. Land surface models (LSMs) forced with observed precipitation P and near-surface meteorology and radiation provide estimates of evapotranspiration (ET). Since variability of atmospheric moisture storage is small on interannual and longer time scales, VMFC equals P minus ET is a good approximation and LSMs can provide an alternative estimate. However, heterogeneous density of rain gauge coverage, especially the sparse coverage over tropical continents, remains a serious concern. Rotated principal component analysis (RPCA) with prefiltering of VMFC to isolate the artificial variability is used to investigate artifacts in five reanalysis systems. This procedure, although ad hoc, enables useful VMFC corrections over global land. The P minus ET estimates from seven different LSMs are evaluated and subsequently used to confirm the efficacy of the RPCA-based adjustments. Global VMFC trends over the period 1979-2012 ranging from 0.07 to minus 0.03 millimeters per day per decade are reduced by the adjustments to 0.016 millimeters per day per decade, much closer to the LSM P minus ET estimate (0.007 millimeters per day per decade). Neither is significant at the 90 percent level. ENSO (El Nino-Southern Oscillation)-related modulation of VMFC and P minus ET remains the largest global interannual signal, with mean LSM and adjusted reanalysis time series correlating at 0.86.

The Beagle 2 Stereo Camera System: Scientific Objectives and Design Characteristics

NASA Astrophysics Data System (ADS)

Griffiths, A.; Coates, A.; Josset, J.; Paar, G.; Sims, M.

2003-04-01

The Stereo Camera System (SCS) will provide wide-angle (48 degree) multi-spectral stereo imaging of the Beagle 2 landing site in Isidis Planitia with an angular resolution of 0.75 milliradians. Based on the SpaceX Modular Micro-Imager, the SCS is composed of twin cameras (with 1024 by 1024 pixel frame transfer CCD) and twin filter wheel units (with a combined total of 24 filters). The primary mission objective is to construct a digital elevation model of the area in reach of the lander’s robot arm. The SCS specifications and following baseline studies are described: Panoramic RGB colour imaging of the landing site and panoramic multi-spectral imaging at 12 distinct wavelengths to study the mineralogy of landing site. Solar observations to measure water vapour absorption and the atmospheric dust optical density. Also envisaged are multi-spectral observations of Phobos &Deimos (observations of the moons relative to background stars will be used to determine the lander’s location and orientation relative to the Martian surface), monitoring of the landing site to detect temporal changes, observation of the actions and effects of the other PAW experiments (including rock texture studies with a close-up-lens) and collaborative observations with the Mars Express orbiter instrument teams. Due to be launched in May of this year, the total system mass is 360 g, the required volume envelope is 747 cm^3 and the average power consumption is 1.8 W. A 10Mbit/s RS422 bus connects each camera to the lander common electronics.

Evaluation of the North American Land Data Assimilation System over the southern Great Plains during the warm season

NASA Astrophysics Data System (ADS)

Robock, Alan; Luo, Lifeng; Wood, Eric F.; Wen, Fenghua; Mitchell, Kenneth E.; Houser, Paul R.; Schaake, John C.; Lohmann, Dag; Cosgrove, Brian; Sheffield, Justin; Duan, Qingyun; Higgins, R. Wayne; Pinker, Rachel T.; Tarpley, J. Dan; Basara, Jeffery B.; Crawford, Kenneth C.

2003-11-01

North American Land Data Assimilation System (NLDAS) land surface models have been run for a retrospective period forced by atmospheric observations from the Eta analysis and actual precipitation and downward solar radiation to calculate land hydrology. We evaluated these simulations using in situ observations over the southern Great Plains for the periods of May-September of 1998 and 1999 by comparing the model outputs with surface latent, sensible, and ground heat fluxes at 24 Atmospheric Radiation Measurement/Cloud and Radiation Testbed stations and with soil temperature and soil moisture observations at 72 Oklahoma Mesonet stations. The standard NLDAS models do a fairly good job but with differences in the surface energy partition and in soil moisture between models and observations and among models during the summer, while they agree quite well on the soil temperature simulations. To investigate why, we performed a series of experiments accounting for differences between model-specified soil types and vegetation and those observed at the stations, and differences in model treatment of different soil types, vegetation properties, canopy resistance, soil column depth, rooting depth, root density, snow-free albedo, infiltration, aerodynamic resistance, and soil thermal diffusivity. The diagnosis and model enhancements demonstrate how the models can be improved so that they can be used in actual data assimilation mode.

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.

Towards monitoring land-cover and land-use changes at a global scale: the global land survey 2005

USGS Publications Warehouse

Gutman, G.; Byrnes, Raymond A.; Masek, J.; Covington, S.; Justice, C.; Franks, S.; Headley, Rachel

2008-01-01

Land cover is a critical component of the Earth system, infl uencing land-atmosphere interactions, greenhouse gas fl uxes, ecosystem health, and availability of food, fi ber, and energy for human populations. The recent Integrated Global Observations of Land (IGOL) report calls for the generation of maps documenting global land cover at resolutions between 10m and 30m at least every fi ve years (Townshend et al., in press). Moreover, despite 35 years of Landsat observations, there has not been a unifi ed global analysis of land-cover trends nor has there been a global assessment of land-cover change at Landsat-like resolution. Since the 1990s, the National Aeronautics and Space Administration (NASA) and the U.S. Geological Survey (USGS) have supported development of data sets based on global Landsat observations (Tucker et al., 2004). These land survey data sets, usually referred to as GeoCover ™, provide global, orthorectifi ed, typically cloud-free Landsat imagery centered on the years 1975, 1990, and 2000, with a preference for leaf-on conditions. Collectively, these data sets provided a consistent set of observations to assess land-cover changes at a decadal scale. These data are freely available via the Internet from the USGS Center for Earth Resources Observation and Science (EROS) (see http://earthexplorer.usgs.gov or http://glovis.usgs.gov). This has resulted in unprecedented downloads of data, which are widely used in scientifi c studies of land-cover change (e.g., Boone et al., 2007; Harris et al., 2005; Hilbert, 2006; Huang et al. 2007; Jantz et al., 2005, Kim et al., 2007; Leimgruber, 2005; Masek et al., 2006). NASA and USGS are continuing to support land-cover change research through the development of GLS2005 - an additional global Landsat assessment circa 20051 . Going beyond the earlier initiatives, this data set will establish a baseline for monitoring changes on a 5-year interval and will pave the way toward continuous global land-cover monitoring at Landsat-like resolution in the next decade.

Assimilation of SMOS Retrieved Soil Moisture into the Land Information System

NASA Technical Reports Server (NTRS)

Blankenship, Clay; Case, Jonathan; Zavodsky, Bradley; Jedlovec, Gary

2014-01-01

Soil moisture retrievals from the Soil Moisture and Ocean Salinity (SMOS) instrument are assimilated into the Noah land surface model (LSM) within the NASA Land Information System (LIS). Before assimilation, SMOS retrievals are bias-corrected to match the model climatological distribution using a Cumulative Distribution Function (CDF) matching approach. Data assimilation is done via the Ensemble Kalman Filter. The goal is to improve the representation of soil moisture within the LSM, and ultimately to improve numerical weather forecasts through better land surface initialization. We present a case study showing a large area of irrigation in the lower Mississippi River Valley, in an area with extensive rice agriculture. High soil moisture value in this region are observed by SMOS, but not captured in the forcing data. After assimilation, the model fields reflect the observed geographic patterns of soil moisture. Plans for a modeling experiment and operational use of the data are given. This work helps prepare for the assimilation of Soil Moisture Active/Passive (SMAP) retrievals in the near future.

Integration of Landsat-based disturbance maps in the Landscape Change Monitoring System (LCMS)

NASA Astrophysics Data System (ADS)

Healey, S. P.; Cohen, W. B.; Eidenshink, J. C.; Hernandez, A. J.; Huang, C.; Kennedy, R. E.; Moisen, G. G.; Schroeder, T. A.; Stehman, S.; Steinwand, D.; Vogelmann, J. E.; Woodcock, C.; Yang, L.; Yang, Z.; Zhu, Z.

2013-12-01

Land cover change can have a profound effect upon an area's natural resources and its role in biogeochemical and hydrological cycles. Many land cover changes processes are sensitive to climate, including: fire; storm damage, and insect activity. Monitoring of both past and ongoing land cover change is critical, particularly as we try to understand the impact of a changing climate on the natural systems we manage. The Landsat series of satellites, which initially launched in 1972, has allowed land observation at spatial and spectral resolutions appropriate for identification of many types of land cover change. Over the years, and particularly since the opening of the Landsat archive in 2008, many approaches have been developed to meet individual monitoring needs. Algorithms vary by the cover type targeted, the rate of change sought, and the period between observations. The Landscape Change Monitoring System (LCMS) is envisioned as a sustained, inter-agency monitoring program that brings together and operationally provides the best available land cover change maps over the United States. Expanding upon the successful USGS/Forest Service Monitoring Trends in Burn Severity project, LCMS is designed to serve a variety of research and management communities. The LCMS Science Team is currently assessing the relative strengths of a variety of leading change detection approaches, primarily emphasizing Landsat observations. Using standardized image pre-processing methods, maps produced by these algorithms have been compared at intensive validation sites across the country. Additionally, LCMS has taken steps toward a data-mining framework, in which ensembles of algorithm outputs are used with non-parametric models to create integrated predictions of change across a variety of scenarios and change dynamics. We present initial findings from the LCMS Science Team, including validation results from individual algorithms and assessment of initial 'integrated' products from the data-mining framework. It is anticipated that these results will directly impact land change information that will in the future be routinely available across the country through LCMS. With a baseline observation period of more than 40 years and a national scope, this data should shed light upon how trends in disturbance may be linked to climatic changes.

The World Atlas of Desertification assessment concept for conscious land use solutions

NASA Astrophysics Data System (ADS)

Cherlet, Michael; Ivits, Eva; Kutnjak, Hrvoje; Smid, Marek; Sommer, Stefan; Zucca, Claudio

2015-04-01

Land degradation and desertification are complex phenomena that result in environmental damage, economic inefficiency and social inequity and are reflected by a reducing productive capacity of the land and soil. Research indicated that they are driven by a multiple but a limited number of causal aspects that unbalance the capacity of the environment system to sustainably produce ecosystem services and economic value. Competition for land, driven by societal needs or economic opportunities, adds further stress on the land resources. To address these complex global challenges, a monitoring and assessment system offering up-to-date information on the status and trends of land degradation and their causes and effects is needed to provide science-based routes for possible land use solutions. The assessment concept that has been outlined for the compilation of the new World Atlas of Desertification (WAD) confronts this complexity by converging evidence of stress on the land system caused by various issues. These issues relate to sets of dynamics of the human-environment system and include changing agricultural or pastoral land use and management practices, changing population and societal aspects, changing aridity and drought. The WAD describes the issues, spatially documents their change, whenever data is available, highlights the importance of the issues in relation to land degradation processes and illustrates the integrated assessment concepts. The first step is the preparation of solid global data layers that are related to, or express aspects that can be related to, land-system productivity dynamics and status. These can be used for identifying and evaluating the interaction of spatial variables with the land-system productivity dynamics. Initial analysis of the land productivity dynamics within stratified land cover/use areas, such as the global croplands, show substantial differences in the extension, geographic location and possible related causes of potentially critical areas. The stratified integration of global data layers does not produce the 'mythical map of global land degradation' but allows locating areas where stress on the land system is observed that can be related to manifest causal issues. Preventing judgement on the complex status of 'land degradation' the WAD opens the way to a positive approach to deal with the problem, providing also helpful evidence for stakeholders to design more conscious solutions for land use.

Assessment and Enhancement of MERRA Land Surface Hydrology Estimates

NASA Technical Reports Server (NTRS)

Reichle, Rolf H.; Koster, Randal D.; deLannoy, Gabrielle J. M.; Forman, Barton A.; Liu, Qing; Mahanama, Sarith P. P.; Toure, Ally

2012-01-01

The Modern-Era Retrospective analysis for Research and Applications (MERRA) is a state-ofthe-art reanalysis that provides, in addition to atmospheric fields, global estimates of soil moisture, latent heat flux, snow, and runoff for 1979-present. This study introduces a supplemental and improved set of land surface hydrological fields ("MERRA-Land") generated by re-running a revised version of the land component of the MERRA system. Specifically, the MERRA-Land estimates benefit from corrections to the precipitation forcing with the Global Precipitation Climatology Project pentad product (version 2.1) and from revised parameter values in the rainfall interception model, changes that effectively correct for known limitations in the MERRA surface meteorological forcings. The skill (defined as the correlation coefficient of the anomaly time series) in land surface hydrological fields from MERRA and MERRA-Land is assessed here against observations and compared to the skill of the state-of-the-art ERA-Interim (ERA-I) reanalysis. MERRA-Land and ERA-I root zone soil moisture skills (against in situ observations at 85 US stations) are comparable and significantly greater than that of MERRA. Throughout the northern hemisphere, MERRA and MERRA-Land agree reasonably well with in situ snow depth measurements (from 583 stations) and with snow water equivalent from an independent analysis. Runoff skill (against naturalized stream flow observations from 18 US basins) of MERRA and MERRA-Land is typically higher than that of ERA-I. With a few exceptions, the MERRA-Land data appear more accurate than the original MERRA estimates and are thus recommended for those interested in using MERRA output for land surface hydrological studies.

Treatment of systematic errors in land data assimilation systems

NASA Astrophysics Data System (ADS)

Crow, W. T.; Yilmaz, M.

2012-12-01

Data assimilation systems are generally designed to minimize the influence of random error on the estimation of system states. Yet, experience with land data assimilation systems has also revealed the presence of large systematic differences between model-derived and remotely-sensed estimates of land surface states. Such differences are commonly resolved prior to data assimilation through implementation of a pre-processing rescaling step whereby observations are scaled (or non-linearly transformed) to somehow "match" comparable predictions made by an assimilation model. While the rationale for removing systematic differences in means (i.e., bias) between models and observations is well-established, relatively little theoretical guidance is currently available to determine the appropriate treatment of higher-order moments during rescaling. This talk presents a simple analytical argument to define an optimal linear-rescaling strategy for observations prior to their assimilation into a land surface model. While a technique based on triple collocation theory is shown to replicate this optimal strategy, commonly-applied rescaling techniques (e.g., so called "least-squares regression" and "variance matching" approaches) are shown to represent only sub-optimal approximations to it. Since the triple collocation approach is likely infeasible in many real-world circumstances, general advice for deciding between various feasible (yet sub-optimal) rescaling approaches will be presented with an emphasis of the implications of this work for the case of directly assimilating satellite radiances. While the bulk of the analysis will deal with linear rescaling techniques, its extension to nonlinear cases will also be discussed.

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.

Impact of Optimized land Surface Parameters on the Land-Atmosphere Coupling in WRF Simulations of Dry and Wet Extremes

NASA Technical Reports Server (NTRS)

Kumar, Sujay; Santanello, Joseph; Peters-Lidard, Christa; Harrison, Ken

2011-01-01

Land-atmosphere (L-A) interactions play a critical role in determining the diurnal evolution of both planetary boundary layer (PBL) and land surface temperature and moisture budgets, as well as controlling feedbacks with clouds and precipitation that lead to the persistence of dry and wet regimes. Recent efforts to quantify the strength of L-A coupling in prediction models have produced diagnostics that integrate across both the land and PBL components of the system. In this study, we examine the impact of improved specification of land surface states, anomalies, and fluxes on coupled WRF forecasts during the summers of extreme dry (2006) and wet (2007) conditions in the U.S. Southern Great Plains. The improved land initialization and surface flux parameterizations are obtained through the use of a new optimization and uncertainty module in NASA's Land Information System (LIS-OPT), whereby parameter sets are calibrated in the Noah land surface model and classified according to the land cover and soil type mapping of the observations and the full domain. The impact of the calibrated parameters on the a) spin up of land surface states used as initial conditions, and b) heat and moisture fluxes of the coupled (LIS-WRF) simulations are then assessed in terms of ambient weather, PBL budgets, and precipitation along with L-A coupling diagnostics. In addition, the sensitivity of this approach to the period of calibration (dry, wet, normal) is investigated. Finally, tradeoffs of computational tractability and scientific validity (e.g.,. relating to the representation of the spatial dependence of parameters) and the feasibility of calibrating to multiple observational datasets are also discussed.

Nonlinear automatic landing control of unmanned aerial vehicles on moving platforms via a 3D laser radar

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

Hervas, Jaime Rubio; Tang, Hui; Reyhanoglu, Mahmut

2014-12-10

This paper presents a motion tracking and control system for automatically landing Unmanned Aerial Vehicles (UAVs) on an oscillating platform using Laser Radar (LADAR) observations. The system itself is assumed to be mounted on a ship deck. A full nonlinear mathematical model is first introduced for the UAV. The ship motion is characterized by a Fourier transform based method which includes a realistic characterization of the sea waves. LADAR observation models are introduced and an algorithm to process those observations for yielding the relative state between the vessel and the UAV is presented, from which the UAV's state relative tomore » an inertial frame can be obtained and used for feedback purposes. A sliding mode control algorithm is derived for tracking a landing trajectory defined by a set of desired waypoints. An extended Kalman filter (EKF) is proposed to account for process and observation noises in the design of a state estimator. The effectiveness of the control algorithm is illustrated through a simulation example.« less

The Utility of the Real-Time NASA Land Information System Data for Drought Monitoring Applications

NASA Technical Reports Server (NTRS)

White, Kristopher D.; Case, Jonathan L.

2013-01-01

Measurements of soil moisture are a crucial component for the proper monitoring of drought conditions. The large spatial variability of soil moisture complicates the problem. Unfortunately, in situ soil moisture observing networks typically consist of sparse point observations, and conventional numerical model analyses of soil moisture used to diagnose drought are of coarse spatial resolution. Decision support systems such as the U.S. Drought Monitor contain drought impact resolution on sub-county scales, which may not be supported by the existing soil moisture networks or analyses. The NASA Land Information System, which is run with 3 km grid spacing over the eastern United States, has demonstrated utility for monitoring soil moisture. Some of the more useful output fields from the Land Information System are volumetric soil moisture in the 0-10 cm and 40-100 cm layers, column-integrated relative soil moisture, and the real-time green vegetation fraction derived from MODIS (Moderate Resolution Imaging Spectroradiometer) swath data that are run within the Land Information System in place of the monthly climatological vegetation fraction. While these and other variables have primarily been used in local weather models and other operational forecasting applications at National Weather Service offices, the use of the Land Information System for drought monitoring has demonstrated utility for feedback to the Drought Monitor. Output from the Land Information System is currently being used at NWS Huntsville to assess soil moisture, and to provide input to the Drought Monitor. Since feedback to the Drought Monitor takes place on a weekly basis, weekly difference plots of column-integrated relative soil moisture are being produced by the NASA Short-term Prediction Research and Transition Center and analyzed to facilitate the process. In addition to the Drought Monitor, these data are used to assess drought conditions for monthly feedback to the Alabama Drought Monitoring and Impact Group and the Tennessee Drought Task Force, which are comprised of federal, state, and local agencies and other water resources professionals.

MODIS Land Data Products: Generation, Quality Assurance and Validation

NASA Technical Reports Server (NTRS)

Masuoka, Edward; Wolfe, Robert; Morisette, Jeffery; Sinno, Scott; Teague, Michael; Saleous, Nazmi; Devadiga, Sadashiva; Justice, Christopher; Nickeson, Jaime

2008-01-01

The Moderate Resolution Imaging Spectrometer (MODIS) on-board NASA's Earth Observing System (EOS) Terra and Aqua Satellites are key instruments for providing data on global land, atmosphere, and ocean dynamics. Derived MODIS land, atmosphere and ocean products are central to NASA's mission to monitor and understand the Earth system. NASA has developed and generated on a systematic basis a suite of MODIS products starting with the first Terra MODIS data sensed February 22, 2000 and continuing with the first MODIS-Aqua data sensed July 2, 2002. The MODIS Land products are divided into three product suites: radiation budget products, ecosystem products, and land cover characterization products. The production and distribution of the MODIS Land products are described, from initial software delivery by the MODIS Land Science Team, to operational product generation and quality assurance, delivery to EOS archival and distribution centers, and product accuracy assessment and validation. Progress and lessons learned since the first MODIS data were in early 2000 are described.

An Earth Observation Land Data Assimilation System for Data from Multiple Wavelength Domains: Water and Energy Balance Components

NASA Astrophysics Data System (ADS)

Quaife, T. L.; Davenport, I. J.; Lines, E.; Styles, J.; Lewis, P.; Gurney, R. J.

2012-12-01

Satellite observations offer a spatially and temporally synoptic data source for constraining models of land surface processes, but exploitation of these data for such purposes has been largely ad-hoc to date. In part this is because traditional land surface models, and hence most land surface data assimilation schemes, have tended to focus on a specific component of the land surface problem; typically either surface fluxes of water and energy or biogeochemical cycles such as carbon and nitrogen. Furthermore the assimilation of satellite data into such models tends to be restricted to a single wavelength domain, for example passive microwave, thermal or optical, depending on the problem at hand. The next generation of land surface schemes, such as the Joint UK Land Environment Simulator (JULES) and the US Community Land Model (CLM) represent a broader range of processes but at the expense of increasing overall model complexity and in some cases reducing the level of detail in specific processes to accommodate this. Typically, the level of physical detail used to represent the interaction of electromagnetic radiation with the surface is not sufficient to enable prediction of intrinsic satellite observations (reflectance, brightness temperature and so on) and consequently these are not assimilated directly into the models. A seemingly attractive alternative is to assimilate high-level products derived from satellite observations but these are often only superficially related to the corresponding variables in land surface models due to conflicting assumptions between the two. This poster describes the water and energy balance modeling components of a project funded by the European Space Agency to develop a data assimilation scheme for the land surface and observation operators to translate between models and the intrinsic observations acquired by satellite missions. The rationale behind the design of the underlying process model is to represent the physics of the water and energy balance in as parsimonious manner as possible, using a force-restore approach, but describing the physics of electromagnetic radiation scattering at the surface sufficiently well that it is possible to assimilate the intrinsic observations made by remote sensing instruments. In this manner the initial configuration of the resulting scheme will be able to make optimal use of available satellite observations at arbitrary wavelengths and geometries. Model complexity can then be built up from this point whilst ensuring consistency with satellite observations.

Version 3 of the SMAP Level 4 Soil Moisture Product

NASA Technical Reports Server (NTRS)

Reichle, Rolf; Liu, Qing; Ardizzone, Joe; Crow, Wade; De Lannoy, Gabrielle; Kolassa, Jana; Kimball, John; Koster, Randy

2017-01-01

The NASA Soil Moisture Active Passive (SMAP) Level 4 Soil Moisture (L4_SM) product provides 3-hourly, 9-km resolution, global estimates of surface (0-5 cm) and root zone (0-100 cm) soil moisture as well as related land surface states and fluxes from 31 March 2015 to present with a latency of 2.5 days. The ensemble-based L4_SM algorithm is a variant of the Goddard Earth Observing System version 5 (GEOS-5) land data assimilation system and ingests SMAP L-band (1.4 GHz) Level 1 brightness temperature observations into the Catchment land surface model. The soil moisture analysis is non-local (spatially distributed), performs downscaling from the 36-km resolution of the observations to that of the model, and respects the relative uncertainties of the modeled and observed brightness temperatures. Prior to assimilation, a climatological rescaling is applied to the assimilated brightness temperatures using a 6 year record of SMOS observations. A new feature in Version 3 of the L4_SM data product is the use of 2 years of SMAP observations for rescaling where SMOS observations are not available because of radio frequency interference, which expands the impact of SMAP observations on the L4_SM estimates into large regions of northern Africa and Asia. This presentation investigates the performance and data assimilation diagnostics of the Version 3 L4_SM data product. The L4_SM soil moisture estimates meet the 0.04 m3m3 (unbiased) RMSE requirement. We further demonstrate that there is little bias in the soil moisture analysis. Finally, we illustrate where the assimilation system overestimates or underestimates the actual errors in the system.

Cubesats and drones: bridging the spatio-temporal divide for enhanced earth observation

NASA Astrophysics Data System (ADS)

McCabe, M. F.; Aragon, B.; Parkes, S. D.; Mascaro, J.; Houborg, R.

2017-12-01

In just the last few years, a range of advances in remote sensing technologies have enabled an unprecedented opportunity in earth observation. Parallel developments in cubesats and unmanned aerial vehicles (UAVs) have overcome one of the outstanding challenges in observing the land surface: the provision of timely retrievals at a spatial resolution that is sufficiently detailed to make field-level decisions. Planet cubesats have revolutionized observing capacity through their objective of near daily global retrieval. These nano-satellite systems provide high resolution (approx. 3 m) retrievals in red-green-blue and near-infrared wavelengths, offering capacity to develop vegetation metrics for both hydrological and precision agricultural applications. Apart from satellite based advances, nearer to earth technology is being exploited for a range of observation needs. UAVs provide an adaptable platform from which a variety of sensing systems can be deployed. Combinations of optical, thermal, multi- and hyper-spectral systems allow for the estimation of a range of land surface variables, including vegetation structure, vegetation health, land surface temperature and evaporation. Here we explore some of these exciting developments in the context of agricultural hydrology, providing examples of cubesat and UAV imagery that has been used to inform upon crop health and water use. An investigation of the spatial and temporal advantage of these complementary systems is undertaken, with examples of multi-day high-resolution vegetation dynamics from cubesats presented alongside diurnal-cycle responses derived from multiple within-day UAV flights.

A Comparison of Methods for a Priori Bias Correction in Soil Moisture Data Assimilation

NASA Technical Reports Server (NTRS)

Kumar, Sujay V.; Reichle, Rolf H.; Harrison, Kenneth W.; Peters-Lidard, Christa D.; Yatheendradas, Soni; Santanello, Joseph A.

2011-01-01

Data assimilation is being increasingly used to merge remotely sensed land surface variables such as soil moisture, snow and skin temperature with estimates from land models. Its success, however, depends on unbiased model predictions and unbiased observations. Here, a suite of continental-scale, synthetic soil moisture assimilation experiments is used to compare two approaches that address typical biases in soil moisture prior to data assimilation: (i) parameter estimation to calibrate the land model to the climatology of the soil moisture observations, and (ii) scaling of the observations to the model s soil moisture climatology. To enable this research, an optimization infrastructure was added to the NASA Land Information System (LIS) that includes gradient-based optimization methods and global, heuristic search algorithms. The land model calibration eliminates the bias but does not necessarily result in more realistic model parameters. Nevertheless, the experiments confirm that model calibration yields assimilation estimates of surface and root zone soil moisture that are as skillful as those obtained through scaling of the observations to the model s climatology. Analysis of innovation diagnostics underlines the importance of addressing bias in soil moisture assimilation and confirms that both approaches adequately address the issue.

Understanding SMAP-L4 soil moisture estimation skill and their dependence with topography, precipitation and vegetation type using Mesonet and Micronet networks.

NASA Astrophysics Data System (ADS)

Moreno, H. A.; Basara, J. B.; Thompson, E.; Bertrand, D.; Johnston, C. S.

2017-12-01

Soil moisture measurements using satellite information can benefit from a land data assimilation model Goddard Earth Observing System (GEOS-5) and land data assimilation system (LDAS) to improve the representation of fine-scale dynamics and variability. This work presents some advances to understand the predictive skill of L4-SM product across different land-cover types, topography and precipitation totals, by using a dense network of multi-level soil moisture sensors (i.e. Mesonet and Micronet) in Oklahoma. 130 soil moisture stations are used across different precipitation gradients (i.e. arid vs wet), land cover (e.g. forest, shrubland, grasses, crops), elevation (low, mid and high) and slope to assess the improvements by the L4_SM product relative to the raw SMAP L-band brightness temperatures. The comparisons are conducted between July 2015 and July 2016 at the daily time scale. Results show the highest L4-SM overestimations occur in pastures and cultivated crops, during the rainy season and at higher elevation lands (over 800 meters asl). The smallest errors occur in low elevation lands, low rainfall and developed lands. Forested area's soil moisture biases lie in between pastures (max biases) and low intensity/developed lands (min biases). Fine scale assessment of L4-SM should help GEOS-5 and LDAS teams refine model parameters in light of observed differences and improve assimilation techniques in light of land-cover, topography and precipitation regime. Additionally, regional decision makers could have a framework to weight the utility of this product for water resources applications.

Biospheric Monitoring and Ecological Forecasting using EOS/MODIS data, ecosystem modeling, planning and scheduling technologies

NASA Astrophysics Data System (ADS)

Nemani, R. R.; Votava, P.; Golden, K.; Hashimoto, H.; Jolly, M.; White, M.; Running, S.; Coughlan, J.

2003-12-01

The latest generation of NASA Earth Observing System satellites has brought a new dimension to continuous monitoring of the living part of the Earth System, the Biosphere. EOS data can now provide weekly global measures of vegetation productivity and ocean chlorophyll, and many related biophysical factors such as land cover changes or snowmelt rates. However, information with the highest economic value would be forecasting impending conditions of the biosphere that would allow advanced decision-making to mitigate dangers, or exploit positive trends. We have developed a software system called the Terrestrial Observation and Prediction System (TOPS) to facilitate rapid analysis of ecosystem states/functions by integrating EOS data with ecosystem models, surface weather observations and weather/climate forecasts. Land products from MODIS (Moderate Resolution Imaging Spectroradiometer) including land cover, albedo, snow, surface temperature, leaf area index are ingested into TOPS for parameterization of models and for verifying model outputs such as snow cover and vegetation phenology. TOPS is programmed to gather data from observing networks such as USDA soil moisture, AMERIFLUX, SNOWTEL to further enhance model predictions. Key technologies enabling TOPS implementation include the ability to understand and process heterogeneous-distributed data sets, automated planning and execution of ecosystem models, causation analysis for understanding model outputs. Current TOPS implementations at local (vineyard) to global scales (global net primary production) can be found at http://www.ntsg.umt.edu/tops.

Estimating surface fluxes over middle and upper streams of the Heihe River Basin with ASTER imagery

NASA Astrophysics Data System (ADS)

Ma, W.; Ma, Y.; Hu, Z.; Su, Z.; Wang, J.; Ishikawa, H.

2011-05-01

Land surface heat fluxes are essential measures of the strengths of land-atmosphere interactions involving energy, heat and water. Correct parameterization of these fluxes in climate models is critical. Despite their importance, state-of-the-art observation techniques cannot provide representative areal averages of these fluxes comparable to the model grid. Alternative methods of estimation are thus required. These alternative approaches use (satellite) observables of the land surface conditions. In this study, the Surface Energy Balance System (SEBS) algorithm was evaluated in a cold and arid environment, using land surface parameters derived from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data. Field observations and estimates from SEBS were compared in terms of net radiation flux (Rn), soil heat flux (G0), sensible heat flux (H) and latent heat flux (λE) over a heterogeneous land surface. As a case study, this methodology was applied to the experimental area of the Watershed Allied Telemetry Experimental Research (WATER) project, located on the mid-to-upstream sections of the Heihe River in northwest China. ASTER data acquired between 3 May and 4 June 2008, under clear-sky conditions were used to determine the surface fluxes. Ground-based measurements of land surface heat fluxes were compared with values derived from the ASTER data. The results show that the derived surface variables and the land surface heat fluxes furnished by SEBS in different months over the study area are in good agreement with the observed land surface status under the limited cases (some cases looks poor results). So SEBS can be used to estimate turbulent heat fluxes with acceptable accuracy in areas where there is partial vegetation cover in exceptive conditions. It is very important to perform calculations using ground-based observational data for parameterization in SEBS in the future. Nevertheless, the remote-sensing results can provide improved explanations of land surface fluxes over varying land coverage at greater spatial scales.

Land and cryosphere products from Suomi NPP VIIRS: Overview and status.

PubMed

Justice, Christopher O; Román, Miguel O; Csiszar, Ivan; Vermote, Eric F; Wolfe, Robert E; Hook, Simon J; Friedl, Mark; Wang, Zhuosen; Schaaf, Crystal B; Miura, Tomoaki; Tschudi, Mark; Riggs, George; Hall, Dorothy K; Lyapustin, Alexei I; Devadiga, Sadashiva; Davidson, Carol; Masuoka, Edward J

2013-09-16

[1] The Visible Infrared Imaging Radiometer Suite (VIIRS) instrument was launched in October 2011 as part of the Suomi National Polar-Orbiting Partnership (S-NPP). The VIIRS instrument was designed to improve upon the capabilities of the operational Advanced Very High Resolution Radiometer and provide observation continuity with NASA's Earth Observing System's Moderate Resolution Imaging Spectroradiometer (MODIS). Since the VIIRS first-light images were received in November 2011, NASA- and NOAA-funded scientists have been working to evaluate the instrument performance and generate land and cryosphere products to meet the needs of the NOAA operational users and the NASA science community. NOAA's focus has been on refining a suite of operational products known as Environmental Data Records (EDRs), which were developed according to project specifications under the National Polar-Orbiting Environmental Satellite System. The NASA S-NPP Science Team has focused on evaluating the EDRs for science use, developing and testing additional products to meet science data needs, and providing MODIS data product continuity. This paper presents to-date findings of the NASA Science Team's evaluation of the VIIRS land and cryosphere EDRs, specifically Surface Reflectance, Land Surface Temperature, Surface Albedo, Vegetation Indices, Surface Type, Active Fires, Snow Cover, Ice Surface Temperature, and Sea Ice Characterization. The study concludes that, for MODIS data product continuity and earth system science, an enhanced suite of land and cryosphere products and associated data system capabilities are needed beyond the EDRs currently available from the VIIRS.

"Detecting people"

NASA Astrophysics Data System (ADS)

Arneth, A.; Pugh, T.; Krause, A.; Bayer, A.; Lindeskog, M.

2015-12-01

Land-use change (LUC) is known to significantly affect biogeochemical cycles as well as surface energy partitioning - with important implications, ranging from understanding present-day measurements, to simulations of climate change and impacts on ecosystems, to assessments of the mitigation potential of land-based mitigation policies on ecosystems. When connecting observations of surface-atmosphere interactions and modelling at different scales, two important issues in this context are: legacy effects (e.g., to what degree and for how long does past LUC at a given location affect vegetation structure, CO2 fluxes and carbon pools), and sub-grid variability of the land-use change per se (e.g., whether bi-directional information about changes are taken into consideration). Both are important when bridging between scales (in time and in space) to enhance long-term observation networks. This contribution to the session will be very much from a process-based modelling perspective. Using a second generation dynamic global vegetation model we will show how different land-use histories impact vegetation and soil recovery (carbon pool-size, fluxes) differently, depending on the type of previous land-use, its length, and on the type of biome. We also study the difference between "gross" and "net" LUC accounting for simulated carbon cycling. Two important aspects, considering the session's objectives, are: 1) When establishing and developing observation networks, land-use history is key information for the interpretation of measured fluxes and needs to be collected and made available;, 2) Observation networks that "operate" solely in the natural science domain need to increasingly seek cooperation with socio-economic observations (such as land-use change, land management) in order to gain better understanding of coupled socio-ecological systems.

High resolution land surface response of inland moving Indian monsoon depressions over Bay of Bengal

NASA Astrophysics Data System (ADS)

Rajesh, P. V.; Pattnaik, S.

2016-05-01

During Indian summer monsoon (ISM) season, nearly about half of the monsoonal rainfall is brought inland by the low pressure systems called as Monsoon Depressions (MDs). These systems bear large amount of rainfall and frequently give copious amount of rainfall over land regions, therefore accurate forecast of these synoptic scale systems at short time scale can help in disaster management, flood relief, food safety. The goal of this study is to investigate, whether an accurate moisture-rainfall feedback from land surface can improve the prediction of inland moving MDs. High Resolution Land Data Assimilation System (HRLDAS) is used to generate improved land state .i.e. soil moisture and soil temperature profiles by means of NOAH-MP land-surface model. Validation of the model simulated basic atmospheric parameters at surface layer and troposphere reveals that the incursion of high resolution land state yields least Root Mean Squared Error (RMSE) with a higher correlation coefficient and facilitates accurate depiction of MDs. Rainfall verification shows that HRLDAS simulations are spatially and quantitatively in more agreement with the observations and the improved surface characteristics could result in the realistic reproduction of the storm spatial structure, movement as well as intensity. These results signify the necessity of investigating more into the land surface-rainfall feedbacks through modifications in moisture flux convergence within the storm.

Reconnoitering the effect of shallow groundwater on land surface temperature and surface energy balance using MODIS and SEBS

USDA-ARS?s Scientific Manuscript database

The possibility of observing shallow groundwater depth and areal extent using satellite measurements can support groundwater models and vast irrigation systems management. Besides, these measurements help to integrate groundwater effects on surface energy balance within land surface models and clima...

The role of statewide planning goals in Oregon's system of coordination and planning and their effect on transportation planning.

DOT National Transportation Integrated Search

2008-01-01

The motivation for this study was the observation that the reactive approach to the coordination of land use and transportation planning, which treats transportation planning as the handmaiden of land use planning and which greatly limits the options...

Earth Observing-1 Advanced Land Imager: Radiometric Response Calibration

NASA Technical Reports Server (NTRS)

Mendenhall, J. A.; Lencioni, D. E.; Evans, J. B.

2000-01-01

The Advanced Land Imager (ALI) is one of three instruments to be flown on the first Earth Observing mission (EO-1) under NASA's New Millennium Program (NMP). ALI contains a number of innovative features, including a wide field of view optical design, compact multispectral focal plane arrays, non-cryogenic HgCdTe detectors for the short wave infrared bands, and silicon carbide optics. This document outlines the techniques adopted during ground calibration of the radiometric response of the Advanced Land Imager. Results from system level measurements of the instrument response, signal-to-noise ratio, saturation radiance, and dynamic range for all detectors of every spectral band are also presented.

Evaluating Land-Atmosphere Moisture Feedbacks in Earth System Models With Spaceborne Observations

NASA Astrophysics Data System (ADS)

Levine, P. A.; Randerson, J. T.; Lawrence, D. M.; Swenson, S. C.

2016-12-01

We have developed a set of metrics for measuring the feedback loop between the land surface moisture state and the atmosphere globally on an interannual time scale. These metrics consider both the forcing of terrestrial water storage (TWS) on subsequent atmospheric conditions as well as the response of TWS to antecedent atmospheric conditions. We designed our metrics to take advantage of more than one decade's worth of satellite observations of TWS from the Gravity Recovery and Climate Experiment (GRACE) along with atmospheric variables from the Atmospheric Infrared Sounder (AIRS), the Global Precipitation Climatology Project (GPCP), and Clouds and the Earths Radiant Energy System (CERES). Metrics derived from spaceborne observations were used to evaluate the strength of the feedback loop in the Community Earth System Model (CESM) Large Ensemble (LENS) and in several models that contributed simulations to Phase 5 of the Coupled Model Intercomparison Project (CMIP5). We found that both forcing and response limbs of the feedback loop were generally stronger in tropical and temperate regions in CMIP5 models and even more so in LENS compared to satellite observations. Our analysis suggests that models may overestimate the strength of the feedbacks between the land surface and the atmosphere, which is consistent with previous studies conducted across different spatial and temporal scales.

Investigating potential transferability of place-based research in land system science

NASA Astrophysics Data System (ADS)

Václavík, Tomáš; Langerwisch, Fanny; Cotter, Marc; Fick, Johanna; Häuser, Inga; Hotes, Stefan; Kamp, Johannes; Settele, Josef; Spangenberg, Joachim H.; Seppelt, Ralf

2016-09-01

Much of our knowledge about land use and ecosystem services in interrelated social-ecological systems is derived from place-based research. While local and regional case studies provide valuable insights, it is often unclear how relevant this research is beyond the study areas. Drawing generalized conclusions about practical solutions to land management from local observations and formulating hypotheses applicable to other places in the world requires that we identify patterns of land systems that are similar to those represented by the case study. Here, we utilize the previously developed concept of land system archetypes to investigate potential transferability of research from twelve regional projects implemented in a large joint research framework that focus on issues of sustainable land management across four continents. For each project, we characterize its project archetype, i.e. the unique land system based on a synthesis of more than 30 datasets of land-use intensity, environmental conditions and socioeconomic indicators. We estimate the transferability potential of project research by calculating the statistical similarity of locations across the world to the project archetype, assuming higher transferability potentials in locations with similar land system characteristics. Results show that areas with high transferability potentials are typically clustered around project sites but for some case studies can be found in regions that are geographically distant, especially when values of considered variables are close to the global mean or where the project archetype is driven by large-scale environmental or socioeconomic conditions. Using specific examples from the local case studies, we highlight the merit of our approach and discuss the differences between local realities and information captured in global datasets. The proposed method provides a blueprint for large research programs to assess potential transferability of place-based studies to other geographical areas and to indicate possible gaps in research efforts.

Assimilation of Feng-Yun-3B satellite microwave humidity sounder data over land

NASA Astrophysics Data System (ADS)

Chen, Keyi; Bormann, Niels; English, Stephen; Zhu, Jiang

2018-03-01

The ECMWF has been assimilating Feng-Yun-3B (FY-3B) satellite microwave humidity sounder (MWHS) data over ocean in an operational forecasting system since 24 September 2014. It is more difficult, however, to assimilate microwave observations over land and sea ice than over the open ocean due to higher uncertainties in land surface temperature, surface emissivity and less effective cloud screening. We compare approaches in which the emissivity is retrieved dynamically from MWHS channel 1 [150 GHz (vertical polarization)] with the use of an evolving emissivity atlas from 89 GHz observations from the MWHS onboard NOAA and EUMETSAT satellites. The assimilation of the additional data over land improves the fit of short-range forecasts to other observations, notably ATMS (Advanced Technology Microwave Sounder) humidity channels, and the forecast impacts are mainly neutral to slightly positive over the first five days. The forecast impacts are better in boreal summer and the Southern Hemisphere. These results suggest that the techniques tested allow for effective assimilation of MWHS/FY-3B data over land.

Advances in U.S. Land Imaging Capabilities

NASA Astrophysics Data System (ADS)

Stryker, T. S.

2017-12-01

Advancements in Earth observations, cloud computing, and data science are improving everyday life. Information from land-imaging satellites, such as the U.S. Landsat system, helps us to better understand the changing landscapes where we live, work, and play. This understanding builds capacity for improved decision-making about our lands, waters, and resources, driving economic growth, protecting lives and property, and safeguarding the environment. The USGS is fostering the use of land remote sensing technology to meet local, national, and global challenges. A key dimension to meeting these challenges is the full, free, and open provision of land remote sensing observations for both public and private sector applications. To achieve maximum impact, these data must also be easily discoverable, accessible, and usable. The presenter will describe the USGS Land Remote Sensing Program's current capabilities and future plans to collect and deliver land remote sensing information for societal benefit. He will discuss these capabilities in the context of national plans and policies, domestic partnerships, and international collaboration. The presenter will conclude with examples of how Landsat data is being used on a daily basis to improve lives and livelihoods.

Evaluation of reanalysis datasets against observational soil temperature data over China

NASA Astrophysics Data System (ADS)

Yang, Kai; Zhang, Jingyong

2018-01-01

Soil temperature is a key land surface variable, and is a potential predictor for seasonal climate anomalies and extremes. Using observational soil temperature data in China for 1981-2005, we evaluate four reanalysis datasets, the land surface reanalysis of the European Centre for Medium-Range Weather Forecasts (ERA-Interim/Land), the second modern-era retrospective analysis for research and applications (MERRA-2), the National Center for Environmental Prediction Climate Forecast System Reanalysis (NCEP-CFSR), and version 2 of the Global Land Data Assimilation System (GLDAS-2.0), with a focus on 40 cm soil layer. The results show that reanalysis data can mainly reproduce the spatial distributions of soil temperature in summer and winter, especially over the east of China, but generally underestimate their magnitudes. Owing to the influence of precipitation on soil temperature, the four datasets perform better in winter than in summer. The ERA-Interim/Land and GLDAS-2.0 produce spatial characteristics of the climatological mean that are similar to observations. The interannual variability of soil temperature is well reproduced by the ERA-Interim/Land dataset in summer and by the CFSR dataset in winter. The linear trend of soil temperature in summer is well rebuilt by reanalysis datasets. We demonstrate that soil heat fluxes in April-June and in winter are highly correlated with the soil temperature in summer and winter, respectively. Different estimations of surface energy balance components can contribute to different behaviors in reanalysis products in terms of estimating soil temperature. In addition, reanalysis datasets can mainly rebuild the northwest-southeast gradient of soil temperature memory over China.

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.

New Directions in Land Remote Sensing Policy and International Cooperation

NASA Astrophysics Data System (ADS)

Stryker, Timothy

2010-12-01

Recent changes to land remote sensing satellite data policies in Brazil and the United States have led to the phenomenal growth in the delivery of land imagery to users worldwide. These new policies, which provide free and unrestricted access to land remote sensing data over a standard electronic interface, are expected to provide significant benefits to scientific and operational users, and open up new areas of Earth system science research and environmental monitoring. Freely-available data sets from the China-Brazil Earth Resources Satellites (CBERS), the U.S. Landsat satellites, and other satellite missions provide essential information for land surface monitoring, ecosystems management, disaster mitigation, and climate change research. These missions are making important contributions to the goals and objectives of regional and global terrestrial research and monitoring programs. These programs are in turn providing significant support to the goals and objectives of the United Nations Framework Convention on Climate Change (UN FCCC), the Global Earth Observation System of Systems (GEOSS), and the UN Reduction in Emissions from Deforestation and Degradation (REDD) program. These data policies are well-aligned with the "Data Democracy" initiative undertaken by the international Committee on Earth Observation Satellites (CEOS), through its current Chair, Brazil's National Institute for Space Research (Instituto Nacional de Pesquisas Espaciais, or INPE), and its former chairs, South Africa's Council for Scientific and Industrial Research (CSIR) and Thailand's Geo Informatics and Space Technology Development Agency (GISTDA). Comparable policies for land imaging data are under consideration within Europe and Canada. Collectively, these initiatives have the potential to accelerate and improve international mission collaboration, and greatly enhance the access, use, and application of land surface imagery for environmental monitoring and societal adaption to changing climate conditions.

The monsoon system: Land-sea breeze or the ITCZ?

NASA Astrophysics Data System (ADS)

Gadgil, Sulochana

2018-02-01

For well over 300 years, the monsoon has been considered to be a gigantic land-sea breeze driven by the land-ocean contrast in surface temperature. In this paper, this hypothesis and its implications for the variability of the monsoon are discussed and it is shown that the observations of monsoon variability do not support this popular theory of the monsoon. An alternative hypothesis (whose origins can be traced to Blanford's (1886) remarkably perceptive analysis) in which the basic system responsible for the Indian summer monsoon is considered to be the Intertropical Convergence Zone (ITCZ) or the equatorial trough, is then examined and shown to be consistent with the observations. The implications of considering the monsoon as a manifestation of the seasonal migration of the ITCZ for the variability of the Indian summer monsoon and for identification of the monsoonal regions of the world are briefly discussed.

Experimental land observing data system feasibility study

NASA Technical Reports Server (NTRS)

Buckley, J. L.; Kraiman, H.

1982-01-01

An end-to-end data system to support a Shuttle-based Multispectral Linear Array (MLA) mission in the mid-1980's was defined. The experimental Land Observing System (ELOS) is discussed. A ground system that exploits extensive assets from the LANDSAT-D Program to effectively meet the objectives of the ELOS Mission was defined. The goal of 10 meter pixel precision, the variety of data acquisition capabilities, and the use of Shuttle are key to the mission requirements, Ground mission management functions are met through the use of GSFC's Multi-Satellite Operations Control Center (MSOCC). The MLA Image Generation Facility (MIGF) combines major hardware elements from the Applications Development Data System (ADDS) facility and LANDSAT Assessment System (LAS) with a special purpose MLA interface unit. LANDSAT-D image processing techniques, adapted to MLA characteristics, form the basis for the use of existing software and the definition of new software required.

Industrial use of land observation satellite systems

NASA Technical Reports Server (NTRS)

Henderson, F. B., III

1984-01-01

The principal industrial users of land observation satellite systems are the geological industries; oil/gas, mining, and engineering/environmental companies. The primary system used is LANDSAT/MSS. Currently, use is also being made of the limited amounts of SKYLAB photography, SEASAT and SIR-A radar, and the new LANDSAT/TM data available. Although considered experimental, LANDSAT data is now used operationally by several hundred exploration and engineering companies worldwide as a vastly improved geological mapping tool to help direct more expensive geophysical and drilling phases, leading to more efficient decision-making and results. Future needs include global LANDSAT/TM; higher spatial resolution; stereo and radar; improved data handling, processing distribution and archiving systems, and integrated geographical information systems (GIS). For a promising future, governments must provide overall continuity (government and/or private sector) of such systems, insure continued government R and D, and commit to operating internationally under the civil Open Skies policy.

Cross-compartment evaluation of a fully-coupled hydrometeorological modeling system using comprehensive observation data

NASA Astrophysics Data System (ADS)

Fersch, Benjamin; Senatore, Alfonso; Kunstmann, Harald

2017-04-01

Fully-coupled hydrometeorological modeling enables investigations about the complex and often non-linear exchange mechanisms among subsurface, land, and atmosphere with respect to water and energy fluxes. The consideration of lateral redistribution of surface and subsurface water in such modeling systems is a crucial enhancement, allowing for a better representation of surface spatial patterns and providing also channel discharge predictions. However, the evaluation of fully-coupled simulations is difficult since the amount of physical detail along with feedback mechanisms leads to high degrees of freedom. Therefore, comprehensive observation data is required to obtain meaningful model configurations. We present a case study for a medium-sized river catchment in southern Germany that includes the calibration of the stand-alone and the evaluation of the fully-coupled WRF-Hydro modeling system with a horizontal resolution of 1 x 1 km2, for the period June to August 2015. ECMWF ERA-Interim reanalysis is used for model driving. Land-surface processes are represented by the Noah-MP land surface model. Land-cover is described by the EU CORINE data set. Observations for model evaluation are obtained from the TERENO Pre-Alpine observatory (http://www.imk-ifu.kit.edu/tereno.php) and are complemented by further measurements from the ScaleX campaign (http://scalex.imk-ifu.kit.edu) such as atmospheric profiles obtained from radiometer sounding and airborne systems as well as soil moisture and -temperature networks. We show how well water budgets and heat-fluxes are being reproduced by the stand-alone WRF, the stand-alone WRF-Hydro and the fully-coupled WRF-Hydro model.

Development and verification of a new wind speed forecasting system using an ensemble Kalman filter data assimilation technique in a fully coupled hydrologic and atmospheric model

NASA Astrophysics Data System (ADS)

Williams, John L.; Maxwell, Reed M.; Monache, Luca Delle

2013-12-01

Wind power is rapidly gaining prominence as a major source of renewable energy. Harnessing this promising energy source is challenging because of the chaotic nature of wind and its inherently intermittent nature. Accurate forecasting tools are critical to support the integration of wind energy into power grids and to maximize its impact on renewable energy portfolios. We have adapted the Data Assimilation Research Testbed (DART), a community software facility which includes the ensemble Kalman filter (EnKF) algorithm, to expand our capability to use observational data to improve forecasts produced with a fully coupled hydrologic and atmospheric modeling system, the ParFlow (PF) hydrologic model and the Weather Research and Forecasting (WRF) mesoscale atmospheric model, coupled via mass and energy fluxes across the land surface, and resulting in the PF.WRF model. Numerous studies have shown that soil moisture distribution and land surface vegetative processes profoundly influence atmospheric boundary layer development and weather processes on local and regional scales. We have used the PF.WRF model to explore the connections between the land surface and the atmosphere in terms of land surface energy flux partitioning and coupled variable fields including hydraulic conductivity, soil moisture, and wind speed and demonstrated that reductions in uncertainty in these coupled fields realized through assimilation of soil moisture observations propagate through the hydrologic and atmospheric system. The sensitivities found in this study will enable further studies to optimize observation strategies to maximize the utility of the PF.WRF-DART forecasting system.

Comparison of Observation Impacts in Two Forecast Systems using Adjoint Methods

NASA Technical Reports Server (NTRS)

Gelaro, Ronald; Langland, Rolf; Todling, Ricardo

2009-01-01

An experiment is being conducted to compare directly the impact of all assimilated observations on short-range forecast errors in different operational forecast systems. We use the adjoint-based method developed by Langland and Baker (2004), which allows these impacts to be efficiently calculated. This presentation describes preliminary results for a "baseline" set of observations, including both satellite radiances and conventional observations, used by the Navy/NOGAPS and NASA/GEOS-5 forecast systems for the month of January 2007. In each system, about 65% of the total reduction in 24-h forecast error is provided by satellite observations, although the impact of rawinsonde, aircraft, land, and ship-based observations remains significant. Only a small majority (50- 55%) of all observations assimilated improves the forecast, while the rest degrade it. It is found that most of the total forecast error reduction comes from observations with moderate-size innovations providing small to moderate impacts, not from outliers with very large positive or negative innovations. In a global context, the relative impacts of the major observation types are fairly similar in each system, although regional differences in observation impact can be significant. Of particular interest is the fact that while satellite radiances have a large positive impact overall, they degrade the forecast in certain locations common to both systems, especially over land and ice surfaces. Ongoing comparisons of this type, with results expected from other operational centers, should lead to more robust conclusions about the impacts of the various components of the observing system as well as about the strengths and weaknesses of the methodologies used to assimilate them.

Benefits and Pitfalls of GRACE Terrestrial Water Storage Data Assimilation

NASA Technical Reports Server (NTRS)

Girotto, Manuela

2018-01-01

Satellite observations of terrestrial water storage (TWS) from the Gravity Recovery and Climate Experiment (GRACE) mission have a coarse resolution in time (monthly) and space (roughly 150,000 sq km at midlatitudes) and vertically integrate all water storage components over land, including soil moisture and groundwater. Nonetheless, data assimilation can be used to horizontally downscale and vertically partition GRACE-TWS observations. This presentation illustrates some of the benefits and drawbacks of assimilating TWS observations from GRACE into a land surface model over the continental United States and India. The assimilation scheme yields improved skill metrics for groundwater compared to the no-assimilation simulations. A smaller impact is seen for surface and root-zone soil moisture. Further, GRACE observes TWS depletion associated with anthropogenic groundwater extraction. Results from the assimilation emphasize the importance of representing anthropogenic processes in land surface modeling and data assimilation systems.

DasPy 1.0 - the Open Source Multivariate Land Data Assimilation Framework in combination with the Community Land Model 4.5

NASA Astrophysics Data System (ADS)

Han, X.; Li, X.; He, G.; Kumbhar, P.; Montzka, C.; Kollet, S.; Miyoshi, T.; Rosolem, R.; Zhang, Y.; Vereecken, H.; Franssen, H.-J. H.

2015-08-01

Data assimilation has become a popular method to integrate observations from multiple sources with land surface models to improve predictions of the water and energy cycles of the soil-vegetation-atmosphere continuum. Multivariate data assimilation refers to the simultaneous assimilation of observation data from multiple model state variables into a simulation model. In recent years, several land data assimilation systems have been developed in different research agencies. Because of the software availability or adaptability, these systems are not easy to apply for the purpose of multivariate land data assimilation research. We developed an open source multivariate land data assimilation framework (DasPy) which is implemented using the Python script language mixed with the C++ and Fortran programming languages. LETKF (Local Ensemble Transform Kalman Filter) is implemented as the main data assimilation algorithm, and uncertainties in the data assimilation can be introduced by perturbed atmospheric forcing data, and represented by perturbed soil and vegetation parameters and model initial conditions. The Community Land Model (CLM) was integrated as the model operator. The implementation allows also parameter estimation (soil properties and/or leaf area index) on the basis of the joint state and parameter estimation approach. The Community Microwave Emission Modelling platform (CMEM), COsmic-ray Soil Moisture Interaction Code (COSMIC) and the Two-Source Formulation (TSF) were integrated as observation operators for the assimilation of L-band passive microwave, cosmic-ray soil moisture probe and land surface temperature measurements, respectively. DasPy has been evaluated in several assimilation studies of neutron count intensity (soil moisture), L-band brightness temperature and land surface temperature. DasPy is parallelized using the hybrid Message Passing Interface and Open Multi-Processing techniques. All the input and output data flows are organized efficiently using the commonly used NetCDF file format. Online 1-D and 2-D visualization of data assimilation results is also implemented to facilitate the post simulation analysis. In summary, DasPy is a ready to use open source parallel multivariate land data assimilation framework.

Assimilation of SMOS (and SMAP) Retrieved Soil Moisture into the Land Information System

NASA Technical Reports Server (NTRS)

Blankenship, Clay; Zavodsky, Bradley; Case, Jonathan; Stano, Geoffrey

2016-01-01

Goal: Accurate, high-resolution (approx.3 km) soil moisture in near-real time. Situational awareness (drought assessment, flood and fire threat). Local modeling applications (to improve sfc-PBL exchanges) Method: Assimilate satellite soil moisture retrievals into a land surface model. Combines high-resolution geophysical model data with latest satellite observations.

MEaSUREs Land Surface Temperature from GOES Satellites

NASA Astrophysics Data System (ADS)

Pinker, Rachel T.; Chen, Wen; Ma, Yingtao; Islam, Tanvir; Borbas, Eva; Hain, Chris; Hulley, Glynn; Hook, Simon

2017-04-01

Information on Land Surface Temperature (LST) can be generated from observations made from satellites in low Earth orbit (LEO) such as MODIS and ASTER and by sensors in geostationary Earth orbit (GEO) such as GOES. Under a project titled: "A Unified and Coherent Land Surface Temperature and Emissivity Earth System Data Record for Earth Science" led by Jet Propulsion Laboratory, an effort is underway to develop long term consistent information from both such systems. In this presentation we will describe an effort to derive LST information from GOES satellites. Results will be presented from two approaches: 1) based on regression developed from a wide range of simulations using MODTRAN, SeeBor Version 5.0 global atmospheric profiles and the CAMEL (Combined ASTER and MODIS Emissivity for Land) product based on the standard University of Wisconsin 5 km emissivity values (UWIREMIS) and the ASTER Global Emissivity Database (GED) product; 2) RTTOV radiative transfer model driven with MERRA-2 reanalysis fields. We will present results of evaluation of these two methods against various products, such as MOD11, and ground observations for the five year period of (2004-2008).

Autonomous BBOBS-NX (NX-2G) for New Era of Ocean Bottom Broadband Seismology

NASA Astrophysics Data System (ADS)

Shiobara, H.; Ito, A.; Sugioka, H.; Shinohara, M.

2017-12-01

The broadband ocean bottom seismometer (BBOBS) and its new generation system (BBOBS-NX) have been developed in Japan, and we performed several test and practical observations to create and establish a new category of the ocean floor broadband seismology, since 1999. Now, the data obtained by our BBOBS and BBOBS-NX is proved to be adequate for broadband seismic analyses. Especially, the BBOBS-NX can obtain the horizontal data comparable to land sites in longer periods (10 s -). Moreover, the BBOBST-NX is in practical evaluation for the mobile tilt observation that enables dense geodetic monitoring. The BBOBS-NX system is a powerful tool, although, it has intrinsic limitation of the ROV operation. If this system can be used without the ROV, like as the BBOBS, it should lead us a true breakthrough of ocean bottom seismology. Hereafter, the new autonomous BBOBS-NX is noted as NX-2G in short. The main problem to realize the NX-2G is a tilt of the sensor unit on landing, which exceed the acceptable limit (±8°) in about 50%. As we had no evidence at which moment and how this tilt occurred, we tried to observe it during the BBOBST-NX landing in 2015 by attaching a video camera and an acceleration logger. The result shows that the tilt on landing was determined by the final posture of the system at the penetration into the sediment, and the large oscillating tilt more than ±10° was observed in descending. The function of the NX-2G system is based on 3 stage operations as shown in the image. The glass float is aimed not only to obtain enough buoyancy to extract the sensor unit, but also to suppress the oscillating tilt of the system in descending. In Oct. 2016, we made the first in-situ test of the NX-2G system with a ROV. It was dropped from the sea surface with the video camera and the acceleration logger. The ROV was used to watch the operation of the system at the seafloor. The landing looked well and it was examined from the acceleration data. As the maximum tilt in descending was about ±2.5°, the glass float effectively suppressed the oscillating tilt. The extraction of the sensor unit was also succeeded with the total buoyancy of about 75 kgf within about 2.5 minutes. As the final step experiment, the one-year-long observation of this NX-2G system has been started in this April with the BBOBS, to obtain simultaneous data for the noise level evaluation.

BOREAS AFM-12 1-km AVHRR Seasonal Land Cover Classification

NASA Technical Reports Server (NTRS)

Steyaert, Lou; Hall, Forrest G.; Newcomer, Jeffrey A. (Editor); Knapp, David E. (Editor); Loveland, Thomas R.; Smith, David E. (Technical Monitor)

2000-01-01

The Boreal Ecosystem-Atmosphere Study (BOREAS) Airborne Fluxes and Meteorology (AFM)-12 team's efforts focused on regional scale Surface Vegetation and Atmosphere (SVAT) modeling to improve parameterization of the heterogeneous BOREAS landscape for use in larger scale Global Circulation Models (GCMs). This regional land cover data set was developed as part of a multitemporal one-kilometer Advanced Very High Resolution Radiometer (AVHRR) land cover analysis approach that was used as the basis for regional land cover mapping, fire disturbance-regeneration, and multiresolution land cover scaling studies in the boreal forest ecosystem of central Canada. This land cover classification was derived by using regional field observations from ground and low-level aircraft transits to analyze spectral-temporal clusters that were derived from an unsupervised cluster analysis of monthly Normalized Difference Vegetation Index (NDVI) image composites (April-September 1992). This regional data set was developed for use by BOREAS investigators, especially those involved in simulation modeling, remote sensing algorithm development, and aircraft flux studies. Based on regional field data verification, this multitemporal one-kilometer AVHRR land cover mapping approach was effective in characterizing the biome-level land cover structure, embedded spatially heterogeneous landscape patterns, and other types of key land cover information of interest to BOREAS modelers.The land cover mosaics in this classification include: (1) wet conifer mosaic (low, medium, and high tree stand density), (2) mixed coniferous-deciduous forest (80% coniferous, codominant, and 80% deciduous), (3) recent visible bum, vegetation regeneration, or rock outcrops-bare ground-sparsely vegetated slow regeneration bum (four classes), (4) open water and grassland marshes, and (5) general agricultural land use/ grasslands (three classes). This land cover mapping approach did not detect small subpixel-scale landscape features such as fens, bogs, and small water bodies. Field observations and comparisons with Landsat Thematic Mapper (TM) suggest a minimum effective resolution of these land cover classes in the range of three to four kilometers, in part, because of the daily to monthly compositing process. In general, potential accuracy limitations are mitigated by the use of conservative parameterization rules such as aggregation of predominant land cover classes within minimum horizontal grid cell sizes of ten kilometers. The AFM-12 one-kilometer AVHRR seasonal land cover classification data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files are available on a CD-ROM (see document number 20010000884).

Diagnosing the Nature of Land-Atmosphere Coupling During the 2006-7 Dry/Wet Extremes in the U. S. Southern Great Plains

NASA Technical Reports Server (NTRS)

Santanello, Joseph A., Jr.; Peters-Lidard, Christa D.; Kumar, Sujay V.; Dong, Xiquan; Kennedy, Aaron D.

2011-01-01

The degree of coupling between the land surface and PBL in NWP models remains largely undiagnosed due to the complex interactions and feedbacks present across a range of scales. In this study, a framework for diagnosing local land-atmosphere coupling (LoCo) is presented using a coupled mesoscale model with observations during the summers of 2006/7 in the U.S. Southern Great Plains. Specifically, the Weather Research and Forecasting (WRF) model has been coupled to NASA's Land Information System (LIS), which enables a suite of PBL and land surface model (LSM) options along provides a flexible and high-resolution representation and initialization of land surface physics and states. This coupling is one component of a larger project to develop a NASA-Unified WRF (NU-WRF) system. A range of diagnostics exploring the feedbacks between soil moisture and precipitation are examined for the dry/wet extremes, along with the sensitivity of PBL-LSM coupling to perturbations in soil moisture.

Tower-scale performance of four observation-based evapotranspiration algorithms within the WACMOS-ET project

NASA Astrophysics Data System (ADS)

Michel, Dominik; Miralles, Diego; Jimenez, Carlos; Ershadi, Ali; McCabe, Matthew F.; Hirschi, Martin; Seneviratne, Sonia I.; Jung, Martin; Wood, Eric F.; (Bob) Su, Z.; Timmermans, Joris; Chen, Xuelong; Fisher, Joshua B.; Mu, Quiaozen; Fernandez, Diego

2015-04-01

Research on climate variations and the development of predictive capabilities largely rely on globally available reference data series of the different components of the energy and water cycles. Several efforts have recently aimed at producing large-scale and long-term reference data sets of these components, e.g. based on in situ observations and remote sensing, in order to allow for diagnostic analyses of the drivers of temporal variations in the climate system. Evapotranspiration (ET) is an essential component of the energy and water cycle, which cannot be monitored directly on a global scale by remote sensing techniques. In recent years, several global multi-year ET data sets have been derived from remote sensing-based estimates, observation-driven land surface model simulations or atmospheric reanalyses. The LandFlux-EVAL initiative presented an ensemble-evaluation of these data sets over the time periods 1989-1995 and 1989-2005 (Mueller et al. 2013). The WACMOS-ET project (http://wacmoset.estellus.eu) started in the year 2012 and constitutes an ESA contribution to the GEWEX initiative LandFlux. It focuses on advancing the development of ET estimates at global, regional and tower scales. WACMOS-ET aims at developing a Reference Input Data Set exploiting European Earth Observations assets and deriving ET estimates produced by a set of four ET algorithms covering the period 2005-2007. The algorithms used are the SEBS (Su et al., 2002), Penman-Monteith from MODIS (Mu et al., 2011), the Priestley and Taylor JPL model (Fisher et al., 2008) and GLEAM (Miralles et al., 2011). The algorithms are run with Fluxnet tower observations, reanalysis data (ERA-Interim), and satellite forcings. They are cross-compared and validated against in-situ data. In this presentation the performance of the different ET algorithms with respect to different temporal resolutions, hydrological regimes, land cover types (including grassland, cropland, shrubland, vegetation mosaic, savanna, woody savanna, needleleaf forest, deciduous forest and mixed forest) are evaluated at the tower-scale in 24 pre-selected study regions on three continents (Europe, North America, and Australia). References: Fisher, J. B., Tu, K.P., and Baldocchi, D.D. Global estimates of the land-atmosphere water flux based on monthly AVHRR and ISLSCP-II data, validated at 16 FLUXNET sites, Remote Sens. Environ. 112, 901-919, 2008. Jiménez, C. et al. Global intercomparison of 12 land surface heat flux estimates. J. Geophys. Res. 116, D02102, 2011. 
 Miralles, D.G. et al. Global land-surface evaporation estimated from satellite-based observations. Hydrol. Earth Syst. Sci. 15, 453-469, 2011. 
 Mu, Q., Zhao, M. & Running, S.W. Improvements to a MODIS global terrestrial evapotranspiration algorithm. Remote Sens. Environ. 115, 1781-1800, 2011. 
 Mueller, B., Hirschi, M., Jimenez, C., Ciais, P., Dirmeyer, P. A., Dolman, A. J., Fisher, J. B., Jung, M., Ludwig, F., Maignan, F., Miralles, D. G., McCabe, M. F., Reichstein, M., Sheffield, J., Wang, K., Wood, E. F., Zhang, Y., and Seneviratne, S. I. (2013). Benchmark products for land evapotranspiration: LandFlux-EVAL multi-data set synthesis. Hydrology and Earth System Sciences, 17, 3707-3720. Mueller, B. et al. Benchmark products for land evapotranspiration: LandFlux-EVAL multi-dataset synthesis. Hydrol. Earth Syst. Sci. 17, 3707-3720, 2013. Su, Z. The Surface Energy Balance System (SEBS) for estimation of turbulent heat fluxes. Hydrol. Earth Syst. Sci. 6, 85-99, 2002.

Land subsidence and relative sea-level rise in the southern Chesapeake Bay region

USGS Publications Warehouse

Eggleston, Jack; Pope, Jason

2013-01-01

The southern Chesapeake Bay region is experiencing land subsidence and rising water levels due to global sea-level rise; land subsidence and rising water levels combine to cause relative sea-level rise. Land subsidence has been observed since the 1940s in the southern Chesapeake Bay region at rates of 1.1 to 4.8 millimeters per year (mm/yr), and subsidence continues today. This land subsidence helps explain why the region has the highest rates of sea-level rise on the Atlantic Coast of the United States. Data indicate that land subsidence has been responsible for more than half the relative sea-level rise measured in the region. Land subsidence increases the risk of flooding in low-lying areas, which in turn has important economic, environmental, and human health consequences for the heavily populated and ecologically important southern Chesapeake Bay region. The aquifer system in the region has been compacted by extensive groundwater pumping in the region at rates of 1.5- to 3.7-mm/yr; this compaction accounts for more than half of observed land subsidence in the region. Glacial isostatic adjustment, or the flexing of the Earth’s crust in response to glacier formation and melting, also likely contributes to land subsidence in the region.

78 FR 3882 - U.S. Integrated Ocean Observing System (IOOS®) Advisory Committee

Federal Register 2010, 2011, 2012, 2013, 2014

2013-01-17

... be held at the Western Management Development Center, Cherry Creek Place, 3151 S Vaughn Way, Aurora... Observation System Act, part of the Omnibus Public Land Management Act of 2009 (Pub. L. 111-11). The Committee... Committee for review and advice. The Committee will provide advice on: (a) Administration, operation...

Assimilation of spatially sparse in situ soil moisture networks into a continuous model domain

USDA-ARS?s Scientific Manuscript database

Growth in the availability of near-real-time soil moisture observations from ground-based networks has spurred interest in the assimilation of these observations into land surface models via a two-dimensional data assimilation system. However, the design of such systems is currently hampered by our ...

Linking Land Use Changes to Surface Water Quality Variability in Lake Victoria: Some Insights From Remote Sensing (GC41B-1101)

NASA Technical Reports Server (NTRS)

Limaye, Ashutosh; Mugo, Robinson; Wanjohi, James; Farah, Hussein; Wahome, Anastasia; Flores, Africa; Irwin, Dan

2016-01-01

Various land use changes driven by urbanization, conversion of grasslands and woodlands into farmlands, intensification of agricultural practices, deforestation, land fragmentation and degradation are taking place in Africa. In Kenya, agriculture is the main driver of land use conversions. The impacts of these land use changes are observable in land cover maps, and eventually in the hydrological systems. Reduction or change of natural vegetation cover types increases the speed of surface runoff and reduces water and nutrient retention capacities. This can lead to high nutrient inputs into lakes, resulting in eutrophication, siltation and infestation of floating aquatic vegetation. To assess if changes in land use could be contributing to increased phytoplankton blooms and sediment loads into Lake Victoria, we analyzed land use land cover data from Landsat, as well as surface chlorophyll-a and total suspended matter from MODIS-Aqua sensor.

Comparison of Land Skin Temperature from a Land Model, Remote Sensing, and In-situ Measurement

NASA Technical Reports Server (NTRS)

Wang, Aihui; Barlage, Michael; Zeng, Xubin; Draper, Clara Sophie

2014-01-01

Land skin temperature (Ts) is an important parameter in the energy exchange between the land surface and atmosphere. Here hourly Ts from the Community Land Model Version 4.0, MODIS satellite observations, and in-situ observations in 2003 were compared. Compared with the in-situ observations over four semi-arid stations, both MODIS and modeled Ts show negative biases, but MODIS shows an overall better performance. Global distribution of differences between MODIS and modeled Ts shows diurnal, seasonal, and spatial variations. Over sparsely vegetated areas, the model Ts is generally lower than the MODIS observed Ts during the daytime, while the situation is opposite at nighttime. The revision of roughness length for heat and the constraint of minimum friction velocity from Zeng et al. [2012] bring the modeled Ts closer to MODIS during the day, and have little effect on Ts at night. Five factors contributing to the Ts differences between the model and MODIS are identified, including the difficulty in properly accounting for cloud cover information at the appropriate temporal and spatial resolutions, and uncertainties in surface energy balance computation, atmospheric forcing data, surface emissivity, and MODIS Ts data. These findings have implications for the cross-evaluation of modeled and remotely sensed Ts, as well as the data assimilation of Ts observations into Earth system models.

Navy Supplement to the DOD Dictionary of Military and Associated Terms

DTIC Science & Technology

2011-04-01

light harpoon landing restraint system LI interference level LI/ LO lock-in/lock-out LIA laser illuminator assembly LIC low-intensity conflict lidar...monitoring system LMSR large, medium-speed roll-on/roll-off (ship) LN legalman (USN rating) LND land LNO liaison officer LO locked open; low...observable; lubricating oil fill, transfer and purification LO /LI lock-out/lock-in LO / LO lift-on/lift-off LOA letter of approval; letter of authorization

Verification of land-atmosphere coupling in forecast models, reanalyses and land surface models using flux site observations.

PubMed

Dirmeyer, Paul A; Chen, Liang; Wu, Jiexia; Shin, Chul-Su; Huang, Bohua; Cash, Benjamin A; Bosilovich, Michael G; Mahanama, Sarith; Koster, Randal D; Santanello, Joseph A; Ek, Michael B; Balsamo, Gianpaolo; Dutra, Emanuel; Lawrence, D M

2018-02-01

We confront four model systems in three configurations (LSM, LSM+GCM, and reanalysis) with global flux tower observations to validate states, surface fluxes, and coupling indices between land and atmosphere. Models clearly under-represent the feedback of surface fluxes on boundary layer properties (the atmospheric leg of land-atmosphere coupling), and may over-represent the connection between soil moisture and surface fluxes (the terrestrial leg). Models generally under-represent spatial and temporal variability relative to observations, which is at least partially an artifact of the differences in spatial scale between model grid boxes and flux tower footprints. All models bias high in near-surface humidity and downward shortwave radiation, struggle to represent precipitation accurately, and show serious problems in reproducing surface albedos. These errors create challenges for models to partition surface energy properly and errors are traceable through the surface energy and water cycles. The spatial distribution of the amplitude and phase of annual cycles (first harmonic) are generally well reproduced, but the biases in means tend to reflect in these amplitudes. Interannual variability is also a challenge for models to reproduce. Our analysis illuminates targets for coupled land-atmosphere model development, as well as the value of long-term globally-distributed observational monitoring.

Using Dynamic Time Warping and Data Forensics to Examine Tradeoffs among Land-Energy-Water Networks Across the Conterminous United States

NASA Astrophysics Data System (ADS)

McManamay, R.; Allen, M. R.; Piburn, J.; Sanyal, J.; Stewart, R.; Bhaduri, B. L.

2017-12-01

Characterizing interdependencies among land-energy-water sectors, their vulnerabilities, and tipping points, is challenging, especially if all sectors are simultaneously considered. Because such holistic system behavior is uncertain, largely unmodeled, and in need of testable hypotheses of system drivers, these dynamics are conducive to exploratory analytics of spatiotemporal patterns, powered by tools, such as Dynamic Time Warping (DTW). Here, we conduct a retrospective analysis (1950 - 2010) of temporal trends in land use, energy use, and water use within US counties to identify commonalities in resource consumption and adaptation strategies to resource limitations. We combine existing and derived data from statistical downscaling to synthesize a temporally comprehensive land-energy-water dataset at the US county level and apply DTW and subsequent hierarchical clustering to examine similar temporal trends in resource typologies for land, energy, and water sectors. As expected, we observed tradeoffs among water uses (e.g., public supply vs irrigation) and land uses (e.g., urban vs ag). Strong associations between clusters amongst sectors reveal tight system interdependencies, whereas weak associations suggest unique behaviors and potential for human adaptations towards disruptive technologies and less resource-dependent population growth. Our framework is useful for exploring complex human-environmental system dynamics and generating hypotheses to guide subsequent energy-water-nexus research.

Satellite and earth science data management activities at the U.S. geological survey's EROS data center

USGS Publications Warehouse

Carneggie, David M.; Metz, Gary G.; Draeger, William C.; Thompson, Ralph J.

1991-01-01

The U.S. Geological Survey's Earth Resources Observation Systems (EROS) Data Center, the national archive for Landsat data, has 20 years of experience in acquiring, archiving, processing, and distributing Landsat and earth science data. The Center is expanding its satellite and earth science data management activities to support the U.S. Global Change Research Program and the National Aeronautics and Space Administration (NASA) Earth Observing System Program. The Center's current and future data management activities focus on land data and include: satellite and earth science data set acquisition, development and archiving; data set preservation, maintenance and conversion to more durable and accessible archive medium; development of an advanced Land Data Information System; development of enhanced data packaging and distribution mechanisms; and data processing, reprocessing, and product generation systems.

Understanding our Changing Planet: NASA's Earth Science Enterprise

NASA Technical Reports Server (NTRS)

Forehand, Lon; Griner, Charlotte (Editor); Greenstone, Renny (Editor)

1999-01-01

NASA has been studying the Earth and its changing environment by observing the atmosphere, oceans, land, ice, and snow and their influence on climate and weather since the agency's creation. This study has lead to a new approach to understanding the interaction of the Earth's systems, Earth System Science. The Earth Science Enterprise, NASA's comprehensive program for Earth System Science, uses satellites and other tools to intensively study the Earth. The Earth Science Enterprise has three main components: (1) a series of Earth-observing satellites, (2) an advanced data system and (3) teams of scientist who study the data. Key areas of study include: (1) clouds, (2) water and energy cycles, (3) oceans, (4) chemistry of the atmosphere, (5) land surface, water and ecosystems processes; (6) glaciers and polar ice sheets, and (7) the solid earth.

Uncertainty quantification of surface-water/groundwater exchange estimates in large wetland systems using Python

NASA Astrophysics Data System (ADS)

Hughes, J. D.; Metz, P. A.

2014-12-01

Most watershed studies include observation-based water budget analyses to develop first-order estimates of significant flow terms. Surface-water/groundwater (SWGW) exchange is typically assumed to be equal to the residual of the sum of inflows and outflows in a watershed. These estimates of SWGW exchange, however, are highly uncertain as a result of the propagation of uncertainty inherent in the calculation or processing of the other terms of the water budget, such as stage-area-volume relations, and uncertainties associated with land-cover based evapotranspiration (ET) rate estimates. Furthermore, the uncertainty of estimated SWGW exchanges can be magnified in large wetland systems that transition from dry to wet during wet periods. Although it is well understood that observation-based estimates of SWGW exchange are uncertain it is uncommon for the uncertainty of these estimates to be directly quantified. High-level programming languages like Python can greatly reduce the effort required to (1) quantify the uncertainty of estimated SWGW exchange in large wetland systems and (2) evaluate how different approaches for partitioning land-cover data in a watershed may affect the water-budget uncertainty. We have used Python with the Numpy, Scipy.stats, and pyDOE packages to implement an unconstrained Monte Carlo approach with Latin Hypercube sampling to quantify the uncertainty of monthly estimates of SWGW exchange in the Floral City watershed of the Tsala Apopka wetland system in west-central Florida, USA. Possible sources of uncertainty in the water budget analysis include rainfall, ET, canal discharge, and land/bathymetric surface elevations. Each of these input variables was assigned a probability distribution based on observation error or spanning the range of probable values. The Monte Carlo integration process exposes the uncertainties in land-cover based ET rate estimates as the dominant contributor to the uncertainty in SWGW exchange estimates. We will discuss the uncertainty of SWGW exchange estimates using an ET model that partitions the watershed into open water and wetland land-cover types. We will also discuss the uncertainty of SWGW exchange estimates calculated using ET models partitioned into additional land-cover types.

Models meet data: Challenges and opportunities in implementing land management in Earth system models.

PubMed

Pongratz, Julia; Dolman, Han; Don, Axel; Erb, Karl-Heinz; Fuchs, Richard; Herold, Martin; Jones, Chris; Kuemmerle, Tobias; Luyssaert, Sebastiaan; Meyfroidt, Patrick; Naudts, Kim

2018-04-01

As the applications of Earth system models (ESMs) move from general climate projections toward questions of mitigation and adaptation, the inclusion of land management practices in these models becomes crucial. We carried out a survey among modeling groups to show an evolution from models able only to deal with land-cover change to more sophisticated approaches that allow also for the partial integration of land management changes. For the longer term a comprehensive land management representation can be anticipated for all major models. To guide the prioritization of implementation, we evaluate ten land management practices-forestry harvest, tree species selection, grazing and mowing harvest, crop harvest, crop species selection, irrigation, wetland drainage, fertilization, tillage, and fire-for (1) their importance on the Earth system, (2) the possibility of implementing them in state-of-the-art ESMs, and (3) availability of required input data. Matching these criteria, we identify "low-hanging fruits" for the inclusion in ESMs, such as basic implementations of crop and forestry harvest and fertilization. We also identify research requirements for specific communities to address the remaining land management practices. Data availability severely hampers modeling the most extensive land management practice, grazing and mowing harvest, and is a limiting factor for a comprehensive implementation of most other practices. Inadequate process understanding hampers even a basic assessment of crop species selection and tillage effects. The need for multiple advanced model structures will be the challenge for a comprehensive implementation of most practices but considerable synergy can be gained using the same structures for different practices. A continuous and closer collaboration of the modeling, Earth observation, and land system science communities is thus required to achieve the inclusion of land management in ESMs. © 2017 John Wiley & Sons Ltd.

LDAS-Monde: Global scale satellite driven Land Data Assimilation System based on SURFEX modelling platform

NASA Astrophysics Data System (ADS)

Munier, Simon; Albergel, Clément; Leroux, Delphine; Calvet, Jean-Christophe

2017-04-01

In the past decades, large efforts have been made to improve our understanding of the dynamics of the terrestrial water cycle, including vertical and horizontal water fluxes as well as water stored in the biosphere. The soil water content is closely related to the development of the vegetation, which is in turn closely related to the water and energy exchanges with the atmosphere (through evapotranspiration) as well as to carbon fluxes. Land Surface Models (LSMs) are usually designed to represent biogeophysical variables, such as Surface and Root Zone Soil Moisture (SSM, RZSM) or Leaf Area Index (LAI), in order to simulate water, energy and carbon fluxes at the interface between land and atmosphere. With the recent increase of satellite missions and derived products, LSMs can benefit from Earth Observations via Data Assimilation systems to improve their representation of different biogeophysical variables. This study, which is part of the eartH2Observe European project (http://www.earth2observe.eu), presents LDAS-Monde, a global Land Data Assimilation System using an implementation of the Simplified Extended Kalman Filter (SEKF) in the Météo-France's modelling platform (SURFEX). SURFEX is based on the coupling of the multilayer, CO2-responsive version of the Interactions Between Soil, Biosphere, and Atmosphere model (ISBA) coupled with Météo-France's version of the Total Runoff Integrating Pathways continental hydrological system (CTRIP). Two global operational datasets derived from satellite observations are assimilated simultaneously: (i) SSM from the ESA Climate Change Initiative and (ii) LAI from the Copernicus Global Land Service project. Atmospheric forcing used in SURFEX are derived from the ERA-Interim reanalysis and corrected from GPCC precipitations. The simulations are conducted at the global scale at a 1 degree spatial resolution over the period 2000-2014. An analysis of the model sensitivity to the assimilated observations is performed over different regions of the globe under various hydro-climatic conditions. The impact of the SEKF on different biogeophysical and hydrological variables is assessed. It is shown that the assimilation scheme greatly improves the representation of the observed variables (SSM and LAI) and that it effectively affects most of the other variables related to the terrestrial water and vegetation cycles. Future developments include the optimization of LDAS-Monde in order to improve the spatial resolution and then take full advantage of the potential of Earth Observations.

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.

A Multimodel Global Drought Information System (GDIS) for Near Real-Time Monitoring of Surface Water Conditions (Invited)

NASA Astrophysics Data System (ADS)

Nijssen, B.

2013-12-01

While the absolute magnitude of economic losses associated with weather and climate disasters such as droughts is greatest in the developed world, the relative impact is much larger in the developing world, where agriculture typically constitutes a much larger percentage of the labor force and food insecurity is a major concern. Nonetheless, our ability to monitor and predict the development and occurrence of droughts at a global scale in near real-time is limited and long-term records of soil moisture are essentially non-existent globally The problem is particularly critical given that many of the most damaging droughts occur in parts of the world that are most deficient in terms of in situ precipitation observations. In recent years, a number of near real-time drought monitoring systems have been developed with regional or global extent. While direct observations of key variables such as moisture storage are missing, the evolution of land surface models that are globally applicable provides a means of reconstructing them. The implementation of a multi-model drought monitoring system is described, which provides near real-time estimates of surface moisture storage for the global land areas between 50S and 50N with a time lag of about one day. Near real-time forcings are derived from satellite-based precipitation estimates and modeled air temperatures. The system is distinguished from other operational systems in that it uses multiple land surface models to simulate surface moisture storage, which are then combined to derive a multi-model estimate of drought. Previous work has shown that while land surface models agree in broad context, particularly in terms of soil moisture percentiles, important differences remain, which motivates a multi-model ensemble approach. The system is an extension of similar systems developed by at the University of Washington for the Pacific Northwest and for the United States, but global application of the protocols used in the U.S. systems poses new challenges, particularly with respect to the generation of meteorological forcings that drive the land surface models. Agricultural and hydrological droughts are inherently defined in the context of a long-term climatology. Changes in observing platforms can be misinterpreted as droughts (or as excessively wet periods). This problem cannot simply be addressed through the addition of more observations or through the development of new observing platforms. Instead, it will require careful (re)construction of long-term records that are updated in near real-time in a consistent manner so that changes in surface meteorological forcings reflect actual conditions rather than changes in methods or sources.

Improving wind energy forecasts using an Ensemble Kalman Filter data assimilation technique in a fully coupled hydrologic and atmospheric model

NASA Astrophysics Data System (ADS)

Williams, J. L.; Maxwell, R. M.; Delle Monache, L.

2012-12-01

Wind power is rapidly gaining prominence as a major source of renewable energy. Harnessing this promising energy source is challenging because of the chaotic nature of wind and its propensity to change speed and direction over short time scales. Accurate forecasting tools are critical to support the integration of wind energy into power grids and to maximize its impact on renewable energy portfolios. Numerous studies have shown that soil moisture distribution and land surface vegetative processes profoundly influence atmospheric boundary layer development and weather processes on local and regional scales. Using the PF.WRF model, a fully-coupled hydrologic and atmospheric model employing the ParFlow hydrologic model with the Weather Research and Forecasting model coupled via mass and energy fluxes across the land surface, we have explored the connections between the land surface and the atmosphere in terms of land surface energy flux partitioning and coupled variable fields including hydraulic conductivity, soil moisture and wind speed, and demonstrated that reductions in uncertainty in these coupled fields propagate through the hydrologic and atmospheric system. We have adapted the Data Assimilation Research Testbed (DART), an implementation of the robust Ensemble Kalman Filter data assimilation algorithm, to expand our capability to nudge forecasts produced with the PF.WRF model using observational data. Using a semi-idealized simulation domain, we examine the effects of assimilating observations of variables such as wind speed and temperature collected in the atmosphere, and land surface and subsurface observations such as soil moisture on the quality of forecast outputs. The sensitivities we find in this study will enable further studies to optimize observation collection to maximize the utility of the PF.WRF-DART forecasting system.

LandSense: A Citizen Observatory and Innovation Marketplace for Land Use and Land Cover Monitoring

NASA Astrophysics Data System (ADS)

Moorthy, Inian; Fritz, Steffen; See, Linda; McCallum, Ian

2017-04-01

Currently within the EU's Earth Observation (EO) monitoring framework, there is a need for low-cost methods for acquiring high quality in-situ data to create accurate and well-validated environmental monitoring products. To help address this need, a new four year Horizon 2020 project entitled LandSense will link remote sensing data with modern participatory data collection methods that involve citizen scientists. This paper will describe the citizen science activities within the LandSense Observatory that aim to deliver concrete, measurable and quality-assured ground-based data that will complement existing satellite monitoring systems. LandSense will deploy advanced tools, services and resources to mobilize and engage citizens to collect in-situ observations (i.e. ground-based data and visual interpretations of EO imagery). Integrating these citizen-driven in-situ data collections with established authoritative and open access data sources will help reduce costs, extend GEOSS and Copernicus capacities, and support comprehensive environmental monitoring systems. Policy-relevant campaigns will be implemented in close collaboration with multiple stakeholders to ensure that citizen observations address user requirements and contribute to EU-wide environmental governance and decision-making. Campaigns for addressing local and regional Land Use and Land Cover (LULC) issues are planned for select areas in Austria, France, Germany, Spain, Slovenia and Serbia. Novel LandSense services (LandSense Campaigner, FarmLand Support, Change Detector and Quality Assurance & Control) will be deployed and tested in these areas to address critical LULC issues (i.e. urbanization, agricultural land use and forest/habitat monitoring). For example, local residents in the cities of Vienna, Tulln, and Heidelberg will help cooperatively detect and map changes in land cover and green space to address key issues of urban sprawl, land take and flooding. Such campaigns are facilitated through numerous pathways of citizen empowerment via the LandSense Engagement Platform, i.e. tools for discussion, online voting collaborative mapping, as well as events linked to public consultation and cooperative planning. In addition to creating tools for data collection, quality assurance, and interaction with the public, the project aims to drive innovation through collaboration with the private sector. LandSense will build an innovation marketplace to attract a vast community of users across numerous disciplines and sectors and boost Europe's role in the business of ground-based monitoring. The anticipated outcomes of LandSense have considerable potential to lower expenditure costs on ground-based data collection and greatly extend the current sources of such data, thereby realizing citizen-powered innovations in the processing chain of LULC monitoring activities both within and beyond Europe.

Advancements in medium and high resolution Earth observation for land-surface imaging: Evolutions, future trends and contributions to sustainable development

NASA Astrophysics Data System (ADS)

Ouma, Yashon O.

2016-01-01

Technologies for imaging the surface of the Earth, through satellite based Earth observations (EO) have enormously evolved over the past 50 years. The trends are likely to evolve further as the user community increases and their awareness and demands for EO data also increases. In this review paper, a development trend on EO imaging systems is presented with the objective of deriving the evolving patterns for the EO user community. From the review and analysis of medium-to-high resolution EO-based land-surface sensor missions, it is observed that there is a predictive pattern in the EO evolution trends such that every 10-15 years, more sophisticated EO imaging systems with application specific capabilities are seen to emerge. Such new systems, as determined in this review, are likely to comprise of agile and small payload-mass EO land surface imaging satellites with the ability for high velocity data transmission and huge volumes of spatial, spectral, temporal and radiometric resolution data. This availability of data will magnify the phenomenon of ;Big Data; in Earth observation. Because of the ;Big Data; issue, new computing and processing platforms such as telegeoprocessing and grid-computing are expected to be incorporated in EO data processing and distribution networks. In general, it is observed that the demand for EO is growing exponentially as the application and cost-benefits are being recognized in support of resource management.

A joint global carbon inversion system using both CO2 and 13CO2 atmospheric concentration data

NASA Astrophysics Data System (ADS)

Chen, Jing M.; Mo, Gang; Deng, Feng

2017-03-01

Observations of 13CO2 at 73 sites compiled in the GLOBALVIEW database are used for an additional constraint in a global atmospheric inversion of the surface CO2 flux using CO2 observations at 210 sites (62 collocated with 13CO2 sites) for the 2002-2004 period for 39 land regions and 11 ocean regions. This constraint is implemented using prior CO2 fluxes estimated with a terrestrial ecosystem model and an ocean model. These models simulate 13CO2 discrimination rates of terrestrial photosynthesis and ocean-atmosphere diffusion processes. In both models, the 13CO2 disequilibrium between fluxes to and from the atmosphere is considered due to the historical change in atmospheric 13CO2 concentration. This joint inversion system using both13CO2 and CO2 observations is effectively a double deconvolution system with consideration of the spatial variations of isotopic discrimination and disequilibrium. Compared to the CO2-only inversion, this 13CO2 constraint on the inversion considerably reduces the total land carbon sink from 3.40 ± 0.84 to 2.53 ± 0.93 Pg C year-1 but increases the total oceanic carbon sink from 1.48 ± 0.40 to 2.36 ± 0.49 Pg C year-1. This constraint also changes the spatial distribution of the carbon sink. The largest sink increase occurs in the Amazon, while the largest source increases are in southern Africa, and Asia, where CO2 data are sparse. Through a case study, in which the spatial distribution of the annual 13CO2 discrimination rate over land is ignored by treating it as a constant at the global average of -14. 1 ‰, the spatial distribution of the inverted CO2 flux over land was found to be significantly modified (up to 15 % for some regions). The uncertainties in our disequilibrium flux estimation are 8.0 and 12.7 Pg C year-1 ‰ for land and ocean, respectively. These uncertainties induced the unpredictability of 0.47 and 0.54 Pg C year-1 in the inverted CO2 fluxes for land and ocean, respectively. Our joint inversion system is therefore useful for improving the partitioning between ocean and land sinks and the spatial distribution of the inverted carbon flux.

Landsat Data Continuity Mission - Launch Fever

NASA Technical Reports Server (NTRS)

Irons, James R.; Loveland, Thomas R.; Markham, Brian L.; Masek, Jeffrey G.; Cook, Bruce; Dwyer, John L.

2012-01-01

The year 2013 will be an exciting period for those that study the Earth land surface from space, particularly those that observe and characterize land cover, land use, and the change of cover and use over time. Two new satellite observatories will be launched next year that will enhance capabilities for observing the global land surface. The United States plans to launch the Landsat Data Continuity Mission (LDCM) in January. That event will be followed later in the year by the European Space Agency (ESA) launch of the first Sentinel 2 satellite. Considered together, the two satellites will increase the frequency of opportunities for viewing the land surface at a scale where human impact and influence can be differentiated from natural change. Data from the two satellites will provide images for similar spectral bands and for comparable spatial resolutions with rigorous attention to calibration that will facilitate cross comparisons. This presentation will provide an overview of the LDCM satellite system and report its readiness for the January launch.

Land and cryosphere products from Suomi NPP VIIRS: Overview and status

PubMed Central

Justice, Christopher O; Román, Miguel O; Csiszar, Ivan; Vermote, Eric F; Wolfe, Robert E; Hook, Simon J; Friedl, Mark; Wang, Zhuosen; Schaaf, Crystal B; Miura, Tomoaki; Tschudi, Mark; Riggs, George; Hall, Dorothy K; Lyapustin, Alexei I; Devadiga, Sadashiva; Davidson, Carol; Masuoka, Edward J

2013-01-01

[1] The Visible Infrared Imaging Radiometer Suite (VIIRS) instrument was launched in October 2011 as part of the Suomi National Polar-Orbiting Partnership (S-NPP). The VIIRS instrument was designed to improve upon the capabilities of the operational Advanced Very High Resolution Radiometer and provide observation continuity with NASA’s Earth Observing System’s Moderate Resolution Imaging Spectroradiometer (MODIS). Since the VIIRS first-light images were received in November 2011, NASA- and NOAA-funded scientists have been working to evaluate the instrument performance and generate land and cryosphere products to meet the needs of the NOAA operational users and the NASA science community. NOAA’s focus has been on refining a suite of operational products known as Environmental Data Records (EDRs), which were developed according to project specifications under the National Polar-Orbiting Environmental Satellite System. The NASA S-NPP Science Team has focused on evaluating the EDRs for science use, developing and testing additional products to meet science data needs, and providing MODIS data product continuity. This paper presents to-date findings of the NASA Science Team’s evaluation of the VIIRS land and cryosphere EDRs, specifically Surface Reflectance, Land Surface Temperature, Surface Albedo, Vegetation Indices, Surface Type, Active Fires, Snow Cover, Ice Surface Temperature, and Sea Ice Characterization. The study concludes that, for MODIS data product continuity and earth system science, an enhanced suite of land and cryosphere products and associated data system capabilities are needed beyond the EDRs currently available from the VIIRS. PMID:25821661

Root traits explain observed tundra vegetation nitrogen uptake patterns: Implications for trait-based land models: Tundra N Uptake Model-Data Comparison

DOE PAGES

Zhu, Qing; Iversen, Colleen M.; Riley, William J.; ...

2016-12-23

Ongoing climate warming will likely perturb vertical distributions of nitrogen availability in tundra soils through enhancing nitrogen mineralization and releasing previously inaccessible nitrogen from frozen permafrost soil. But, arctic tundra responses to such changes are uncertain, because of a lack of vertically explicit nitrogen tracer experiments and untested hypotheses of root nitrogen uptake under the stress of microbial competition implemented in land models. We conducted a vertically explicit 15N tracer experiment for three dominant tundra species to quantify plant N uptake profiles. Then we applied a nutrient competition model (N-COM), which is being integrated into the ACME Land Model, tomore » explain the observations. Observations using an 15N tracer showed that plant N uptake profiles were not consistently related to root biomass density profiles, which challenges the prevailing hypothesis that root density always exerts first-order control on N uptake. By considering essential root traits (e.g., biomass distribution and nutrient uptake kinetics) with an appropriate plant-microbe nutrient competition framework, our model reasonably reproduced the observed patterns of plant N uptake. Additionally, we show that previously applied nutrient competition hypotheses in Earth System Land Models fail to explain the diverse plant N uptake profiles we observed. These results cast doubt on current climate-scale model predictions of arctic plant responses to elevated nitrogen supply under a changing climate and highlight the importance of considering essential root traits in large-scale land models. Finally, we provided suggestions and a short synthesis of data availability for future trait-based land model development.« less

Decoding the origins of vertical land motions observed today at coasts

NASA Astrophysics Data System (ADS)

Pfeffer, J.; Spada, G.; Mémin, A.; Boy, J.-P.; Allemand, P.

2017-07-01

In recent decades, geodetic techniques have allowed detecting vertical land motions and sea-level changes of a few millimetres per year, based on measurements taken at the coast (tide gauges), on board of satellite platforms (satellite altimetry) or both (Global Navigation Satellite System). Here, contemporary vertical land motions are analysed from January 1993 to July 2013 at 849 globally distributed coastal sites. The vertical displacement of the coastal platform due to surface mass changes is modelled using elastic and viscoelastic Green's functions. Special attention is paid to the effects of glacial isostatic adjustment induced by past and present-day ice melting. Various rheological and loading parameters are explored to provide a set of scenarios that could explain the coastal observations of vertical land motions globally. In well-instrumented regions, predicted vertical land motions explain more than 80 per cent of the variance observed at scales larger than a few hundred kilometres. Residual vertical land motions show a strong local variability, especially in the vicinity of plate boundaries due to the earthquake cycle. Significant residual signals are also observed at scales of a few hundred kilometres over nine well-instrumented regions forming observation windows on unmodelled geophysical processes. This study highlights the potential of our multitechnique database to detect geodynamical processes, driven by anthropogenic influence, surface mass changes (surface loading and glacial isostatic adjustment) and tectonic activity (including the earthquake cycle, sediment and volcanic loading, as well as regional tectonic constraints). Future improvements should be aimed at densifying the instrumental network and at investigating more thoroughly the uncertainties associated with glacial isostatic adjustment models.

Root traits explain observed tundra vegetation nitrogen uptake patterns: Implications for trait-based land models: Tundra N Uptake Model-Data Comparison

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

Zhu, Qing; Iversen, Colleen M.; Riley, William J.

Ongoing climate warming will likely perturb vertical distributions of nitrogen availability in tundra soils through enhancing nitrogen mineralization and releasing previously inaccessible nitrogen from frozen permafrost soil. But, arctic tundra responses to such changes are uncertain, because of a lack of vertically explicit nitrogen tracer experiments and untested hypotheses of root nitrogen uptake under the stress of microbial competition implemented in land models. We conducted a vertically explicit 15N tracer experiment for three dominant tundra species to quantify plant N uptake profiles. Then we applied a nutrient competition model (N-COM), which is being integrated into the ACME Land Model, tomore » explain the observations. Observations using an 15N tracer showed that plant N uptake profiles were not consistently related to root biomass density profiles, which challenges the prevailing hypothesis that root density always exerts first-order control on N uptake. By considering essential root traits (e.g., biomass distribution and nutrient uptake kinetics) with an appropriate plant-microbe nutrient competition framework, our model reasonably reproduced the observed patterns of plant N uptake. Additionally, we show that previously applied nutrient competition hypotheses in Earth System Land Models fail to explain the diverse plant N uptake profiles we observed. These results cast doubt on current climate-scale model predictions of arctic plant responses to elevated nitrogen supply under a changing climate and highlight the importance of considering essential root traits in large-scale land models. Finally, we provided suggestions and a short synthesis of data availability for future trait-based land model development.« less

New and Improved GLDAS and NLDAS Data Sets and Data Services at HDISC/NASA

NASA Technical Reports Server (NTRS)

Rui, Hualan; Beaudoing, Hiroko Kato; Mocko, David M.; Rodell, Matthew; Teng, William L.; Vollmer. Bruce

2010-01-01

Terrestrial hydrological variables are important in global hydrology, climate, and carbon cycle studies. Generating global fields of these variables, however, is still a challenge. The goal of a land data assimilation system (LDAS)is to ingest satellite-and ground-based observational data products, using advanced land surface modeling and data assimilation techniques, in order to generate optimal fields of land surface states and fluxes data and, thereby, facilitate hydrology and climate modeling, research, and forecast.

Remote Sensing of Aerosol Over the Land from the Earth Observing System MODIS Instrument

NASA Technical Reports Server (NTRS)

Kaufman, Yoram; Tanre, Didier; Remer, Lorraine; Einaudi, Franco (Technical Monitor)

2000-01-01

On Dec 18, 1999, NASA launched the Moderate-Resolution Imaging Spectroradiometer (MODIS) instrument on the Earth Observing System (EOS) Terra mission, in a spectacular launch. The mission will provide morning (10:30 AM) global observations of aerosol and other related parameters. It will be followed a year later by a MODIS instrument on EOS Aqua for afternoon observations (1:30 PM). MODIS will measure aerosol over land and ocean with its eight 500 m and 250 m channels in the solar spectrum (0-41 to 2.2 micrometers). Over the land MODIS will measure the total column aerosol loading, and distinguish between submicron pollution particles and large soil particles. Standard daily products of resolution of ten kilometers and global mapped eight day and monthly products on a 1x1 degree global scale will be produced routinely and make available for no or small reproduction charge to the international community. Though the aerosol products will not be available everywhere over the land, it is expected that they will be useful for assessments of the presence, sources and transport of urban pollution, biomass burning aerosol, and desert dust. Other measurements from MODIS will supplement the aerosol information, e.g., land use change, urbanization, presence and magnitude of biomass burning fires, and effect of aerosol on cloud microphysics. Other instruments on Terra, e.g. Multi-angle Imaging SpectroRadiometer (MISR) and the Clouds and the Earth's Radiant Energy System (CERES), will also measure aerosol, its properties and radiative forcing in tandem with the MODIS measurements. During the Aqua period, there are plans to launch in 2003 the Pathfinder Instruments for Cloud and Aerosol Spaceborne Observations (PICASSO) mission for global measurements of the aerosol vertical structure, and the PARASOL mission for aerosol characterization. Aqua-MODIS, PICASSO and PARASOL will fly in formation for detailed simultaneous characterization of the aerosol three-dimensional field, which will feed and evaluate global aerosol transport and climate models. In this talk, some examples of the MODIS measurements will be shown.

In-flight wind identification and soft landing control for autonomous unmanned powered parafoils

NASA Astrophysics Data System (ADS)

Luo, Shuzhen; Tan, Panlong; Sun, Qinglin; Wu, Wannan; Luo, Haowen; Chen, Zengqiang

2018-04-01

For autonomous unmanned powered parafoil, the ability to perform a final flare manoeuvre against the wind direction can allow a considerable reduction of horizontal and vertical velocities at impact, enabling a soft landing for a safe delivery of sensible loads; the lack of knowledge about the surface-layer winds will result in messing up terminal flare manoeuvre. Moreover, unknown or erroneous winds can also prevent the parafoil system from reaching the target area. To realize accurate trajectory tracking and terminal soft landing in the unknown wind environment, an efficient in-flight wind identification method merely using Global Positioning System (GPS) data and recursive least square method is proposed to online identify the variable wind information. Furthermore, a novel linear extended state observation filter is proposed to filter the groundspeed of the powered parafoil system calculated by the GPS information to provide a best estimation of the present wind during flight. Simulation experiments and real airdrop tests demonstrate the great ability of this method to in-flight identify the variable wind field, and it can benefit the powered parafoil system to fulfil accurate tracking control and a soft landing in the unknown wind field with high landing accuracy and strong wind-resistance ability.

Sensitivity of summer climate to anthropogenic land-cover change over the Greater Phoenix, AZ, region

USGS Publications Warehouse

Georgescu, M.; Miguez-Macho, G.; Steyaert, L.T.; Weaver, C.P.

2008-01-01

This work evaluates the first-order effect of land-use/land-cover change (LULCC) on the summer climate of one of the nation's most rapidly expanding metropolitan complexes, the Greater Phoenix, AZ, region. High-resolution-2-km grid spacing-Regional Atmospheric Modeling System (RAMS) simulations of three "wet" and three "dry" summers were carried out for two different land-cover reconstructions for the region: a circa 1992 representation based on satellite observations, and a hypothetical land-cover scenario where the anthropogenic landscape of irrigated agriculture and urban pixels was replaced with current semi-natural vegetation. Model output is evaluated with respect to observed air temperature, dew point, and precipitation. Our results suggest that development of extensive irrigated agriculture adjacent to the urban area has dampened any regional-mean warming due to urbanization. Consistent with previous observationally based work, LULCC produces a systematic increase in precipitation to the north and east of the city, though only under dry conditions. This is due to a change in background atmospheric stability resulting from the advection of both warmth from the urban core and moisture from the irrigated area. ?? 2008 Elsevier Ltd. All rights reserved.

GLOBE Observer: Earth Science in the Palm of Your Hand

NASA Astrophysics Data System (ADS)

Weaver, K. L. K.; Riebeek Kohl, H.

2017-12-01

You can get involved in doing Earth system science research tied to NASA research and data. This demo will introduce GLOBE and GLOBE Observer, a student and citizen science program designed to collect observations of the environment. The GLOBE Observer app, released in September 2016, harnesses smart phone technology to simplify select GLOBE observations to open the program to new audiences and to increase data volume. The end goal is to facilitate new student and scientific research. The demo will provide an overview of the app and show you how to access GLOBE Observer environmental data. The app includes a protocol for observing clouds and sky color (air quality proxy), mosquito habitats, and land cover/land use. The GLOBE Observer observations may be matched to NASA satellite data for a more in-depth analysis.

Canopies to Continents: What spatial scales are needed to represent landcover distributions in earth system models?

NASA Astrophysics Data System (ADS)

Guenther, A. B.; Duhl, T.

2011-12-01

Increasing computational resources have enabled a steady improvement in the spatial resolution used for earth system models. Land surface models and landcover distributions have kept ahead by providing higher spatial resolution than typically used in these models. Satellite observations have played a major role in providing high resolution landcover distributions over large regions or the entire earth surface but ground observations are needed to calibrate these data and provide accurate inputs for models. As our ability to resolve individual landscape components improves, it is important to consider what scale is sufficient for providing inputs to earth system models. The required spatial scale is dependent on the processes being represented and the scientific questions being addressed. This presentation will describe the development a contiguous U.S. landcover database using high resolution imagery (1 to 1000 meters) and surface observations of species composition and other landcover characteristics. The database includes plant functional types and species composition and is suitable for driving land surface models (CLM and MEGAN) that predict land surface exchange of carbon, water, energy and biogenic reactive gases (e.g., isoprene, sesquiterpenes, and NO). We investigate the sensitivity of model results to landcover distributions with spatial scales ranging over six orders of magnitude (1 meter to 1000000 meters). The implications for predictions of regional climate and air quality will be discussed along with recommendations for regional and global earth system modeling.

Land mobile satellite propagation results

NASA Technical Reports Server (NTRS)

Nicholas, David C.

1988-01-01

During the Fall of 1987 a land mobile satellite demonstration using the MARECS B2 satellite at 26 degrees W was performed. While all the data have not been digested, some observations are in order. First, the system worked remarkably well for the margins indicated. Second, when the system worked poorly, the experimenters could almost always identify terrain or other obstacles causing blockage. Third, the forward link seems relatively more reliable than the return link, and occasional return link problems occured which have not been entirely explained.

Estimating Snow Water Storage in North America Using CLM4, DART, and Snow Radiance Data Assimilation

NASA Technical Reports Server (NTRS)

Kwon, Yonghwan; Yang, Zong-Liang; Zhao, Long; Hoar, Timothy J.; Toure, Ally M.; Rodell, Matthew

2016-01-01

This paper addresses continental-scale snow estimates in North America using a recently developed snow radiance assimilation (RA) system. A series of RA experiments with the ensemble adjustment Kalman filter are conducted by assimilating the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) brightness temperature T(sub B) at 18.7- and 36.5-GHz vertical polarization channels. The overall RA performance in estimating snow depth for North America is improved by simultaneously updating the Community Land Model, version 4 (CLM4), snow/soil states and radiative transfer model (RTM) parameters involved in predicting T(sub B) based on their correlations with the prior T(sub B) (i.e., rule-based RA), although degradations are also observed. The RA system exhibits a more mixed performance for snow cover fraction estimates. Compared to the open-loop run (0.171m RMSE), the overall snow depth estimates are improved by 1.6% (0.168m RMSE) in the rule-based RA whereas the default RA (without a rule) results in a degradation of 3.6% (0.177mRMSE). Significant improvement of the snow depth estimates in the rule-based RA as observed for tundra snow class (11.5%, p < 0.05) and bare soil land-cover type (13.5%, p < 0.05). However, the overall improvement is not significant (p = 0.135) because snow estimates are degraded or marginally improved for other snow classes and land covers, especially the taiga snow class and forest land cover (7.1% and 7.3% degradations, respectively). The current RA system needs to be further refined to enhance snow estimates for various snow types and forested regions.

Vision-Aided RAIM: A New Method for GPS Integrity Monitoring in Approach and Landing Phase

PubMed Central

Fu, Li; Zhang, Jun; Li, Rui; Cao, Xianbin; Wang, Jinling

2015-01-01

In the 1980s, Global Positioning System (GPS) receiver autonomous integrity monitoring (RAIM) was proposed to provide the integrity of a navigation system by checking the consistency of GPS measurements. However, during the approach and landing phase of a flight path, where there is often low GPS visibility conditions, the performance of the existing RAIM method may not meet the stringent aviation requirements for availability and integrity due to insufficient observations. To solve this problem, a new RAIM method, named vision-aided RAIM (VA-RAIM), is proposed for GPS integrity monitoring in the approach and landing phase. By introducing landmarks as pseudo-satellites, the VA-RAIM enriches the navigation observations to improve the performance of RAIM. In the method, a computer vision system photographs and matches these landmarks to obtain additional measurements for navigation. Nevertheless, the challenging issue is that such additional measurements may suffer from vision errors. To ensure the reliability of the vision measurements, a GPS-based calibration algorithm is presented to reduce the time-invariant part of the vision errors. Then, the calibrated vision measurements are integrated with the GPS observations for integrity monitoring. Simulation results show that the VA-RAIM outperforms the conventional RAIM with a higher level of availability and fault detection rate. PMID:26378533

Vision-Aided RAIM: A New Method for GPS Integrity Monitoring in Approach and Landing Phase.

PubMed

Fu, Li; Zhang, Jun; Li, Rui; Cao, Xianbin; Wang, Jinling

2015-09-10

In the 1980s, Global Positioning System (GPS) receiver autonomous integrity monitoring (RAIM) was proposed to provide the integrity of a navigation system by checking the consistency of GPS measurements. However, during the approach and landing phase of a flight path, where there is often low GPS visibility conditions, the performance of the existing RAIM method may not meet the stringent aviation requirements for availability and integrity due to insufficient observations. To solve this problem, a new RAIM method, named vision-aided RAIM (VA-RAIM), is proposed for GPS integrity monitoring in the approach and landing phase. By introducing landmarks as pseudo-satellites, the VA-RAIM enriches the navigation observations to improve the performance of RAIM. In the method, a computer vision system photographs and matches these landmarks to obtain additional measurements for navigation. Nevertheless, the challenging issue is that such additional measurements may suffer from vision errors. To ensure the reliability of the vision measurements, a GPS-based calibration algorithm is presented to reduce the time-invariant part of the vision errors. Then, the calibrated vision measurements are integrated with the GPS observations for integrity monitoring. Simulation results show that the VA-RAIM outperforms the conventional RAIM with a higher level of availability and fault detection rate.

Estimating surface fluxes over middle and upper streams of the Heihe River Basin with ASTER imagery

NASA Astrophysics Data System (ADS)

Ma, W.; Ma, Y.; Hu, Z.; Su, B.; Wang, J.; Ishikawa, H.

2009-06-01

Surface fluxes are important boundary conditions for climatological modeling and the Asian monsoon system. Recent availability of high-resolution, multi-band imagery from the ASTER (Advanced Space-borne Thermal Emission and Reflection Radiometer) sensor has enabled us to estimate surface fluxes to bridge the gap between local scale flux measurements using micrometeorological instruments and regional scale land-atmosphere exchanges of water and heat fluxes that are fundamental for the understanding of the water cycle in the Asian monsoon system. A Surface Energy Balance System (SEBS) method based on ASTER data and field observations has been proposed and tested for deriving net radiation flux (Rn), soil heat flux (G0), sensible heat flux (H) and latent heat flux (λ E) over heterogeneous land surface in this paper. As a case study, the methodology was applied to the experimental area of the WATER (Watershed Allied Telemetry Experimental Research), located at the mid-to-upstream sections of the Heihe River, northwest China. The ASTER data of 3 May and 4 June in 2008 was used in this paper for the case of mid-to-upstream sections of the Heihe River Basin. To validate the proposed methodology, the ground-measured land surface heat fluxes (net radiation flux (Rn), soil heat flux (G0), sensible heat flux (H) and latent heat flux (λ E)) were compared to the ASTER derived values. The results show that the derived surface variables and land surface heat fluxes in different months over the study area are in good accordance with the land surface status. It is therefore concluded that the proposed methodology is successful for the retrieval of land surface heat fluxes using the ASTER data and filed observation over the study area.

Monitoring the Global Soil Moisture Climatology Using GLDAS/LIS

NASA Astrophysics Data System (ADS)

Meng, J.; Mitchell, K.; Wei, H.; Gottschalck, J.

2006-05-01

Soil moisture plays a crucial role in the terrestrial water cycle through governing the process of partitioning precipitation among infiltration, runoff and evaporation. Accurate assessment of soil moisture and other land states, namely, soil temperature, snowpack, and vegetation, is critical in numerical environmental prediction systems because of their regulation of surface water and energy fluxes between the surface and atmosphere over a variety of spatial and temporal scales. The Global Land Data Assimilation System (GLDAS) is developed, jointly by NASA Goddard Space Flight Center (GSFC) and NOAA National Centers for Environmental Prediction (NCEP), to perform high-quality global land surface simulation using state-of-art land surface models and further minimizing the errors of simulation by constraining the models with observation- based precipitation, and satellite land data assimilation techniques. The GLDAS-based Land Information System (LIS) infrastructure has been installed on the NCEP supercomputer that serves the operational weather and climate prediction systems. In this experiment, the Noah land surface model is offline executed within the GLDAS/LIS infrastructure, driven by the NCEP Global Reanalysis-2 (GR2) and the CPC Merged Analysis of Precipitation (CMAP). We use the same Noah code that is coupled to the operational NCEP Global Forecast System (GFS) for weather prediction and test bed versions of the NCEP Climate Forecast System (CFS) for seasonal prediction. For assessment, it is crucial that this uncoupled GLDAS/Noah uses exactly the same Noah code (and soil and vegetation parameters therein), and executes with the same horizontal grid, landmask, terrain field, soil and vegetation types, seasonal cycle of green vegetation fraction and surface albedo as in the coupled GFS/Noah and CFS/Noah. This execution is for the 25-year period of 1980-2005, starting with a pre-execution 10-year spin-up. This 25-year GLDAS/Noah global land climatology will be used for both climate variability assessment and as a source of land initial conditions for ensemble CFS/Noah seasonal hindcast experiments. Finally, this GLDAS/Noah climatology will serve as the foundation for a global drought/flood monitoring system that includes near realtime daily updates of the global land states.

Diagnosing the Nature of Land-Atmosphere Coupling During the 2006-7 Dry/Wet Extremes in the U.S. Southern Great Plains

NASA Technical Reports Server (NTRS)

Santanello, Joseph A., Jr.; Peters-Lidard, Christa D.; Kumar, Sujay V.; Dong, Xiquan; Kennedy, Aaron D.

2011-01-01

Land-atmosphere interactions play a critical role in determining the. diurnal evolution of both planetary boundary layer (PBL) and land surface temperature and moisture states. The degree of coupling between the land surface and PBL in numerical weather prediction and climate models remains largely unexplored and undiagnosed due to the complex interactions and feedbacks present across a range of scales. Further, uncoupled systems or experiments (e.g., the Project for Intercomparison of Land Parameterization Schemes, PILPS) may lead to inaccurate water and energy cycle process understanding by neglecting feedback processes such as PBL-top entrainment. In this study, a framework for diagnosing local land-atmosphere coupling (LoCo) is presented using a coupled mesoscale model with a suite of PBL and land surface model (LSM) options along with observations during the summers of 200617 in the U.S. Southern Great Plains. Specifically, the Weather Research and Forecasting (WRF) model has been coupled to NASA's Land Information System (LIS), which provides a flexible and high-resolution representation and initialization of land surface physics and states. A range of diagnostics exploring the links and feedbacks between soil moisture and precipitation are examined for the dry/wet extremes of this region, along with the sensitivity of PBL-LSM coupling to perturbations in soil moisture. As such, this methodology provides a potential pathway to study factors controlling local land-atmosphere coupling (LoCo) using the LIS-WRF system, which is serving as a testbed for LoCo experiments to evaluate coupling diagnostics within the community.

Soil carbon sequestration and land use change associated with biofuel production: Empirical evidence

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

Qin, Zhangcai; Dunn, Jennifer B.; Kwon, Hoyoung

Soil organic carbon (SOC) change can be a major impact of land use change (LUC) associated with biofuel feedstock production. By collecting and analyzing data from worldwide field observations with major LUCs from cropland, grassland and forest to lands producing biofuel crops (i.e., corn, switchgrass, Miscanthus, poplar and willow), we were able to estimate SOC response ratios and sequestration rates and evaluate the effects of soil depth and time scale on SOC change. Both the amount and rate of SOC change were highly dependent on the specific land transition. Irrespective of soil depth or time horizon, cropland conversions resulted inmore » an overall SOC gain of 6-14% relative to initial SOC level, while conversion from grassland or forest to corn (without residue removal) or poplar caused significant carbon loss (9-35%). No significant SOC changes were observed in land converted from grasslands or forests to switchgrass, Miscanthus or willow. The SOC response ratios were similar in both 0-30 and 0-100 cm soil depths in most cases, suggesting SOC changes in deep soil and that use of top soil only for SOC accounting in biofuel life cycle analysis (LCA) might underestimate total SOC changes. Soil carbon sequestration rates varied greatly among studies and land transition types. Generally, the rates of SOC change tended to be the greatest during the 10 years following land conversion, and had declined to approach 0 within about 20 years for most LUCs. Observed trends in SOC change were generally consistent with previous reports. Soil depth and duration of study significantly influence SOC change rates and so should be considered in carbon emission accounting in biofuel LCA. High uncertainty remains for many perennial systems, field trials and modeling efforts are needed to determine the site- and system-specific rates and direction of change associated with their production.« less

77 FR 47819 - U.S. Integrated Ocean Observing System (IOOS®) Advisory Committee

Federal Register 2010, 2011, 2012, 2013, 2014

2012-08-10

... Committee will provide advice on (a) Administration, operation, management, and maintenance of the System... Public Land Management Act of 2009 (Pub. L. 111-11). The Committee will advise the NOAA Administrator and...

Changes in diversity, abundance, and structure of soil bacterial communities in Brazilian Savanna under different land use systems.

PubMed

Rampelotto, Pabulo Henrique; de Siqueira Ferreira, Adão; Barboza, Anthony Diego Muller; Roesch, Luiz Fernando Wurdig

2013-10-01

The Brazilian Savanna, also known as "Cerrado", is the richest and most diverse savanna in the world and has been ranked as one of the main hotspots of biodiversity. The Cerrado is a representative biome in Central Brazil and the second largest biome in species diversity of South America. Nevertheless, large areas of native vegetation have been converted to agricultural land including grain production, livestock, and forestry. In this view, understanding how land use affects microbial communities is fundamental for the sustainable management of agricultural ecosystems. The aim of this work was to analyze and compare the soil bacterial communities from the Brazilian Cerrado associated with different land use systems using high throughput pyrosequencing of 16S rRNA genes. Relevant differences were observed in the abundance and structure of bacterial communities in soils under different land use systems. On the other hand, the diversity of bacterial communities was not relevantly changed among the sites studied. Land use systems had also an important impact on specific bacterial groups in soil, which might change the soil function and the ecological processes. Acidobacteria, Proteobacteria, and Actinobacteria were the most abundant groups in the Brazilian Cerrado. These findings suggest that more important than analyzing the general diversity is to analyze the composition of the communities. Since soil type was the same among the sites, we might assume that land use was the main factor defining the abundance and structure of bacterial communities.

Small Body Landing Accuracy Using In-Situ Navigation

NASA Technical Reports Server (NTRS)

Bhaskaran, Shyam; Nandi, Sumita; Broschart, Stephen; Wallace, Mark; Olson, Corwin; Cangahuala, L. Alberto

2011-01-01

Spacecraft landings on small bodies (asteroids and comets) can require target accuracies too stringent to be met using ground-based navigation alone, especially if specific landing site requirements must be met for safety or to meet science goals. In-situ optical observations coupled with onboard navigation processing can meet the tighter accuracy requirements to enable such missions. Recent developments in deep space navigation capability include a self-contained autonomous navigation system (used in flight on three missions) and a landmark tracking system (used experimentally on the Japanese Hayabusa mission). The merging of these two technologies forms a methodology to perform autonomous onboard navigation around small bodies. This paper presents an overview of these systems, as well as the results from Monte Carlo studies to quantify the achievable landing accuracies by using these methods. Sensitivity of the results to variations in spacecraft maneuver execution error, attitude control accuracy and unmodeled forces are examined. Cases for two bodies, a small asteroid and on a mid-size comet, are presented.

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...

Campaign-level Science Traceability for Earth Observation System Architecting

DTIC Science & Technology

2009-05-01

aerosol size and size distribution 2.4.4 canopy density 1.2.1 Atmospheric temperature fields 2.6.2 landcover status 1.3.1 Water vapor profiles 2.7.1...imagery (land) 3.15516 1.5.2 Cloud type 0.20923951 2.6.1 land use 0.060095 1.5.3 Cloud amount/distribution 0.26680361 2.6.2 landcover status

Sustainable landscapes in a world of change: tropical forests, land use and implementation of REDD+: Part I

Treesearch

Richard Birdsey; Yude Pan; Richard Houghton

2013-01-01

Tropical forests play a critical role in the Earth system; however, tropical landscapes have changed greatly in recent decades because of increasing demand for land to support agriculture and timber production, fuel wood, and other pressures of population and human economics. The observable results are a legacy of persistent deforestation, forest degradation, increased...

Upper Mantle Structure Beneath the Whitmore Mountains, West Antarctic Rift System, and Marie Byrd Land from Body-Wave Tomography

NASA Astrophysics Data System (ADS)

Nyblade, A.; Lloyd, A. J.; Anandakrishnan, S.; Wiens, D. A.; Aster, R. C.; Huerta, A. D.; Wilson, T. J.; Shore, P.; Zhao, D.

2011-12-01

As part of the International Polar Year in Antarctica, 37 seismic stations have been installed across West Antarctica as part of the Polar Earth Observing Network (POLENET). 23 stations form a sparse backbone network of which 21 are co-located on rock sites with a network of continuously recording GPS stations. The remaining 14 stations, in conjunction with 2 backbone stations, form a seismic transect extending from the Ellsworth Mountains across the West Antarctic Rift System (WARS) and into Marie Byrd Land. Here we present preliminary P and S wave velocity models of the upper mantle from regional body wave tomography using P and S travel times from teleseismic events recorded by the seismic transect during the first year (2009-2010) of deployment. Preliminary P wave velocity models consisting of ~3,000 ray paths from 266 events indicate that the upper mantle beneath the Whitmore Mountains is seismically faster than the upper mantle beneath Marie Byrd Land and the WARS. Furthermore, we observe two substantial upper mantle low velocity zones located beneath Marie Byrd Land and near the southern boundary of the WARS.

Research on lunar and planet development and utilization

NASA Astrophysics Data System (ADS)

Iwata, Tsutomu; Etou, Takao; Imai, Ryouichi; Oota, Kazuo; Kaneko, Yutaka; Maeda, Toshihide; Takano, Yutaka

1992-08-01

Status of the study on unmanned and manned lunar missions, unmanned Mars missions, lunar resource development and utilization missions, remote sensing exploration missions, survey and review to elucidate the problems of research and development for lunar resource development and utilization, and the techniques and equipment for lunar and planet exploration are presented. Following items were studied respectively: (1) spacecraft systems for unmanned lunar missions, such as lunar observation satellites, lunar landing vehicles, lunar surface rovers, lunar surface hoppers, and lunar sample retrieval; (2) spacecraft systems for manned lunar missions, such as manned lunar bases, lunar surface operation robots, lunar surface experiment systems, manned lunar take-off and landing vehicles, and lunar freight transportation ships; (3) spacecraft systems for Mars missions, such as Mars satellites, Phobos and Deimos sample retrieval vehicles, Mars landing explorers, Mars rovers, Mars sample retrieval; (4) lunar resource development and utilization; and (5) remote sensing exploration technologies.

Ecohydrological drought monitoring and prediction using a land data assimilation system

NASA Astrophysics Data System (ADS)

Sawada, Y.; Koike, T.

2017-12-01

Despite the importance of the ecological and agricultural aspects of severe droughts, few drought monitor and prediction systems can forecast the deficit of vegetation growth. To address this issue, we have developed a land data assimilation system (LDAS) which can simultaneously simulate soil moisture and vegetation dynamics. By assimilating satellite-observed passive microwave brightness temperature, which is sensitive to both surface soil moisture and vegetation water content, we can significantly improve the skill of a land surface model to simulate surface soil moisture, root zone soil moisture, and leaf area index (LAI). We run this LDAS to generate a global ecohydrological land surface reanalysis product. In this presentation, we will demonstrate how useful this new reanalysis product is to monitor and analyze the historical mega-droughts. In addition, using the analyses of soil moistures and LAI as initial conditions, we can forecast the ecological and hydrological conditions in the middle of droughts. We will present our recent effort to develop a near real time ecohydrological drought monitoring and prediction system in Africa by combining the LDAS and the atmospheric seasonal prediction.

Introduction to Japanese exploration study to the moon

NASA Astrophysics Data System (ADS)

Hashimoto, T.; Hoshino, T.; Tanaka, S.; Otake, H.; Otsuki, M.; Wakabayashi, S.; Morimoto, H.; Masuda, K.

2014-11-01

The Japan Aerospace Exploration Agency (JAXA) views the lunar lander SELENE-2 as the successor to the SELENE mission. In this presentation, the mission objectives of SELENE-2 are shown together with the present design status of the spacecraft. JAXA launched the Kaguya (SELENE) lunar orbiter in September 2007, and the spacecraft observed the Moon and a couple of small satellites using 15 instruments. As the next step in lunar exploration, the lunar lander SELENE-2 is being considered. SELENE-2 will land on the lunar surface and perform in-situ scientific observations, environmental investigations, and research for future lunar utilization including human activity. At the same time, it will demonstrate key technologies for lunar and planetary exploration such as precise and safe landing, surface mobility, and overnight survival. The lander will carry laser altimeters, image sensors, and landing radars for precise and safe landing. Landing legs and a precisely controlled propulsion system will also be developed. A rover is being designed to be able to travel over a wide area and observe featured terrain using scientific instruments. Since some of the instruments require long-term observation on the lunar surface, technology for night survival over more than 2 weeks needs to be considered. The SELENE-2 technologies are expected to be one of the stepping stones towards future Japanese human activities on the moon and to expand the possibilities for deep space science.

A Method to Retrieve Rainfall Rate Over Land from TRMM Microwave Imager Observations

NASA Technical Reports Server (NTRS)

Prabhakara, C.; Iacovazzi, R., Jr.; Yoo, J.-M.; Lau, William K. M. (Technical Monitor)

2002-01-01

Over tropical land regions, rain rate maxima in mesoscale convective systems revealed by the Precipitation Radar (PR) flown on the Tropical Rainfall Measuring Mission (TRMM) satellite are found to correspond to thunderstorms, i.e., Cbs. These Cbs are reflected as minima in the 85 GHz brightness temperature, T85, observed by the TRMM Microwave Imager (TMI) radiometer. Because the magnitude of TMI observations do not discriminate satisfactorily convective and stratiform rain, we developed here a different TMI discrimination method. In this method, two types of Cbs, strong and weak, are inferred from the Laplacian of T85 at minima. Then, to retrieve rain rate, where T85 is less than 270 K, a weak (background) rain rate is deduced using T85 observations. Furthermore, over a circular area of 10 km radius centered at the location of each T85 minimum, an additional Cb component of rain rate is added to the background rain rate. This Cb component of rain rate is estimated with the help of (T19-T37) and T85 observations. Initially, our algorithm is calibrated with the PR rain rate measurements from 20 MCS rain events. After calibration, this method is applied to TMI data taken from several tropical land regions. With the help of the PR observations, we show that the spatial distribution and intensity of rain rate over land estimated from our algorithm are better than those given by the current TMI-Version-5 Algorithm. For this reason, our algorithm may be used to improve the current state of rain retrievals on land.

Characterizing user requirements for future land observing satellites

NASA Technical Reports Server (NTRS)

Barker, J. L.; Cressy, P. J.; Schnetzler, C. C.; Salomonson, V. V.

1981-01-01

The objective procedure was developed for identifying probable sensor and mission characteristics for an operational satellite land observing system. Requirements were systematically compiled, quantified and scored by type of use, from surveys of federal, state, local and private communities. Incremental percent increases in expected value of data were estimated for critical system improvements. Comparisons with costs permitted selection of a probable sensor system, from a set of 11 options, with the following characteristics: 30 meter spatial resolution in 5 bands and 15 meters in 1 band, spectral bands nominally at Thematic Mapper (TM) bands 1 through 6 positions, and 2 day data turn around for receipt of imagery. Improvements are suggested for both the form of questions and the procedures for analysis of future surveys in order to provide a more quantitatively precise definition of sensor and mission requirements.

Development of Early Warning System Using ALOS-2/PALSAR-2 Data to Detect and Prevent Deforestation

NASA Astrophysics Data System (ADS)

Hayashi, M.; Nagatani, I.; Watanabe, T.; Tadono, T.; Miyoshi, H.; Watanabe, M.; Koyama, C.; Shimada, M.; Ogawa, T.; Ishii, K.; Higashiuwatoko, T.; Miura, M.; Okonogi, H.; Adachi, K.; Morita, T.

2017-12-01

Satellite observation is an efficient method for monitoring deforestation, and a synthetic aperture radar (SAR) is useful especially in cloudy tropical forest regions. In this context, JICA and JAXA cooperate to operate the deforestation monitoring system acquired data by the Phased Array type L-band SAR-2 (PALSAR-2) onboard the Advanced Land Observing Satellite-2 (ALOS-2), which is named as "JICA-JAXA Forest Early Warning System in the Tropics" (JJ-FAST), and it have been released on November 2016. JJ-FAST detects deforestation areas, and provides their positional information for 77 countries, which is covering almost all tropical forests. It uses PALSAR-2 ScanSAR observation mode (wide-observation swath width) image, which is 50 m spatial resolution acquired at 1.5 months interval. The dark change areas compared with in two acquisitions by PALSAR-2 HV-polarization images are identified as deforestations in the system. We conducted field surveys to validate detection accuracy of the JJ-FAST in Peru (November and December, 2016), Botswana (April, 2017), and Gabon (July, 2017). As the results, 15 of 18 detected areas were correct deforestation areas, therefore user's accuracy could be confirmed as 83.3 % from limited number of the validation data. Erroneous detection areas were caused by seasonal change in agricultural land and open burning in grass land. For improvement of the accuracy, such areas must be excluded from the analysis by additional algorithms e.g. estimation of accurate masking for non-forested areas. Therefore, we are revising the forest map used for pre-processing step in the system. The JJ-FAST can be expected to contribute to monitor and reduce illegal deforestation activities in tropical forests.

Challenges of coordinating global climate observations - Role of satellites in climate monitoring

NASA Astrophysics Data System (ADS)

Richter, C.

2017-12-01

Global observation of the Earth's atmosphere, ocean and land is essential for identifying climate variability and change, and for understanding their causes. Observation also provides data that are fundamental for evaluating, refining and initializing the models that predict how the climate system will vary over the months and seasons ahead, and that project how climate will change in the longer term under different assumptions concerning greenhouse gas emissions and other human influences. Long-term observational records have enabled the Intergovernmental Panel on Climate Change to deliver the message that warming of the global climate system is unequivocal. As the Earth's climate enters a new era, in which it is forced by human activities, as well as natural processes, it is critically important to sustain an observing system capable of detecting and documenting global climate variability and change over long periods of time. High-quality climate observations are required to assess the present state of the ocean, cryosphere, atmosphere and land and place them in context with the past. The global observing system for climate is not a single, centrally managed observing system. Rather, it is a composite "system of systems" comprising a set of climate-relevant observing, data-management, product-generation and data-distribution systems. Data from satellites underpin many of the Essential Climate Variables(ECVs), and their historic and contemporary archives are a key part of the global climate observing system. In general, the ECVs will be provided in the form of climate data records that are created by processing and archiving time series of satellite and in situ measurements. Early satellite data records are very valuable because they provide unique observations in many regions which were not otherwise observed during the 1970s and which can be assimilated in atmospheric reanalyses and so extend the satellite climate data records back in time.

Understanding Mesoscale Land-Atmosphere Interactions in Arctic Region

NASA Astrophysics Data System (ADS)

Hong, X.; Wang, S.; Nachamkin, J. E.

2017-12-01

Land-atmosphere interactions in Arctic region are examined using the U.S. Navy Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS©*) with the Noah Land Surface Model (LSM). Initial land surface variables in COAMPS are interpolated from the real-time NASA Land Information System (LIS). The model simulations are configured for three nest grids with 27-9-3 km horizontal resolutions. The simulation period is set for October 2015 with 12-h data assimilation update cycle and 24-h integration length. The results are compared with those simulated without using LSM and evaluated with observations from ONR Sea State R/V Sikuliaq cruise and the North Slope of Alaska (NSA). There are complex soil and vegetation types over the surface for simulation with LSM, compared to without LSM simulation. The results show substantial differences in surface heat fluxes between bulk surface scheme and LSM, which may have an important impact on the sea ice evolution over the Arctic region. Evaluations from station data show surface air temperature and relative humidity have smaller biases for simulation using LSM. Diurnal variation of land surface temperature, which is necessary for physical processes of land-atmosphere, is also better captured than without LSM.

Earth observing system: 1989 reference handbook

NASA Technical Reports Server (NTRS)

1989-01-01

NASA is studying a coordinated effort called the Mission to Planet Earth to understand global change. The goals are to understand the Earth as a system, and to determine those processes that contribute to the environmental balance, as well as those that may result in changes. The Earth Observing System (Eos) is the centerpiece of the program. Eos will create an integrated scientific observing system that will enable multidisciplinary study of the Earth including the atmosphere, oceans, land surface, polar regions, and solid Earth. Science goals, the Eos data and information system, experiments, measuring instruments, and interdisciplinary investigations are described.

Implementation of SMOS data monitoring in the Integrated Forecast System. Preliminary results.

NASA Astrophysics Data System (ADS)

Muñoz Sabater, Joaquin; de Rosnay, Patricia; Drusch, Mathias; Dahoui, Mohamed; Delwart, Steven; Wright, Norrie

2010-05-01

The Soil Moisture and Ocean Salinity (SMOS) mission of the European Space Agency (ESA) was successfully launched on November 2nd 2009. Using a novel concept based on the Synthetic Aperture Radar technique, it is expected that SMOS observations will provide global accurate maps of brightness temperatures (TB) and soil moisture at L-band every 3 days and at 50 km ground-spatial resolution. Thus, SMOS data will soon provide a valuable input for numerical weather prediction (NWP), hydrological and land surface systems, among others. Operational numerical weather forecast systems are widely used to evaluate and analyse new types of satellite observations. NWP centres use these observations in their analyses to derive level 2 retrieved geophysical parameters (e.g. soil moisture and ocean salinity for SMOS) from the observed radiances. The European Centre for Medium Range Weather Forecasts is monitoring the first flow of SMOS level 1C TB over sea and land. Monitoring, i.e. the systematic comparison between observations and the corresponding model parameters, is a mandatory step prior to data assimilation. Consequently, monitoring provides an overall quality assessment of SMOS data based on departures values between SMOS observations and the modelled equivalent in the observation space. This is a significant contribution to the calibration / validation activities during the SMOS commissioning phase. Any systematic error or spikes in the data become visible and can be reported to ESA and the other calibration and validation teams without significant delays. Furthermore, the monitored data at global scale will help to calibrate the SMOS instrument at key decision points during the commissioning phase. In this paper the first SMOS data over land is monitored. Special emphasis is given to the effect of different parametrisations and auxiliary data sets on the simulated TB. This is a first step towards the assimilation of SMOS TB to improve the initialization of soil moisture for NWP systems.

An early warning system to forecast the close of the spring burning window from satellite-observed greenness.

PubMed

Pickell, Paul D; Coops, Nicholas C; Ferster, Colin J; Bater, Christopher W; Blouin, Karen D; Flannigan, Mike D; Zhang, Jinkai

2017-10-27

Spring represents the peak of human-caused wildfire events in populated boreal forests, resulting in catastrophic loss of property and human life. Human-caused wildfire risk is anticipated to increase in northern forests as fuels become drier, on average, under warming climate scenarios and as population density increases within formerly remote regions. We investigated springtime human-caused wildfire risk derived from satellite-observed vegetation greenness in the early part of the growing season, a period of increased ignition and wildfire spread potential from snow melt to vegetation green-up with the aim of developing an early warning wildfire risk system. The initial system was developed for 392,856 km 2 of forested lands with satellite observations available prior to the start of the official wildfire season and predicted peak human-caused wildfire activity with 10-day accuracy for 76% of wildfire-protected lands by March 22. The early warning system could have significant utility as a cost-effective solution for wildfire managers to prioritize the deployment of wildfire protection resources in wildfire-prone landscapes across boreal-dominated ecosystems of North America, Europe, and Russia using open access Earth observations.

Technical Report Series on Global Modeling and Data Assimilation. Volume 14; A Comparison of GEOS Assimilated Data with FIFE Observations

NASA Technical Reports Server (NTRS)

Bosilovich, Michael G.; Suarez, Max J. (Editor); Schubert, Siegfried D.

1998-01-01

First ISLSCP Field Experiment (FIFE) observations have been used to validate the near-surface proper- ties of various versions of the Goddard Earth Observing System (GEOS) Data Assimilation System. The site- averaged FIFE data set extends from May 1987 through November 1989, allowing the investigation of several time scales, including the annual cycle, daily means and diurnal cycles. Furthermore, the development of the daytime convective planetary boundary layer is presented for several days. Monthly variations of the surface energy budget during the summer of 1988 demonstrate the affect of the prescribed surface soil wetness boundary conditions. GEOS data comes from the first frozen version of the assimilation system (GEOS-1 DAS) and two experimental versions of GEOS (v. 2.0 and 2.1) with substantially greater vertical resolution and other changes that influence the boundary layer. This report provides a baseline for future versions of the GEOS data assimilation system that will incorporate a state-of-the-art land surface parameterization. Several suggestions are proposed to improve the generality of future comparisons. These include the use of more diverse field experiment observations and an estimate of gridpoint heterogeneity from the new land surface parameterization.

Land use survey and mapping and water resources investigation in Korea

NASA Technical Reports Server (NTRS)

Choi, J. H.; Kim, W. I.; Son, D. S. (Principal Investigator)

1978-01-01

The author has identified the following significant results. Land use imagery is applicable to land use classification for small scale land use mapping less than 1:250,000. Land use mapping by satellite is more efficient and more cost-effective than land use mapping from conventional medium altitude aerial photographs. Six categories of level 1 land use classification are recognizable from MSS imagery. A hydrogeomorphological study of the Han River basin indicates that band 7 is useful for recognizing the soil and the weathering part of bed rock. The morphological change of the main river is accurately recognized and the drainage system in the area observed is easily classified because of the more or less simple rock type. Although the direct hydrological characteristics are not obtained from the MSS imagery, the indirect information such as the permeability of the soil and the vegetation cover, is helpful in interpreting the hydrological aspects.

Initializing carbon cycle predictions from the Community Land Model by assimilating global biomass observations

NASA Astrophysics Data System (ADS)

Fox, A. M.; Hoar, T. J.; Smith, W. K.; Moore, D. J.

2017-12-01

The locations and longevity of terrestrial carbon sinks remain uncertain, however it is clear that in order to predict long-term climate changes the role of the biosphere in surface energy and carbon balance must be understood and incorporated into earth system models (ESMs). Aboveground biomass, the amount of carbon stored in vegetation, is a key component of the terrestrial carbon cycle, representing the balance of uptake through gross primary productivity (GPP), losses from respiration, senescence and mortality over hundreds of years. The best predictions of current and future land-atmosphere fluxes are likely from the integration of process-based knowledge contained in models and information from observations of changes in carbon stocks using data assimilation (DA). By exploiting long times series, it is possible to accurately detect variability and change in carbon cycle dynamics through monitoring ecosystem states, for example biomass derived from vegetation optical depth (VOD), and use this information to initialize models before making predictions. To make maximum use of information about the current state of global ecosystems when using models we have developed a system that combines the Community Land Model (CLM) with the Data Assimilation Research Testbed (DART), a community tool for ensemble DA. This DA system is highly innovative in its complexity, completeness and capabilities. Here we described a series of activities, using both Observation System Simulation Experiments (OSSEs) and real observations, that have allowed us to quantify the potential impact of assimilating VOD data into CLM-DART on future land-atmosphere fluxes. VOD data are particularly suitable to use in this activity due to their long temporal coverage and appropriate scale when combined with CLM, but their absolute values rely on many assumptions. Therefore, we have had to assess the implications of the VOD retrieval algorithms, with an emphasis on detecting uncertainty due to assumptions and inputs in the algorithms that are incompatible with those encoded within CLM. It is probable that VOD describes changes in biomass more accurately than absolute values, so in additional to sequential assimilation of observations, we have tested alternative filter algorithms, and assimilating VOD anomalies.

The Third Tibetan Plateau Atmospheric Scientific Experiment for Understanding the Earth-Atmosphere Coupled System

NASA Astrophysics Data System (ADS)

Zhao, P.; Xu, X.; Chen, F.; Guo, X.; Zheng, X.; Liu, L. P.; Hong, Y.; Li, Y.; La, Z.; Peng, H.; Zhong, L. Z.; Ma, Y.; Tang, S. H.; Liu, Y.; Liu, H.; Li, Y. H.; Zhang, Q.; Hu, Z.; Sun, J. H.; Zhang, S.; Dong, L.; Zhang, H.; Zhao, Y.; Yan, X.; Xiao, A.; Wan, W.; Zhou, X.

2016-12-01

The Third Tibetan Plateau atmospheric scientific experiment (TIPEX-III) was initiated jointly by the China Meteorological Administration, the National Natural Scientific Foundation, and the Chinese Academy of Sciences. This paper presents the background, scientific objectives, and overall experimental design of TIPEX-III. It was designed to conduct an integrated observation of the earth-atmosphere coupled system over the Tibetan Plateau (TP) from land surface, planetary boundary layer (PBL), troposphere, and stratosphere for eight to ten years by coordinating ground- and air-based measurement facilities for understanding spatial heterogeneities of complex land-air interactions, cloud-precipitation physical processes, and interactions between troposphere and stratosphere. TIPEX-III originally began in 2014, and is ongoing. It established multiscale land-surface and PBL observation networks over the TP and a tropospheric meteorological radiosonde network over the western TP, and executed an integrated observation mission for cloud-precipitation physical features using ground-based radar systems and aircraft campaigns and an observation task for atmospheric ozone, aerosol, and water vapor. The archive, management, and share policy of the observation data are also introduced herein. Some TIPEX-III data have been preliminarily applied to analyze the features of surface sensible and latent heat fluxes, cloud-precipitation physical processes, and atmospheric water vapor and ozone over the TP, and to improve the local precipitation forecast. Furthermore, TIPEX-III intends to promote greater scientific and technological cooperation with international research communities and broader organizations. Scientists working internationally are invited to participate in the field campaigns and to use the TIPEX-III data for their own research.

Evaluation ofthe Middle East and North Africa Land Data Assimilation System

NASA Technical Reports Server (NTRS)

Bolten, John D.; Rodell, Matthew; Zaitchik, Benjamin; Ozdogan, Mutlu; Anderson, Martha; Bergaoui, Karim B.; Khalaf, Adla J.; McDonnell, Rachael A.

2012-01-01

The Middle East and North Africa (MENA) region is dominated by dry, warm deserts, areas of dense population, and inefficient use of fresh water resources. Due to the scarcity, high intensity, and short duration of rainfall in the MENA, the region is prone to hydro climatic extremes that are realized by devastating floods and times of drought. However, given its widespread water stress and the considerable demand for water, the MENA remains relatively poorly monitored. This is due in part to the shortage of meteorological observations and the lack of data sharing between nations. As a result, the accurate monitoring of the dynamics of the water cycle in the MENA is difficult. The Land Data Assimilation System for the MENA region (MENA LDAS) has been developed to provide regional, gridded fields of hydrological states and fluxes relevant for water resources assessments. As an extension of the Global Land Data Assimilation System (GLDAS), the MENA LDAS was designed to aid in the identification and evaluation of regional hydrological anomalies by synergistically combining the physically-based Catchment Land Surface Model (CLSM) with observations from several independent data products including soil-water storage variations from the Gravity Recovery and Climate Experiment (GRACE) and irrigation intensity derived from the Moderate Resolution Imaging Spectroradiometer (MODIS). In this fashion, we estimate the mean and seasonal cycle of the water budget components across the MENA.

Improving the Fit of a Land-Surface Model to Data Using its Adjoint

NASA Astrophysics Data System (ADS)

Raoult, Nina; Jupp, Tim; Cox, Peter; Luke, Catherine

2016-04-01

Land-surface models (LSMs) are crucial components of the Earth System Models (ESMs) which are used to make coupled climate-carbon cycle projections for the 21st century. The Joint UK Land Environment Simulator (JULES) is the land-surface model used in the climate and weather forecast models of the UK Met Office. In this study, JULES is automatically differentiated using commercial software from FastOpt, resulting in an analytical gradient, or adjoint, of the model. Using this adjoint, the adJULES parameter estimation system has been developed, to search for locally optimum parameter sets by calibrating against observations. We present an introduction to the adJULES system and demonstrate its ability to improve the model-data fit using eddy covariance measurements of gross primary production (GPP) and latent heat (LE) fluxes. adJULES also has the ability to calibrate over multiple sites simultaneously. This feature is used to define new optimised parameter values for the 5 Plant Functional Types (PFTS) in JULES. The optimised PFT-specific parameters improve the performance of JULES over 90% of the FLUXNET sites used in the study. These reductions in error are shown and compared to reductions found due to site-specific optimisations. Finally, we show that calculation of the 2nd derivative of JULES allows us to produce posterior probability density functions of the parameters and how knowledge of parameter values is constrained by observations.

Impact of Biomass Burning Aerosols on Cloud Formation in Coastal Regions

NASA Astrophysics Data System (ADS)

Nair, U. S.; Wu, Y.; Reid, J. S.

2017-12-01

In the tropics, shallow and deep convective cloud structures organize in hierarchy of spatial scales ranging from meso-gamma (2-20 km) to planetary scales (40,000km). At the lower end of the spectrum is shallow convection over the open ocean, whose upscale growth is dependent upon mesoscale convergence triggers. In this context, cloud systems associated with land breezes that propagate long distances into open ocean areas are important. We utilized numerical model simulations to examine the impact of biomass burning on such cloud systems in the maritime continent, specifically along the coastal regions of Sarawak. Numerical model simulations conducted using the Weather Research and Forecasting Chemistry (WRF-Chem) model show spatial patterns of smoke that show good agreement to satellite observations. Analysis of model simulations show that, during daytime the horizontal convective rolls (HCRs) that form over land play an important role in organizing transport of smoke in the coastal regions. Alternating patterns of low and high smoke concentrations that are well correlated to the wavelengths of HCRs are found in both the simulations and satellite observations. During night time, smoke transport is modulated by the land breeze circulation and a band of enhanced smoke concentration is found along the land breeze front. Biomass burning aerosols are ingested by the convective clouds that form along the land breeze and leads to changes in total water path, cloud structure and precipitation formation.

How Accurate is Land/Ocean Moisture Transport Variability in Reanalyses?

NASA Technical Reports Server (NTRS)

Robertson, F. R.; Bosilovich, M. G.

2014-01-01

Quantifying the global hydrological cycle and its variability across various time scales remains a challenge to the climate community. Direct measurements of evaporation (E), evapotranspiration (ET), and precipitation (P) are not feasible on a global scale, nor is the transport of water vapor over the global oceans and sparsely populated land areas. Expanding satellite data streams have enabled development of various water (and energy) flux products, complementing reanalyses and facilitating observationally constrained modeling. But the evolution of the global observing system has produced additional complications--improvements in satellite sensor resolution and accuracy have resulted in "epochs" of observational quasi-uniformity that can adversely affect reanalysis trends. In this work we focus on vertically integrated moisture flux convergence (VMFC) variations within the period 1979 - present integrated over global land. We show that VMFC in recent reanalyses (e.g. ERA-I, NASA MERRA, NOAA CFSR and JRA55) suffers from observing system changes, though differently in each product. Land Surface Models (LSMs) forced with observations-based precipitation, radiation and near-surface meteorology share closely the interannual P-ET variations of the reanalyses associated with ENSO events. (VMFC over land and P-ET estimates are equivalent quantities since atmospheric storage changes are small on these scales.) But the long-term LSM trend over the period since 1979 is approximately one-fourth that of the reanalyses. Additional reduced observation reanalyses assimilating only surface pressure and /or specifying seasurface temperature also have a much smaller trend in P-ET like the LSMs. We explore the regional manifestation of the reanalysis P-ET / VMFC problems, particularly over land. Both principal component analysis and a simple time series changepoint analysis highlight problems associated with data poor regions such as Equatorial Africa and, for one reanalysis, the Equatorial Andes region. Onset of the availability of passive microwave Special Sensor Microwave Imager (SSMI) moisture data in July 1987 and the transition from the Microwave Sounder Unit (MSU) to an advanced version (AMSU) have significant impacts on VMFC variability. Simple accounting for these errors of leading importance results in modified reanalysis VMFC estimates that agree much better with the LSM results. Regional details of the modified reanalysis VMFC and LSM P-ET are related to changes in Pacific Decadal Variability as manifest in SST changes after the late 1990s.

Orion Multi-Purpose Crew Vehicle Solving and Mitigating the Two Main Cluster Pendulum Problem

NASA Technical Reports Server (NTRS)

Ali, Yasmin; Sommer, Bruce; Troung, Tuan; Anderson, Brian; Madsen, Christopher

2017-01-01

The Orion Multi-purpose Crew Vehicle (MPCV) Orion spacecraft will return humans from beyond earth's orbit, including Mars and will be required to land 20,000 pounds of mass safely in the ocean. The parachute system nominally lands under 3 main parachutes, but the system is designed to be fault tolerant and land under 2 main parachutes. During several of the parachute development tests, it was observed that a pendulum, or swinging, motion could develop while the Crew Module (CM) was descending under two parachutes. This pendulum effect had not been previously predicted by modeling. Landing impact analysis showed that the landing loads would double in some places across the spacecraft. The CM structural design limits would be exceeded upon landing if this pendulum motion were to occur. The Orion descent and landing team was faced with potentially millions of dollars in structural modifications and a severe mass increase. A multidisciplinary team was formed to determine root cause, model the pendulum motion, study alternate canopy planforms and assess alternate operational vehicle controls & operations providing mitigation options resulting in a reliability level deemed safe for human spaceflight. The problem and solution is a balance of risk to a known solution versus a chance to improve the landing performance for the next human-rated spacecraft.

The CEOS constellation for land surface imaging

USGS Publications Warehouse

Bailey, G.B.; Berger, Marsha; Jeanjean, H.; Gallo, K.P.

2007-01-01

A constellation of satellites that routinely and frequently images the Earth's land surface in consistently calibrated wavelengths from the visible through the microwave and in spatial detail that ranges from sub-meter to hundreds of meters would offer enormous potential benefits to society. A well-designed and effectively operated land surface imaging satellite constellation could have great positive impact not only on the quality of life for citizens of all nations, but also on mankind's very ability to sustain life as we know it on this planet long into the future. The primary objective of the Committee on Earth Observation Satellites (CEOS) Land Surface Imaging (LSI) Constellation is to define standards (or guidelines) that describe optimal future LSI Constellation capabilities, characteristics, and practices. Standards defined for a LSI Constellation will be based on a thorough understanding of user requirements, and they will address at least three fundamental areas of the systems comprising a Land Surface Imaging Constellation: the space segments, the ground segments, and relevant policies and plans. Studies conducted by the LSI Constellation Study Team also will address current and shorter-term problems and issues facing the land remote sensing community today, such as seeking ways to work more cooperatively in the operation of existing land surface imaging systems and helping to accomplish tangible benefits to society through application of land surface image data acquired by existing systems. 2007 LSI Constellation studies are designed to establish initial international agreements, develop preliminary standards for a mid-resolution land surface imaging constellation, and contribute data to a global forest assessment.

A new approach to complete aircraft landing gear noise prediction

NASA Astrophysics Data System (ADS)

Lopes, Leonard V.

This thesis describes a new landing gear noise prediction system developed at The Pennsylvania State University, called Landing Gear Model and Acoustic Prediction code (LGMAP). LGMAP is used to predict the noise of an isolated or installed landing gear geometry. The predictions include several techniques to approximate the aeroacoustic and aerodynamic interactions of landing gear noise generation. These include (1) a method for approximating the shielding of noise caused by the landing gear geometry, (2) accounting for local flow variations due to the wing geometry, (3) the interaction of the landing gear wake with high-lift devices, and (4) a method for estimating the effect of gross landing gear design changes on local flow and acoustic radiation. The LGMAP aeroacoustic prediction system has been created to predict the noise generated by a given landing gear. The landing gear is modeled as a set of simple components that represent individual parts of the structure. Each component, ranging from large to small, is represented by a simple geometric shape and the unsteady flow on the component is modeled based on an individual characteristic length, local flow velocity, and the turbulent flow environment. A small set of universal models is developed and applied to a large range of similar components. These universal models, combined with the actual component geometry and local environment, give a unique loading spectrum and acoustic field for each component. Then, the sum of all the individual components in the complete configuration is used to model the high level of geometric complexity typical of current aircraft undercarriage designs. A line of sight shielding algorithm based on scattering by a two-dimensional cylinder approximates the effect of acoustic shielding caused by the landing gear. Using the scattering from a cylinder in two-dimensions at an observer position directly behind the cylinder, LGMAP is able to estimate the reduction in noise due to shielding by the landing gear geometry. This thesis compares predictions with data from a recent wind tunnel experiment conducted at NASA Langley Research Center, and demonstrates that including the acoustic scattering can improve the predictions by LGMAP at all observer positions. In this way, LGMAP provides more information about the actual noise propagation than simple empirical schemes. Two-dimensional FLUENT calculations of approximate wing cross-sections are used by LGMAP to compute the change in noise due to the change in local flow velocity in the vicinity of the landing gear due to circulation around the wing. By varying angle of attack and flap deflection angle in the CFD calculations, LGMAP is able to predict the noise level change due to the change in local flow velocity in the landing gear vicinity. A brief trade study is performed on the angle of attack of the wing and flap deflection angle of the flap system. It is shown that increasing the angle of attack or flap deflection angle reduces the flow velocity in the vicinity of the landing gear, and therefore the predicted noise. Predictions demonstrate the ability of the prediction system to quickly estimate the change in landing gear noise caused by a change in wing configuration. A three-dimensional immersed boundary CFD calculation of simplified landing gear geometries provides relatively quick estimates of the mean flow around the landing gear. The mean flow calculation provides the landing gear wake geometry for the prediction of trailing edge noise associated with the interaction of the landing gear wake with the high lift devices. Using wind tunnel experiments that relate turbulent intensity to wake size and the Ffowcs Williams and Hall trailing edge noise equation for the acoustic calculation, LGMAP is able to predict the landing gear wake generated trailing edge noise. In this manner, LGMAP includes the effect of the interaction of the landing gear's wake with the wing/flap system on the radiated noise. The final prediction technique implemented includes local flow calculations of a landing gear with various truck angles using the immersed boundary scheme. Using the mean flow calculation, LGMAP is able to predict noise changes caused by gross changes in landing gear design. Calculations of the mean flow around the landing gear show that the rear wheels of a six-wheel bogie experience significantly reduced mean flow velocity when the truck is placed in a toe-down configuration. This reduction in the mean flow results is a lower noise signature from the rear wheel. Since the noise from a six-wheel bogie at flyover observer positions is primarily composed of wheel noise, the reduced local flow velocity results in a reduced noise signature from the entire landing gear geometry. Comparisons with measurements show the accuracy of the predictions of landing gear noise levels and directivity. Airframe noise predictions for the landing gear of a complete aircraft are described including all of the above mentioned developments and prediction techniques. These show that the nose gear noise and the landing gear wake/flap interaction noise, while not significantly changing the overall shape of the radiated noise, do contribute to the overall noise from the installed landing gear.

Assimilation of SMOS Retrieved Soil Moisture into the Land Information System

NASA Technical Reports Server (NTRS)

Blankenship, Clay B.; Case, Jonathan L.; Zavodsky, Bradley T.

2014-01-01

Soil moisture is a crucial variable for weather prediction because of its influence on evaporation and surface heat fluxes. It is also of critical importance for drought and flood monitoring and prediction and for public health applications such as monitoring vector-borne diseases. Land surface modeling benefits greatly from regular updates with soil moisture observations via data assimilation. Satellite remote sensing is the only practical observation type for this purpose in most areas due to its worldwide coverage. The newest operational satellite sensor for soil moisture is the Microwave Imaging Radiometer using Aperture Synthesis (MIRAS) instrument aboard the Soil Moisture and Ocean Salinity (SMOS) satellite. The NASA Short-term Prediction Research and Transition Center (SPoRT) has implemented the assimilation of SMOS soil moisture observations into the NASA Land Information System (LIS), an integrated modeling and data assimilation software platform. We present results from assimilating SMOS observations into the Noah 3.2 land surface model within LIS. The SMOS MIRAS is an L-band radiometer launched by the European Space Agency in 2009, from which we assimilate Level 2 retrievals [1] into LIS-Noah. The measurements are sensitive to soil moisture concentration in roughly the top 2.5 cm of soil. The retrievals have a target volumetric accuracy of 4% at a resolution of 35-50 km. Sensitivity is reduced where precipitation, snowcover, frozen soil, or dense vegetation is present. Due to the satellite's polar orbit, the instrument achieves global coverage twice daily at most mid- and low-latitude locations, with only small gaps between swaths.

Quantifying the Observability of CO2 Flux Uncertainty in Atmospheric CO2 Records Using Products from Nasa's Carbon Monitoring Flux Pilot Project

NASA Technical Reports Server (NTRS)

Ott, Lesley; Pawson, Steven; Collatz, Jim; Watson, Gregg; Menemenlis, Dimitris; Brix, Holger; Rousseaux, Cecile; Bowman, Kevin; Bowman, Kevin; Liu, Junjie;

Translation of Land Surface Model Accuracy and Uncertainty into Coupled Land-Atmosphere Prediction

NASA Technical Reports Server (NTRS)

Santanello, Joseph A.; Kumar, Sujay; Peters-Lidard, Christa D.; Harrison, Kenneth W.; Zhou, Shuija

2012-01-01

Land-atmosphere (L-A) Interactions playa critical role in determining the diurnal evolution of both planetary boundary layer (PBL) and land surface heat and moisture budgets, as well as controlling feedbacks with clouds and precipitation that lead to the persistence of dry and wet regimes. Recent efforts to quantify the strength of L-A coupling in prediction models have produced diagnostics that integrate across both the land and PBL components of the system. In this study, we examine the impact of improved specification of land surface states, anomalies, and fluxes on coupled WRF forecasts during the summers of extreme dry (2006) and wet (2007) land surface conditions in the U.S. Southern Great Plains. The improved land initialization and surface flux parameterizations are obtained through the use of a new optimization and uncertainty estimation module in NASA's Land Information System (US-OPT/UE), whereby parameter sets are calibrated in the Noah land surface model and classified according to a land cover and soil type mapping of the observation sites to the full model domain. The impact of calibrated parameters on the a) spinup of the land surface used as initial conditions, and b) heat and moisture states and fluxes of the coupled WRF Simulations are then assessed in terms of ambient weather and land-atmosphere coupling along with measures of uncertainty propagation into the forecasts. In addition, the sensitivity of this approach to the period of calibration (dry, wet, average) is investigated. Finally, tradeoffs of computational tractability and scientific validity, and the potential for combining this approach with satellite remote sensing data are also discussed.

Contributions of Precipitation and Soil Moisture Observations to the Skill of Soil Moisture Estimates in a Land Data Assimilation System

NASA Technical Reports Server (NTRS)

Reichle, Rolf H.; Liu, Qing; Bindlish, Rajat; Cosh, Michael H.; Crow, Wade T.; deJeu, Richard; DeLannoy, Gabrielle J. M.; Huffman, George J.; Jackson, Thomas J.

2011-01-01

The contributions of precipitation and soil moisture observations to the skill of soil moisture estimates from a land data assimilation system are assessed. Relative to baseline estimates from the Modern Era Retrospective-analysis for Research and Applications (MERRA), the study investigates soil moisture skill derived from (i) model forcing corrections based on large-scale, gauge- and satellite-based precipitation observations and (ii) assimilation of surface soil moisture retrievals from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E). Soil moisture skill is measured against in situ observations in the continental United States at 44 single-profile sites within the Soil Climate Analysis Network (SCAN) for which skillful AMSR-E retrievals are available and at four CalVal watersheds with high-quality distributed sensor networks that measure soil moisture at the scale of land model and satellite estimates. The average skill (in terms of the anomaly time series correlation coefficient R) of AMSR-E retrievals is R=0.39 versus SCAN and R=0.53 versus CalVal measurements. The skill of MERRA surface and root-zone soil moisture is R=0.42 and R=0.46, respectively, versus SCAN measurements, and MERRA surface moisture skill is R=0.56 versus CalVal measurements. Adding information from either precipitation observations or soil moisture retrievals increases surface soil moisture skill levels by IDDeltaR=0.06-0.08, and root zone soil moisture skill levels by DeltaR=0.05-0.07. Adding information from both sources increases surface soil moisture skill levels by DeltaR=0.13, and root zone soil moisture skill by DeltaR=0.11, demonstrating that precipitation corrections and assimilation of satellite soil moisture retrievals contribute similar and largely independent amounts of information.

Committed climate change due to historical land use and management: the concept

NASA Astrophysics Data System (ADS)

Freibauer, Annette; Dolman, Han; Don, Axel; Poeplau, Christopher

2013-04-01

A significant fraction of the European land surface has changed its land use over the last 50 years. Management practices have changed in the same period in most land use systems. These changes have affected the carbon and greenhouse gas (GHG) balance of the European land surface. Land use intensity, defined here loosely as the degree to which humans interfere with the land, strongly affects GHG emissions. Land use and land management changes suggest that the variability of the carbon balance and of GHG emissions of cultivated land areas in Europe is much more driven by land use history and management than driven by climate. Importantly changes in land use and its management have implications for future GHG emissions, and therefore present a committed climate change, defined as inevitable future additional climate change induced by past human activity. It is one of the key goals of the large-scale integrating research project "GHG-Europe - Greenhouse gas management in European land use systems" to quantify the committed climate change due to legacy effects by land use and management. The project is funded by the European Commission in the 7th framework programme (Grant agreement no.: 244122). This poster will present the conceptual approach taken to reach this goal. (1) First of all we need to proof that at site, or regional level the management effects are larger than climate effects on carbon balance and GHG emissions. Observations from managed sites and regions will serve as empirical basis. Attribution experiments with models based on process understanding are run on managed sites and regions will serve to demonstrate that the observed patterns of the carbon balance and GHG emissions can only be reproduced when land use and management are included as drivers. (2) The legacy of land use changes will be quantified by combining spatially explicit time series of land use changes with response functions of carbon pools. This will allow to separate short-term and long-term effects of land-use changes, to quantify how much current changes in biomass and soil carbon are driven by past land use change and how much future changes in biomass and soil carbon have already been committed by past and present land use changes. (3) The legacy of land management changes will be quantified by combining spatially explicit time series of land management activities with response functions and relatively simple models of carbon pools and greenhouse gases. This will allow to detect major trends and spatial patterns in carbon and GHG fluxes driven by intensification or extensification over the last decades. The poster will concentrate on background, concept of the legacy analysis, data sources and the scientific strategy for deriving the climate change committed by past and present land use and management in Europe.

A Feasibility Analysis of Land-Based SINS/GNSS Gravimetry for Groundwater Resource Detection in Taiwan

PubMed Central

Chiang, Kai-Wei; Lin, Cheng-An; Kuo, Chung-Yen

2015-01-01

The integration of the Strapdown Inertial Navigation System and Global Navigation Satellite System (SINS/GNSS) has been implemented for land-based gravimetry and has been proven to perform well in estimating gravity. Based on the mGal-level gravimetry results, this research aims to construct and develop a land-based SINS/GNSS gravimetry device containing a navigation-grade Inertial Measurement Unit. This research also presents a feasibility analysis for groundwater resource detection. A preliminary comparison of the kinematic velocities and accelerations using multi-combination of GNSS data including Global Positioning System, Global Navigation Satellite System, and BeiDou Navigation Satellite System, indicates that three-system observations performed better than two-system data in the computation. A comparison of gravity derived from SINS/GNSS and measured using a relative gravimeter also shows that both agree reasonably well with a mean difference of 2.30 mGal. The mean difference between repeat measurements of gravity disturbance using SINS/GNSS is 2.46 mGal with a standard deviation of 1.32 mGal. The gravity variation because of the groundwater at Pingtung Plain, Taiwan could reach 2.72 mGal. Hence, the developed land-based SINS/GNSS gravimetry can sufficiently and effectively detect groundwater resources. PMID:26426019

A Feasibility Analysis of Land-Based SINS/GNSS Gravimetry for Groundwater Resource Detection in Taiwan.

PubMed

Chiang, Kai-Wei; Lin, Cheng-An; Kuo, Chung-Yen

2015-09-29

The integration of the Strapdown Inertial Navigation System and Global Navigation Satellite System (SINS/GNSS) has been implemented for land-based gravimetry and has been proven to perform well in estimating gravity. Based on the mGal-level gravimetry results, this research aims to construct and develop a land-based SINS/GNSS gravimetry device containing a navigation-grade Inertial Measurement Unit. This research also presents a feasibility analysis for groundwater resource detection. A preliminary comparison of the kinematic velocities and accelerations using multi-combination of GNSS data including Global Positioning System, Global Navigation Satellite System, and BeiDou Navigation Satellite System, indicates that three-system observations performed better than two-system data in the computation. A comparison of gravity derived from SINS/GNSS and measured using a relative gravimeter also shows that both agree reasonably well with a mean difference of 2.30 mGal. The mean difference between repeat measurements of gravity disturbance using SINS/GNSS is 2.46 mGal with a standard deviation of 1.32 mGal. The gravity variation because of the groundwater at Pingtung Plain, Taiwan could reach 2.72 mGal. Hence, the developed land-based SINS/GNSS gravimetry can sufficiently and effectively detect groundwater resources.

Global Soil Moisture Estimation from L-Band Satellite Data: The Impact of Radiative Transfer Modeling in Assimilation and Retrieval Systems

NASA Technical Reports Server (NTRS)

De Lannoy, Gabrielle; Reichle, Rolf; Gruber, Alexander; Bechtold, Michel; Quets, Jan; Vrugt, Jasper; Wigneron, Jean-Pierre

2018-01-01

The SMOS and SMAP missions have collected a wealth of global L-band Brightness temperature (Tb) observations. The retrieval of surface Soil moisture estimates, and the estimation of other geophysical Variables, such as root-zone soil moisture and temperature, via data Assimilation into land surface models largely depends on accurate Radiative transfer modeling (RTM). This presentation will focus on various configuration aspects of the RTM (i) for the inversion of SMOS Tb to surface soil moisture, and (ii) for the forward modeling as part of a SMOS Tb data assimilation System to estimate a consistent set of geophysical land surface Variables, using the GEOS-5 Catchment Land Surface Model.

Planimetric Features Generalization for the Production of Small-Scale Map by Using Base Maps and the Existing Algorithms

NASA Astrophysics Data System (ADS)

Modiri, M.; Mohebbi, M.; Masoumi, M.; Khanlu, H.; Eftekhari, A.

2014-11-01

Land reform is identified as a key tool in fostering development in South Africa. With two decades after the advent of democracy in South Africa, the land question remains a critical issue for policy makers. A number of frameworks have been put in place by the government to identify land which is strategically located for land reform. However, many of these frameworks are not well aligned and have hampered the government's land reform initiative in promoting inclusive development. Strategically located land is herein defined as land parcels that are well positioned for the promotion of agriculture, human settlements, rural and tourism development. Accordingly, there is a need to develop a decision tool which facilitates the identification of strategically located land for development. This study proposes the use of geographic information systems (GIS), earth observation (EO) data and multi-criteria decision making (MCDM) to develop a spatial decision support system (SDSS) to identify strategically located land for land reform. The SDDS was therefore designed using GIS, EO data and MCDM to create an index for identification of strategically located land. Expert-led workshops were carried out to ascertain criteria for identifying strategically located land and the analytical hierarchy process (AHP) was utilised used to weight the criteria. The study demonstrates that GIS and EO are invaluable tools in facilitating evidence-based decisions for land reform. However, there is need for capacity building on GIS and EO in government departments responsible for land reform and development planning. The study suggests that there is an urgent need to develop sector specific criteria for the identification of strategically located land for inclusive development.

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.

Big earth-observation data analytics for modelling pan-tropical land-use change trajectories for newly deforested areas

NASA Astrophysics Data System (ADS)

Coca Castro, Alejandro; Reymondin, Louis; Rebetez, Julien; Fabio Satizabal Mejia, Hector; Perez-Uribe, Andres; Mulligan, Mark; Smith, Thomas; Hyman, Glenn

2017-04-01

Global land use monitoring is important to the the Sustainable Development Goals (SDGs). The latest advances in storage and manipulation of big earth-observation data have been key to developing multiple operational forest monitoring initiatives such as FORMA, Terra-i and Global Forest Change. Although the data provided by these systems are useful for identifying and estimating newly deforested areas (from 2000), they do not provide details about the land use to which these deforested areas are transitioned. This information is critical to understand the biodiversity and ecosystem services impact of deforestation and the resulting impacts on human wellbeing, locally and downstream. With the aim of contributing to current forest monitoring initiatives, this research presents a set of experimental case studies in Latin America which integrate existing land-change information derived from remote sensing image and aerial photography/ground datasets, high-temporal resolution MODIS data, advanced machine learning (i.e deep learning) and big data technologies (i.e. Hadoop and Spark) to assess land-use change trajectories in newly deforested areas in near real time.

Comparison of microclimate in various land-use systems in Sumatra, Indonesia

NASA Astrophysics Data System (ADS)

Shekhar Badu, Chandra; Meijide, Ana; Gunawan, Dodo; Knohl, Alexander

2017-04-01

Deforestation and land-use changes are ongoing problems for rain forests in Indonesia. The conversion of forests to monocultures of rubber and oil palm plantations reduces not only biodiversity and carbon pools but also affects canopy structure, which is an important determinant of microclimate. There is, however, a lack of quantitative information characterizing the effect of land transformation on microclimate with a systematic experimental design. Here, we report observations microclimatic conditions (air temperature, relative humidity, soil moisture and soil temperature) on a daily, weekly and seasonal basis across four land-use systems (rain forest, jungle rubber, rubber plantation, oil palm plantation) in two near-by landscapes. The data set covers a period of approximately three years from April 2013 to March 2016 and includes one of the strongest El Nino-Southern Oscillation (ENSO) of the last decades. Mean air temperature, soil temperature, relative humidity, and vapour pressure deficit differed significantly between the four land-use systems whereas the mean soil moisture differed significantly between two landscapes. Air temperature, vapour pressure deficit and soil temperature were highest in oil palm and rubber plantations whereas lowest in forest and jungle rubber. Canopy openness was the most dominant control of microclimatic differences across the land-use systems. During the ENSO 2015, a significant increase in mean air temperature, soil temperature and vapour pressure deficit but a decrease in relative air humidity and soil moisture in all four land-use systems was found. The relative effect of ENSO was highest in forest and jungle rubber compared to rubber and oil palm plantations. In conclusion, conversion of forest to rubber and oil palm plantations has led to substantially warmer and drier microclimatic conditions than before.

A Review of Selected MODIS Algorithms, Data Products, and Applications

EPA Science Inventory

The Moderate Resolution Imaging Spectroradiometer (MODIS) is one of the key instruments designed as part of NASA’s Earth Observing System (EOS) to provide long-term global observation of the Earth’s land, ocean, and atmospheric properties (Asrar and Dokken, 1993). The developmen...

Modeling Land Use Change Impacts on Water Resources in a Tropical West African Catchment (dano, Burkina Faso)

NASA Astrophysics Data System (ADS)

Yira, Y.; Diekkrüger, B.; Steup, G.; Bossa, A. Y.

2015-12-01

This study investigates the impacts of land use change on water resources in the Dano catchment, Burkina Faso, using a physically based hydrological simulation model and land use scenarios. Land use dynamic in the catchment was assessed through the analysis of four land use maps corresponding to the land use status in 1990, 2000, 2007 and 2013. A reclassification procedure of the maps permitted to assess the major land use changes in the catchment from 1990 to 2013. The land use maps were used to build five land use scenarios corresponding to different levels of land use change in the catchment. Water balance was simulated by applying the Water flow and balance Simulation Model (WaSiM) using observed discharge, soil moisture, and groundwater level for model calibration and validation. Model statistical quality measures (R2, NSE and KGE) achieved during the calibration and the validation ranged between 0.9 and 0.6 for total discharge, soil moisture, and groundwater level, indicating satisfying to good agreements between observed and simulated variables. After a successful multi-criteria validation the model was run with the land use scenarios. The land use assessment exhibited a decrease of savannah at an annual rate of 2% since 1990. Conversely, cropland and urban areas have increased. Since urban areas occupy only 3% of the catchment in 2013 it can be assumed that savannah was mainly converted to cropland. The increase in cropland area results from the population growth and the farming system in the catchment. A clear increase in total discharge (+17%) and decrease in evapotranspiration (-5%) was observed following land use change in the catchment. A strong relationship was established between savannah degradation, cropland expansion, discharge increase and reduction of evapotranspiration. The increase in total discharge is related to high discharge and peak flow, suggesting (i) an increase in water resources that is not available for plant growth and the population of the catchment and (ii) an alteration of flood risk for both the population within and downstream of the catchment.

Greenhouse gas emissions of different land uses in the delta region of Red River, Vietnam

NASA Astrophysics Data System (ADS)

Zhou, Minghua; Ha, Thu; An, Ngo The; Brüggemann, Nicolas

2017-04-01

Agricultural activities are responsible for up to a third of total anthropogenic GHG emissions. The subtropical/tropical delta areas of the large rivers in Southeast Asia are long-term history agricultural regions in the world. However, due to lack of field measurements, the estimation of the contribution of agro-ecosystems in the subtropical/tropical delta areas to global greenhouse gas emissions remains largely uncertain. Here, we conducted field experiments since January 2016 to quantify greenhouse gases (CO2, CH4 and N2O) emissions from four agricultural land uses of annual rice-rice, rice-vegetable, continuous vegetable system and fish pond in Red River delta region of Vietnam by using the transparent static chamber-gas chromatography technique. Higher N2O emissions were observed in the rice-vegetable and continuous vegetable systems, while lower N2O emissions were observed in the rice-rice and find pond systems. Compared to rice-rice system the cumulative N2O fluxes were on average twenty-fold higher in the rice-vegetable and continuous vegetable systems but significantly lower (75%) in the fish pond. Overall the net CO2 sinks were observed in the rice-rice system while other three land uses of rice-vegetable, continuous vegetable and fish pond acted as the net CO2 sources. The rice-rice and fish pond showed net CH4 emissions while variations of CH4 emissions (i.e. shifting between sources and sinks) along variations of soil moisture and temperature were observed in rice-vegetable and continuous vegetable systems. Compared to rice-rice system, the cumulative CH4 fluxes were significantly decreased by 100% for continuous vegetable system, 94% for rice-vegetable system and 89% for fish pond. Overall, the data suggest that conversion of traditional rice-rice paddy system to rice-vegetable, continuous vegetable system and find pond, which are currently undergoing driven by the economical requests and environmental changes (e.g., salinity intrusion) in this delta region, could alter CH4, CO2 and N2O emissions.

Complementarity of ResourceSat-1 AWiFS and Landsat TM/ETM+ sensors

USGS Publications Warehouse

Goward, S.N.; Chander, G.; Pagnutti, M.; Marx, A.; Ryan, R.; Thomas, N.; Tetrault, R.

2012-01-01

Considerable interest has been given to forming an international collaboration to develop a virtual moderate spatial resolution land observation constellation through aggregation of data sets from comparable national observatories such as the US Landsat, the Indian ResourceSat and related systems. This study explores the complementarity of India's ResourceSat-1 Advanced Wide Field Sensor (AWiFS) with the Landsat 5 Thematic Mapper (TM) and Landsat 7 Enhanced Thematic Mapper Plus (ETM+). The analysis focuses on the comparative radiometry, geometry, and spectral properties of the two sensors. Two applied assessments of these data are also explored to examine the strengths and limitations of these alternate sources of moderate resolution land imagery with specific application domains. There are significant technical differences in these imaging systems including spectral band response, pixel dimensions, swath width, and radiometric resolution which produce differences in observation data sets. None of these differences was found to strongly limit comparable analyses in agricultural and forestry applications. Overall, we found that the AWiFS and Landsat TM/ETM+ imagery are comparable and in some ways complementary, particularly with respect to temporal repeat frequency. We have found that there are limits to our understanding of the AWiFS performance, for example, multi-camera design and stability of radiometric calibration over time, that leave some uncertainty that has been better addressed for Landsat through the Image Assessment System and related cross-sensor calibration studies. Such work still needs to be undertaken for AWiFS and similar observatories that may play roles in the Global Earth Observation System of Systems Land Surface Imaging Constellation.

Seasonal-to-Interannual Variability and Land Surface Processes

NASA Technical Reports Server (NTRS)

Koster, Randal

2004-01-01

Atmospheric chaos severely limits the predictability of precipitation on subseasonal to interannual timescales. Hope for accurate long-term precipitation forecasts lies with simulating atmospheric response to components of the Earth system, such as the ocean, that can be predicted beyond a couple of weeks. Indeed, seasonal forecasts centers now rely heavily on forecasts of ocean circulation. Soil moisture, another slow component of the Earth system, is relatively ignored by the operational seasonal forecasting community. It is starting, however, to garner more attention. Soil moisture anomalies can persist for months. Because these anomalies can have a strong impact on evaporation and other surface energy fluxes, and because the atmosphere may respond consistently to anomalies in the surface fluxes, an accurate soil moisture initialization in a forecast system has the potential to provide additional forecast skill. This potential has motivated a number of atmospheric general circulation model (AGCM) studies of soil moisture and its contribution to variability in the climate system. Some of these studies even suggest that in continental midlatitudes during summer, oceanic impacts on precipitation are quite small relative to soil moisture impacts. The model results, though, are strongly model-dependent, with some models showing large impacts and others showing almost none at all. A validation of the model results with observations thus naturally suggests itself, but this is exceedingly difficult. The necessary contemporaneous soil moisture, evaporation, and precipitation measurements at the large scale are virtually non-existent, and even if they did exist, showing statistically that soil moisture affects rainfall would be difficult because the other direction of causality - wherein rainfall affects soil moisture - is unquestionably active and is almost certainly dominant. Nevertheless, joint analyses of observations and AGCM results do reveal some suggestions of land-atmosphere feedback in the observational record, suggestions that soil moisture can affect precipitation over seasonal timescales and across certain large continental areas. The strength of this observed feedback in nature is not large but is still significant enough to be potentially useful, e.g., for forecasts. This talk will address all of these issues. It will begin with a brief overview of land surface modeling in atmospheric models but will then focus on recent research - using both observations and models - into the impact of land surface processes on variability in the climate system.

Development of the mechanical cryocooler system for the Sea Land Surface Temperature Radiometer

NASA Astrophysics Data System (ADS)

Camilletti, Adam; Burgess, Christopher; Donchev, Anton; Watson, Stuart; Weatherstone Akbar, Shane; Gamo-Albero, Victoria; Romero-Largacha, Victor; Caballero-Olmo, Gema

2014-11-01

The Sea Land Surface Temperature Radiometer is a dual view Earth observing instrument developed as part of the European Global Monitoring for Environment and Security programme. It is scheduled for launch on two satellites, Sentinel 3A and 3B in 2014. The instrument detectors are cooled to below 85 K by two split Stirling Cryocoolers running in hot redundancy. These coolers form part of a cryocooler system that includes a support structure and drive electronics. Aspects of the system design, including control and reduction of exported vibration are discussed; and results, including thermal performance and exported vibration from the Engineering Model Cryooler System test campaign are presented.

Evaluation of the Snow Simulations from the Community Land Model, Version 4 (CLM4)

NASA Technical Reports Server (NTRS)

Toure, Ally M.; Rodell, Matthew; Yang, Zong-Liang; Beaudoing, Hiroko; Kim, Edward; Zhang, Yongfei; Kwon, Yonghwan

2015-01-01

This paper evaluates the simulation of snow by the Community Land Model, version 4 (CLM4), the land model component of the Community Earth System Model, version 1.0.4 (CESM1.0.4). CLM4 was run in an offline mode forced with the corrected land-only replay of the Modern-Era Retrospective Analysis for Research and Applications (MERRA-Land) and the output was evaluated for the period from January 2001 to January 2011 over the Northern Hemisphere poleward of 30 deg N. Simulated snow-cover fraction (SCF), snow depth, and snow water equivalent (SWE) were compared against a set of observations including the Moderate Resolution Imaging Spectroradiometer (MODIS) SCF, the Interactive Multisensor Snow and Ice Mapping System (IMS) snow cover, the Canadian Meteorological Centre (CMC) daily snow analysis products, snow depth from the National Weather Service Cooperative Observer (COOP) program, and Snowpack Telemetry (SNOTEL) SWE observations. CLM4 SCF was converted into snow-cover extent (SCE) to compare with MODIS SCE. It showed good agreement, with a correlation coefficient of 0.91 and an average bias of -1.54 x 10(exp 2) sq km. Overall, CLM4 agreed well with IMS snow cover, with the percentage of correctly modeled snow-no snow being 94%. CLM4 snow depth and SWE agreed reasonably well with the CMC product, with the average bias (RMSE) of snow depth and SWE being 0.044m (0.19 m) and -0.010m (0.04 m), respectively. CLM4 underestimated SNOTEL SWE and COOP snow depth. This study demonstrates the need to improve the CLM4 snow estimates and constitutes a benchmark against which improvement of the model through data assimilation can be measured.

Field-based study of connectivity in an agricultural catchment

NASA Astrophysics Data System (ADS)

Lexartza-Artza, I.; Wainwright, J.

2009-12-01

Field-based studies of hydrological connectivity can provide context-specific knowledge that might both help understand dynamic complex systems and contribute to other synthetic or modelling approaches. The importance of such an understanding of catchment processes and also of the knowledge of catchment connections with water bodies and the changes of concentration with scale for Integrated Catchment Management has been increasingly emphasized. To provide a holistic understanding, approaches to the study of connectivity need to include both structural and functional aspects of the system and must consider the processes taking place within and across different temporal and spatial scales. A semi-quantitative nested approach has been used to investigate connectivity and study the interactions and feedbacks between the factors influencing transfer processes in the Ingbirchworth Catchment, in the uplands of the River Don, England. A series of reconnaissance techniques have been combined with monitoring of aspects such as rainfall, runoff, sediment transfer and soil-moisture distribution from plot to catchment scale and with consideration of linkages between land and water bodies. The temporal aspect has also been considered, with a special focus on the temporal distribution of events and the influence of longer term catchment changes such as those in land use and management practices. A variability of responses has been observed in relation to the characteristics of events, land use and scale of observation, with elements traditionally considered as limiting or enhancing connectivity responding differently under changing conditions. Sediment redistribution, reshaping of structure and consequent reinforcing loops can be observed across all land uses and landscape units, but the relevance it terms of effective connectivity of highly connected patches varies as the scale is increased. The knowledge acquired can contribute to recognise emerging processes significant for active land-water connection and thus provide useful knowledge for decision making.

Upper Blue Nile basin water budget from a multi-model perspective

NASA Astrophysics Data System (ADS)

Jung, Hahn Chul; Getirana, Augusto; Policelli, Frederick; McNally, Amy; Arsenault, Kristi R.; Kumar, Sujay; Tadesse, Tsegaye; Peters-Lidard, Christa D.

2017-12-01

Improved understanding of the water balance in the Blue Nile is of critical importance because of increasingly frequent hydroclimatic extremes under a changing climate. The intercomparison and evaluation of multiple land surface models (LSMs) associated with different meteorological forcing and precipitation datasets can offer a moderate range of water budget variable estimates. In this context, two LSMs, Noah version 3.3 (Noah3.3) and Catchment LSM version Fortuna 2.5 (CLSMF2.5) coupled with the Hydrological Modeling and Analysis Platform (HyMAP) river routing scheme are used to produce hydrological estimates over the region. The two LSMs were forced with different combinations of two reanalysis-based meteorological datasets from the Modern-Era Retrospective analysis for Research and Applications datasets (i.e., MERRA-Land and MERRA-2) and three observation-based precipitation datasets, generating a total of 16 experiments. Modeled evapotranspiration (ET), streamflow, and terrestrial water storage estimates were evaluated against the Atmosphere-Land Exchange Inverse (ALEXI) ET, in-situ streamflow observations, and NASA Gravity Recovery and Climate Experiment (GRACE) products, respectively. Results show that CLSMF2.5 provided better representation of the water budget variables than Noah3.3 in terms of Nash-Sutcliffe coefficient when considering all meteorological forcing datasets and precipitation datasets. The model experiments forced with observation-based products, the Climate Hazards group Infrared Precipitation with Stations (CHIRPS) and the Tropical Rainfall Measuring Mission (TRMM) Multi-Satellite Precipitation Analysis (TMPA), outperform those run with MERRA-Land and MERRA-2 precipitation. The results presented in this paper would suggest that the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System incorporate CLSMF2.5 and HyMAP routing scheme to better represent the water balance in this region.

Use of remote sensing for land use policy formulation

NASA Technical Reports Server (NTRS)

1987-01-01

The overall objectives and strategies of the Center for Remote Sensing remain to provide a center for excellence for multidisciplinary scientific expertise to address land-related global habitability and earth observing systems scientific issues. Specific research projects that were underway during the final contract period include: digital classification of coniferous forest types in Michigan's northern lower peninsula; a physiographic ecosystem approach to remote classification and mapping; land surface change detection and inventory; analysis of radiant temperature data; and development of methodologies to assess possible impacts of man's changes of land surface on meteorological parameters. Significant progress in each of the five project areas has occurred. Summaries on each of the projects are provided.

Global Soil Moisture from the Aquarius/SAC-D Satellite: Description and Initial Assessment

NASA Technical Reports Server (NTRS)

Bindlish, Rajat; Jackson, Thomas; Cosh, Michael; Zhao, Tianjie; O'Neil, Peggy

2015-01-01

Aquarius satellite observations over land offer a new resource for measuring soil moisture from space. Although Aquarius was designed for ocean salinity mapping, our objective in this investigation is to exploit the large amount of land observations that Aquarius acquires and extend the mission scope to include the retrieval of surface soil moisture. The soil moisture retrieval algorithm development focused on using only the radiometer data because of the extensive heritage of passive microwave retrieval of soil moisture. The single channel algorithm (SCA) was implemented using the Aquarius observations to estimate surface soil moisture. Aquarius radiometer observations from three beams (after bias/gain modification) along with the National Centers for Environmental Prediction model forecast surface temperatures were then used to retrieve soil moisture. Ancillary data inputs required for using the SCA are vegetation water content, land surface temperature, and several soil and vegetation parameters based on land cover classes. The resulting global spatial patterns of soil moisture were consistent with the precipitation climatology and with soil moisture from other satellite missions (Advanced Microwave Scanning Radiometer for the Earth Observing System and Soil Moisture Ocean Salinity). Initial assessments were performed using in situ observations from the U.S. Department of Agriculture Little Washita and Little River watershed soil moisture networks. Results showed good performance by the algorithm for these land surface conditions for the period of August 2011-June 2013 (rmse = 0.031 m(exp 3)/m(exp 3), Bias = -0.007 m(exp 3)/m(exp 3), and R = 0.855). This radiometer-only soil moisture product will serve as a baseline for continuing research on both active and combined passive-active soil moisture algorithms. The products are routinely available through the National Aeronautics and Space Administration data archive at the National Snow and Ice Data Center.

Study on a Dynamic Vegetation Model for Simulating Land Surface Flux Exchanges at Lien-Hua-Chih Flux Observation Site in Taiwan

NASA Astrophysics Data System (ADS)

Yeh, T. Y.; Li, M. H.; Chen, Y. Y.; Ryder, J.; McGrath, M.; Otto, J.; Naudts, K.; Luyssaert, S.; MacBean, N.; Bastrikov, V.

2016-12-01

Dynamic vegetation model ORCHIDEE (Organizing Carbon and Hydrology In Dynamic EcosystEms) is a state of art land surface component of the IPSL (Institute Pierre Simon Laplace) Earth System Model. It has been used world-wide to investigate variations of water, carbon, and energy exchanges between the land surface and the atmosphere. In this study we assessed the applicability of using ORCHIDEE-CAN, a new feature with 3-D CANopy structure (Naudts et al., 2015; Ryder et al., 2016), to simulate surface fluxes measured at tower-based eddy covariance fluxes at the Lien-Hua-Chih experimental watershed in Taiwan. The atmospheric forcing including radiation, air temperature, wind speed, and the dynamics of vertical canopy structure for driving the model were obtained from the observations site. Suitable combinations of default plant function types were examined to meet in-situ observations of soil moisture and leaf area index from 2009 to 2013. The simulated top layer soil moisture was ranging from 0.1 to 0.4 and total leaf area was ranging from 2.2 to 4.4, respectively. A sensitivity analysis was performed to investigate the sensitive of model parameters and model skills of ORCHIDEE-CAN on capturing seasonal variations of surface fluxes. The most sensitive parameters were suggested and calibrated by an automatic data assimilation tool ORCHDAS (ORCHIDEE Data Assimilation Systems; http://orchidas.lsce.ipsl.fr/). Latent heat, sensible heat, and carbon fluxes simulated by the model were compared with long-term observations at the site. ORCHIDEE-CAN by making use of calibrated surface parameters was used to study variations of land-atmosphere interactions on a variety of temporal scale in associations with changes in both land and atmospheric conditions. Ref: Naudts, K., et al.,: A vertically discretised canopy description for ORCHIDEE (SVN r2290) and the modifications to the energy, water and carbon fluxes, Geoscientific Model Development, 8, 2035-2065, doi:10.5194/gmd-8-2035-2015,2015. Ryder, J., et al. : A multi-layer land surface energy budget model for implicit coupling with global atmospheric simulations, Geoscientific Model Development, 9, 223-245, doi:10.5194/gmd-9-223-2016, 2016.

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.

Hydro-meteorological processes on the Qinghai - Tibet Plateau observed from space

NASA Astrophysics Data System (ADS)

Menenti, Massimo; Colin, Jerome; Jia, Li; D'Urso, Guido; Foken, Thomas; Immerzeel, Walter; Jha, Ramakar; Liu, Qinhuo; Liu, Changming; Ma, Yaoming; Sobrino, Jose Antonio; Yan, Guangjian; Pelgrum, Henk; Porcu, Federico; Wang, Jian; Wang, Jiemin; Shen, Xueshun; Su, Zhongbo; Ueno, Kenichi

2014-05-01

The Qinghai - Tibet Plateau is characterized by a significant intra-annual variability and spatial heterogeneity of surface conditions. Snow and vegetation cover, albedo, surface temperature and wetness change very significantly during the year and from place to place. The influence of temporal changes on convective events and the onset of the monsoon has been documented by ground based measurements of land - atmosphere exchanges of heat and water. The state of the land surface over the entire Plateau can be determined by space observation of surface albedo, temperature, snow and vegetation cover and soil moisture. Fully integrated use of satellite and ground observations is necessary to support water resources management in SE Asia and to clarify the roles of the interactions between the land surface and the atmosphere over the Tibetan Plateau in the Asian monsoon system. New or significantly improved algorithms have been developed and evaluated against ground measurements. Variables retrieved include land surface properties, rain rate, aerosol optical depth, water vapour, snow cover and water equivalent, soil moisture and lake level. The three years time series of gap-free daily and hourly evaporation derived from geostationary data collected by the FY-2D satellite was a major achievement. The hydrologic modeling system has been implemented and applied to the Qinghai Tibet Plateau and the headwaters of the major rivers in South and East Asia. Case studies on response of atmospheric circulation and specifically of convective activity to land surface conditions have been completed and the controlling land surface conditions and processes have been documented. Two new drought indicators have been developed: Normalized Temperature Anomaly Index (NTAI) and Normalized Vegetation Anomaly Index (NVAI). Case study in China and India showed that these indicators capture effectively drought severity and evolution. A new method has been developed for monitoring and early warning of flooded areas at the regional scale.

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

Assessment of MERRA-2 Land Surface Energy Flux Estimates

NASA Technical Reports Server (NTRS)

Draper, Clara; Reichle, Rolf; Koster, Randal

2017-01-01

In MERRA-2, observed precipitation is inserted in place of model-generated precipitation at the land surface. The use of observed precipitation was originally developed for MERRA-Land(a land-only replay of MERRA with model-generated precipitation replaced with observations).Previously shown that the land hydrology in MERRA-2 and MERRA-Land is better than MERRA. We test whether the improved land surface hydrology in MERRA-2 leads to the expected improvements in the land surface energy fluxes and 2 m air temperatures (T2m).

Video guidance, landing, and imaging systems

NASA Technical Reports Server (NTRS)

Schappell, R. T.; Knickerbocker, R. L.; Tietz, J. C.; Grant, C.; Rice, R. B.; Moog, R. D.

1975-01-01

The adaptive potential of video guidance technology for earth orbital and interplanetary missions was explored. The application of video acquisition, pointing, tracking, and navigation technology was considered to three primary missions: planetary landing, earth resources satellite, and spacecraft rendezvous and docking. It was found that an imaging system can be mechanized to provide a spacecraft or satellite with a considerable amount of adaptability with respect to its environment. It also provides a level of autonomy essential to many future missions and enhances their data gathering ability. The feasibility of an autonomous video guidance system capable of observing a planetary surface during terminal descent and selecting the most acceptable landing site was successfully demonstrated in the laboratory. The techniques developed for acquisition, pointing, and tracking show promise for recognizing and tracking coastlines, rivers, and other constituents of interest. Routines were written and checked for rendezvous, docking, and station-keeping functions.

Development of Compact Seafloor Cabled Seismic and Tsunami Observation System Using ICT and Installation Plan to Off-Sanriku Region, Japan

NASA Astrophysics Data System (ADS)

Shinohara, M.; Yamada, T.; Sakai, S.; Shiobara, H.; Kanazawa, T.

2014-12-01

A seismic and tsunami observation system using seafloor optical fiber had been installed off Sanriku, northeastern Japan in 1996. The objectives of the system are to obtain exact seismic activity related to plate subduction and to observe tsunami on seafloor. The continuous real-time observation has been carried out since the installation. In March 2011, the Tohoku earthquake occurred at the plate boundary near the Japan Trench, and the system recorded seismic waves and tsunamis by the mainshock. These data are useful to obtain accurate position of the source faults and source region of tsunami generated by the event. However, the landing station of the system was damaged by huge tsunami, and the observation was suspended. Because the real-time seafloor observation by cabled system is important in this region, we decide to reconstruct a landing station and install newly developed Ocean Bottom Cabled Seismic and Tsunami (OBCST) observation system for additional observation and/or replacement of the existing system. From 2005, we have been developed the new compact Ocean Bottom Cabled Seismometer (OBCS) system using Information and Communication Technology (ICT). Our system is characterized by securement of reliability by using TCP/IP technology and down-sizing of an observation node using up-to-date electronics technology. In 2010, the first OBCS was installed near Awashima-island in the Japan Sea, and is being operated continuously. The new OBCST system is placed as the second generation of our system, and has two types of observation nodes. Both types have accelerometers as seismic sensors. One type of observation nodes equips a crystal oscillator type pressure gauge as tsunami sensor. Another type has an external port for additional observation sensor by using Power over Ethernet technology. Clocks in observation nodes can be synchronized through TCP/IP protocol with an accuracy of 300 ns (IEEE 1588). A simple canister for tele-communication seafloor cable is adopted for the observation node, and has diameter of 26 cm and length of about 1.3 m. At the present, we are producing a practical OBCST system which has total length of approximately 100 km and three observation nodes. We have a plan to install the practical system in 2015.

Satellites monitor Atlanta regional development

USGS Publications Warehouse

Todd, William J.; Blackmon, C.C.; Rudasill, R.G.

1979-01-01

Since the adoption of a Regional Development Plan in 1975, the Atlanta Regional Commission has investigated methods for monitoring regional development patterns in a periodic, efficient manner. A promising approach appears to be the use of Landsat satellite data. In cooperation with the Earth Resources Observation Systems (EROS) Data Center, the commission used machine processing of digital temporal overlays of Landsat data collected in 1972, 1974 and 1976 to detect land use and land cover changes in the Atlanta metropolitan area. Results of the analysis revealed the conversion of forested and open space areas to residential, commercial and industrial land use in the urban-rural fringe zone from 1972 to 1974 and from 1974 to 1976. The study indicated that a land use and land cover change-detection program may be used to revise small-area forecasts of land use, population and employment made by planning models.

Theoretical Accuracy of Global Snow-Cover Mapping Using Satellite Data in the Earth Observing System (EOS) Era

NASA Technical Reports Server (NTRS)

Hall, D. K.; Foster, J. L.; Salomonson, V. V.; Klein, A. G.; Chien, J. Y. L.

1998-01-01

Following the launch of the Earth Observing System first morning (EOS-AM1) satellite, daily, global snow-cover mapping will be performed automatically at a spatial resolution of 500 m, cloud-cover permitting, using Moderate Resolution Imaging Spectroradiometer (MODIS) data. A technique to calculate theoretical accuracy of the MODIS-derived snow maps is presented. Field studies demonstrate that under cloud-free conditions when snow cover is complete, snow-mapping errors are small (less than 1%) in all land covers studied except forests where errors are greater and more variable. The theoretical accuracy of MODIS snow-cover maps is largely determined by percent forest cover north of the snowline. Using the 17-class International Geosphere-Biosphere Program (IGBP) land-cover maps of North America and Eurasia, the Northern Hemisphere is classified into seven land-cover classes and water. Snow-mapping errors estimated for each of the seven land-cover classes are extrapolated to the entire Northern Hemisphere for areas north of the average continental snowline for each month. Average monthly errors for the Northern Hemisphere are expected to range from 5 - 10%, and the theoretical accuracy of the future global snow-cover maps is 92% or higher. Error estimates will be refined after the first full year that MODIS data are available.

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.

Land Boundary Conditions for the Goddard Earth Observing System Model Version 5 (GEOS-5) Climate Modeling System: Recent Updates and Data File Descriptions

NASA Technical Reports Server (NTRS)

Mahanama, Sarith P.; Koster, Randal D.; Walker, Gregory K.; Takacs, Lawrence L.; Reichle, Rolf H.; De Lannoy, Gabrielle; Liu, Qing; Zhao, Bin; Suarez, Max J.

2015-01-01

The Earths land surface boundary conditions in the Goddard Earth Observing System version 5 (GEOS-5) modeling system were updated using recent high spatial and temporal resolution global data products. The updates include: (i) construction of a global 10-arcsec land-ocean lakes-ice mask; (ii) incorporation of a 10-arcsec Globcover 2009 land cover dataset; (iii) implementation of Level 12 Pfafstetter hydrologic catchments; (iv) use of hybridized SRTM global topography data; (v) construction of the HWSDv1.21-STATSGO2 merged global 30 arc second soil mineral and carbon data in conjunction with a highly-refined soil classification system; (vi) production of diffuse visible and near-infrared 8-day MODIS albedo climatologies at 30-arcsec from the period 2001-2011; and (vii) production of the GEOLAND2 and MODIS merged 8-day LAI climatology at 30-arcsec for GEOS-5. The global data sets were preprocessed and used to construct global raster data files for the software (mkCatchParam) that computes parameters on catchment-tiles for various atmospheric grids. The updates also include a few bug fixes in mkCatchParam, as well as changes (improvements in algorithms, etc.) to mkCatchParam that allow it to produce tile-space parameters efficiently for high resolution AGCM grids. The update process also includes the construction of data files describing the vegetation type fractions, soil background albedo, nitrogen deposition and mean annual 2m air temperature to be used with the future Catchment CN model and the global stream channel network to be used with the future global runoff routing model. This report provides detailed descriptions of the data production process and data file format of each updated data set.

Impact of Calibrated Land Surface Model Parameters on the Accuracy and Uncertainty of Land-Atmosphere Coupling in WRF Simulations

NASA Technical Reports Server (NTRS)

Santanello, Joseph A., Jr.; Kumar, Sujay V.; Peters-Lidard, Christa D.; Harrison, Ken; Zhou, Shujia

2012-01-01

Land-atmosphere (L-A) interactions play a critical role in determining the diurnal evolution of both planetary boundary layer (PBL) and land surface temperature and moisture budgets, as well as controlling feedbacks with clouds and precipitation that lead to the persistence of dry and wet regimes. Recent efforts to quantify the strength of L-A coupling in prediction models have produced diagnostics that integrate across both the land and PBL components of the system. In this study, we examine the impact of improved specification of land surface states, anomalies, and fluxes on coupled WRF forecasts during the summers of extreme dry (2006) and wet (2007) land surface conditions in the U.S. Southern Great Plains. The improved land initialization and surface flux parameterizations are obtained through the use of a new optimization and uncertainty estimation module in NASA's Land Information System (LIS-OPT/UE), whereby parameter sets are calibrated in the Noah land surface model and classified according to a land cover and soil type mapping of the observation sites to the full model domain. The impact of calibrated parameters on the a) spinup of the land surface used as initial conditions, and b) heat and moisture states and fluxes of the coupled WRF simulations are then assessed in terms of ambient weather and land-atmosphere coupling along with measures of uncertainty propagation into the forecasts. In addition, the sensitivity of this approach to the period of calibration (dry, wet, average) is investigated. Finally, tradeoffs of computational tractability and scientific validity, and the potential for combining this approach with satellite remote sensing data are also discussed.

Land cover mapping of North and Central America—Global Land Cover 2000

USGS Publications Warehouse

Latifovic, Rasim; Zhu, Zhi-Liang

2004-01-01

The Land Cover Map of North and Central America for the year 2000 (GLC 2000-NCA), prepared by NRCan/CCRS and USGS/EROS Data Centre (EDC) as a regional component of the Global Land Cover 2000 project, is the subject of this paper. A new mapping approach for transforming satellite observations acquired by the SPOT4/VGTETATION (VGT) sensor into land cover information is outlined. The procedure includes: (1) conversion of daily data into 10-day composite; (2) post-seasonal correction and refinement of apparent surface reflectance in 10-day composite images; and (3) extraction of land cover information from the composite images. The pre-processing and mosaicking techniques developed and used in this study proved to be very effective in removing cloud contamination, BRDF effects, and noise in Short Wave Infra-Red (SWIR). The GLC 2000-NCA land cover map is provided as a regional product with 28 land cover classes based on modified Federal Geographic Data Committee/Vegetation Classification Standard (FGDC NVCS) classification system, and as part of a global product with 22 land cover classes based on Land Cover Classification System (LCCS) of the Food and Agriculture Organisation. The map was compared on both areal and per-pixel bases over North and Central America to the International Geosphere–Biosphere Programme (IGBP) global land cover classification, the University of Maryland global land cover classification (UMd) and the Moderate Resolution Imaging Spectroradiometer (MODIS) Global land cover classification produced by Boston University (BU). There was good agreement (79%) on the spatial distribution and areal extent of forest between GLC 2000-NCA and the other maps, however, GLC 2000-NCA provides additional information on the spatial distribution of forest types. The GLC 2000-NCA map was produced at the continental level incorporating specific needs of the region.

The Significance of Land-Atmosphere Processes in the Earth System

NASA Astrophysics Data System (ADS)

Suni, T.; Kulmala, M. T.; Guenther, A. B.

2012-12-01

The land-atmosphere interface is where humans primarily operate. Humans modify the land surface in many ways that influence the fluxes of energy and trace gases between land and atmosphere. Their emissions change the chemical composition of the atmosphere and anthropogenic aerosols change the radiative balance of the globe directly by scattering sunlight back to space and indirectly by changing the properties of clouds. Feedback loops among all these processes, land, the atmosphere, and biogeochemical cycles of nutrients and trace gases extend the human influence even further. Over the last decade, the importance of land-atmosphere processes and feedbacks in the Earth System has been shown on many levels and with multiple approaches, and a number of publications have shown the crucial role of the terrestrial ecosystems as regulators of climate [1-6]. Modellers have clearly shown the effect of missing land cover changes and other feedback processes and regional characteristics in current climate models and recommended actions to improve them [7-11]. Unprecedented insights of the long-term net impacts of aerosols on clouds and precipitation have also been provided [12-14]. Land-cover change has been emphasized with model intercomparison projects that showed that realistic land-use representation was essential in land surface modelling [11, 15]. Crucially important tools in this research have been the networks of long-term flux stations and large-scale land-atmosphere observation platforms that are also beginning to combine remote sensing techniques with ground observations [16-20]. Human influence has always been an important part of land-atmosphere science but in order to respond to the new challenges of global sustainability, closer ties with social science and economics groups will be necessary to produce realistic estimates of land use and anthropogenic emissions by analysing future population increase, migration patterns, food production allocation, land management practices, energy production, industrial development, and urbanization. Emphasis should be placed on, for instance, new observation networks incorporating remote sensing techniques with ground-based observations; the role of land-cover changes in modulating carbon, nitrogen, and hydrological cycles and, consequently, atmospheric chemistry, aerosol dynamics, and climate; regional (high-latitude) processes and their influence on global simulations; and interactions among anthropogenic and biogenic aerosols, clouds, and climate. 1. Ciais Ph 2005 Nature 2. Kulmala M et al 2004 Atmos Chem Phys 3. Philippon N et al 2005 J Geophys Res 4. Arneth A et al 2010a Nature Geoscience 5. Ganzeveld L et al 2010 J Geophys Res 6. Teuling A et al. 2010 Nature Geoscience 7. Arneth A et al 2010b Biogeosciences 8. Bonan GB et al. 2011 J Geophys Res 9. Davin EL and Seneviratne SI 2011 Biogeosciences 10. Pitman AJ et al 2011 Int J Clim 11. de Noblet-Ducoudré N et al 2012 J Clim 12. Rosenfeld D et al. 2008 Science 13. Stevens B and Feingold G 2009 Nature 14. Li Z et al 2011 Nature Geoscience 15. Pitman AJ et al 2009 Geophys Res Let 16. Baldocchi DD et al. 2005 Int J Biomet 17. Hari P et al 2009 Bor Env Res 18. Guenther A et al 2011 Bor Env Res 19. de Leeuw G et al. 2011 Biogeosciences 20. Jung M et al 2011 J Geophys Res

Improving precipitation simulation from updated surface characteristics in South America

NASA Astrophysics Data System (ADS)

Pereira, Gabriel; Silva, Maria Elisa Siqueira; Moraes, Elisabete Caria; Chiquetto, Júlio Barboza; da Silva Cardozo, Francielle

2017-07-01

Land use and land cover maps and their physical-chemical and biological properties are important variables in the numerical modeling of Earth systems. In this context, the main objective of this study is to analyze the improvements resulting from the land use and land cover map update in numerical simulations performed using the Regional Climate Model system version 4 (RegCM4), as well as the seasonal variations of physical parameters used by the Biosphere Atmosphere Transfer Scheme (BATS). In general, the update of the South America 2007 land use and land cover map, used by the BATS, improved the simulation of precipitation by 10 %, increasing the mean temporal correlation coefficient, compared to observed data, from 0.84 to 0.92 (significant at p < 0.05, Student's t test). Correspondingly, the simulations performed with adjustments in maximum fractional vegetation cover, in visible and shortwave infrared reflectance, and in the leaf area index, showed a good agreement for maximum and minimum temperature, with values closer to observed data. The changes in physical parameters and land use updating in BATS/RegCM4 reduced overestimation of simulated precipitation from 19 to 7 % (significant at p < 0.05, Student's t test). Regarding evapotranspiration and precipitation, the most significant differences due to land use updating were located (1) in the Amazon deforestation arc; (2) around the Brazil-Bolivia border (in the Brazilian Pantanal wetlands); (3) in the Northeast region of Brazil; (4) in northwestern Paraguay; and (5) in the River Plate Basin, in Argentina. Moreover, the main precipitation differences between sensitivity and control experiments occurred during the rainy months in central-north South America (October to March). These were associated with a displacement in the South Atlantic convergence zone (SACZ) positioning, presenting a spatial pattern of alternated areas with higher and lower precipitation rates. These important differences occur due to the replacement of tropical rainforest for pasture and agriculture and the replacement of agricultural areas for pasture, scrubland, and deciduous forest.

Landsat continuity: Issues and opportunities for land cover monitoring

USGS Publications Warehouse

Wulder, M.A.; White, Joanne C.; Goward, S.N.; Masek, J.G.; Irons, J.R.; Herold, M.; Cohen, W.B.; Loveland, Thomas R.; Woodcock, C.E.

2008-01-01

Initiated in 1972, the Landsat program has provided a continuous record of earth observation for 35 years. The assemblage of Landsat spatial, spectral, and temporal resolutions, over a reasonably sized image extent, results in imagery that can be processed to represent land cover over large areas with an amount of spatial detail that is absolutely unique and indispensable for monitoring, management, and scientific activities. Recent technical problems with the two existing Landsat satellites, and delays in the development and launch of a successor, increase the likelihood that a gap in Landsat continuity may occur. In this communication, we identify the key features of the Landsat program that have resulted in the extensive use of Landsat data for large area land cover mapping and monitoring. We then augment this list of key features by examining the data needs of existing large area land cover monitoring programs. Subsequently, we use this list as a basis for reviewing the current constellation of earth observation satellites to identify potential alternative data sources for large area land cover applications. Notions of a virtual constellation of satellites to meet large area land cover mapping and monitoring needs are also presented. Finally, research priorities that would facilitate the integration of these alternative data sources into existing large area land cover monitoring programs are identified. Continuity of the Landsat program and the measurements provided are critical for scientific, environmental, economic, and social purposes. It is difficult to overstate the importance of Landsat; there are no other systems in orbit, or planned for launch in the short-term, that can duplicate or approach replication, of the measurements and information conferred by Landsat. While technical and political options are being pursued, there is no satellite image data stream poised to enter the National Satellite Land Remote Sensing Data Archive should system failures occur to Landsat-5 and -7.

Effects of Land Use Change on Tropical Coastal Systems are Exacerbated by the Decline of Marine Mega-Herbivores

NASA Astrophysics Data System (ADS)

Lamers, L. P.; Christianen, M. J.; Govers, L. L.; Kiswara, W.; Bouma, T.; Roelofs, J. G.; Van Katwijk, M. M.

2011-12-01

Land use changes in tropical regions such as deforestation, mining activities, and shrimp farming, not only affect freshwater and terrestrial ecosystems, but also have a strong impact on coastal marine ecosystems. The increased influx of sediments and nutrients affects these ecosystems in multiple ways. Seagrass meadows that line coastal marine ecosystems provide important ecosystem services, e.g. sediment trapping, coastal protection and fisheries. Based on studies in East Kalimantan (Indonesia) we have shown that seagrass meadow parameters may provide more reliable indicators of land use change than the sampling of either marine sediments or water quality chemical parameters. Observations of changes in ecosystem functioning are particularly valuable for those areas where flux values are lacking and rapid surveys are needed. Time series of estuarine seagrass transects can show not only the intensity, but also the radius of action of land use change on coastal marine systems. Marine mega-herbivores pose a strong top-down control in seagrass ecosystems. We will provide a conceptual model, based on experimental evidence, to show that the global decline of marine mega-herbivore populations (as a result of large-scale poaching) may decrease the resilience of seagrass systems to increased anthropogenic forcing including land use changes. These outcomes not only urge the need for better regulation of land use change, but also for the establishment of marine protected areas (MPA's) in tropical coastal regions.

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.

All Recent Mars Landers Have Landed Downrange - Are Mars Atmosphere Models Mis-Predicting Density?

NASA Technical Reports Server (NTRS)

Desai, Prasun N.

2008-01-01

All recent Mars landers (Mars Pathfinder, the two Mars Exploration Rovers Spirit and Opportunity, and the Mars Phoenix Lander) have landed further downrange than their pre-entry predictions. Mars Pathfinder landed 27 km downrange of its prediction [1], Spirit and Opportunity landed 13.4 km and 14.9 km, respectively, downrange from their predictions [2], and Phoenix landed 21 km downrange from its prediction [3]. Reconstruction of their entries revealed a lower density profile than the best a priori atmospheric model predictions. Do these results suggest that there is a systemic issue in present Mars atmosphere models that predict a higher density than observed on landing day? Spirit Landing: The landing location for Spirit was 13.4 km downrange of the prediction as shown in Fig. 1. The navigation errors upon Mars arrival were very small [2]. As such, the entry interface conditions were not responsible for this downrange landing. Consequently, experiencing a lower density during the entry was the underlying cause. The reconstructed density profile that Spirit experienced is shown in Fig. 2, which is plotted as a fraction of the pre-entry baseline prediction that was used for all the entry, descent, and landing (EDL) design analyses. The reconstructed density is observed to be less dense throughout the descent reaching a maximum reduction of 15% at 21 km. This lower density corresponded to approximately a 1- low profile relative to the dispersions predicted. Nearly all the deceleration during the entry occurs within 10- 50 km. As such, prediction of density within this altitude band is most critical for entry flight dynamics analyses and design (e.g., aerodynamic and aerothermodynamic predictions, landing location, etc.).

Confounding factors in determining causal soil moisture-precipitation feedback

NASA Astrophysics Data System (ADS)

Tuttle, Samuel E.; Salvucci, Guido D.

2017-07-01

Identification of causal links in the land-atmosphere system is important for construction and testing of land surface and general circulation models. However, the land and atmosphere are highly coupled and linked by a vast number of complex, interdependent processes. Statistical methods, such as Granger causality, can help to identify feedbacks from observational data, independent of the different parameterizations of physical processes and spatiotemporal resolution effects that influence feedbacks in models. However, statistical causal identification methods can easily be misapplied, leading to erroneous conclusions about feedback strength and sign. Here, we discuss three factors that must be accounted for in determination of causal soil moisture-precipitation feedback in observations and model output: seasonal and interannual variability, precipitation persistence, and endogeneity. The effect of neglecting these factors is demonstrated in simulated and observational data. The results show that long-timescale variability and precipitation persistence can have a substantial effect on detected soil moisture-precipitation feedback strength, while endogeneity has a smaller effect that is often masked by measurement error and thus is more likely to be an issue when analyzing model data or highly accurate observational data.

Landsat-based Earth Observations and Crowd-sourced Data Provide Near Real-time Monitoring of Chimpanzee Habitat

NASA Astrophysics Data System (ADS)

Nackoney, J.; Pintea, L.; Jantz, S.; Hansen, M.

2015-12-01

The endangered chimpanzee (Pan troglodytes) is threatened by habitat loss from resource extraction and land conversion, as well as hunting, disease and the illegal pet trade. It has been estimated that more than 70% of chimpanzee's tropical forest habitats in Africa are now threatened by land use change. Recent developments in remote sensing and cloud computing enable the use of satellite observations to provide a synoptic view of chimpanzee habitats at finer spatial and temporal resolutions that are locally relevant and consistent across the entire species' range. We present a practical Decision Support System to be used by the Jane Goodall Institute and partners to annually monitor and forecast chimpanzee habitat health in Africa. The system integrates Earth observations from 30-meter resolution Landsat data with a species-specific habitat model and a model forecasting future land use change, enhanced by crowd-sourced field data collected by local communities and rangers using the Open Data Kit app and Android mobile smartphones and tablets. While coarser-scale and static chimpanzee habitat models have been previously developed, this project is the first to develop a dynamic monitoring system updated annually via Earth observations data that will systematically monitor threats and changes in habitat over time. Since the chimpanzee is an important keystone, flagship and umbrella species, an annual chimpanzee habitat health index would support conservation goals of other species within its large 2.5 million sq. km range and could be an important indicator of overall ecosystem health of tropical forests in Africa.

An Investigation of Candidate Sensor-Observable Wake Vortex Strength Parameters for the NASA Aircraft Vortex Spacing System (AVOSS)

NASA Technical Reports Server (NTRS)

Tatnall, Chistopher R.

1998-01-01

The counter-rotating pair of wake vortices shed by flying aircraft can pose a threat to ensuing aircraft, particularly on landing approach. To allow adequate time for the vortices to disperse/decay, landing aircraft are required to maintain certain fixed separation distances. The Aircraft Vortex Spacing System (AVOSS), under development at NASA, is designed to prescribe safe aircraft landing approach separation distances appropriate to the ambient weather conditions. A key component of the AVOSS is a ground sensor, to ensure, safety by making wake observations to verify predicted behavior. This task requires knowledge of a flowfield strength metric which gauges the severity of disturbance an encountering aircraft could potentially experience. Several proposed strength metric concepts are defined and evaluated for various combinations of metric parameters and sensor line-of-sight elevation angles. Representative populations of generating and following aircraft types are selected, and their associated wake flowfields are modeled using various wake geometry definitions. Strength metric candidates are then rated and compared based on the correspondence of their computed values to associated aircraft response values, using basic statistical analyses.

Moving towards Hyper-Resolution Hydrologic Modeling

NASA Astrophysics Data System (ADS)

Rouf, T.; Maggioni, V.; Houser, P.; Mei, Y.

2017-12-01

Developing a predictive capability for terrestrial hydrology across landscapes, with water, energy and nutrients as the drivers of these dynamic systems, faces the challenge of scaling meter-scale process understanding to practical modeling scales. Hyper-resolution land surface modeling can provide a framework for addressing science questions that we are not able to answer with coarse modeling scales. In this study, we develop a hyper-resolution forcing dataset from coarser resolution products using a physically based downscaling approach. These downscaling techniques rely on correlations with landscape variables, such as topography, roughness, and land cover. A proof-of-concept has been implemented over the Oklahoma domain, where high-resolution observations are available for validation purposes. Hourly NLDAS (North America Land Data Assimilation System) forcing data (i.e., near-surface air temperature, pressure, and humidity) have been downscaled to 500m resolution over the study area for 2015-present. Results show that correlation coefficients between the downscaled temperature dataset and ground observations are consistently higher than the ones between the NLDAS temperature data at their native resolution and ground observations. Not only correlation coefficients are higher, but also the deviation around the 1:1 line in the density scatterplots is smaller for the downscaled dataset than the original one with respect to the ground observations. Results are therefore encouraging as they demonstrate that the 500m temperature dataset has a good agreement with the ground information and can be adopted to force the land surface model for soil moisture estimation. The study has been expanded to wind speed and direction, incident longwave and shortwave radiation, pressure, and precipitation. Precipitation is well known to vary dramatically with elevation and orography. Therefore, we are pursuing a downscaling technique based on both topographical and vegetation characteristics.

Sequential assimilation of satellite-derived vegetation and soil moisture products using SURFEX_v8.0: LDAS-Monde assessment over the Euro-Mediterranean area

NASA Astrophysics Data System (ADS)

Albergel, Clément; Munier, Simon; Leroux, Delphine Jennifer; Dewaele, Hélène; Fairbairn, David; Lavinia Barbu, Alina; Gelati, Emiliano; Dorigo, Wouter; Faroux, Stéphanie; Meurey, Catherine; Le Moigne, Patrick; Decharme, Bertrand; Mahfouf, Jean-Francois; Calvet, Jean-Christophe

2017-10-01

In this study, a global land data assimilation system (LDAS-Monde) is applied over Europe and the Mediterranean basin to increase monitoring accuracy for land surface variables. LDAS-Monde is able to ingest information from satellite-derived surface soil moisture (SSM) and leaf area index (LAI) observations to constrain the interactions between soil-biosphere-atmosphere (ISBA, Interactions between Soil, Biosphere and Atmosphere) land surface model (LSM) coupled with the CNRM (Centre National de Recherches Météorologiques) version of the Total Runoff Integrating Pathways (ISBA-CTRIP) continental hydrological system. It makes use of the CO2-responsive version of ISBA which models leaf-scale physiological processes and plant growth. Transfer of water and heat in the soil rely on a multilayer diffusion scheme. SSM and LAI observations are assimilated using a simplified extended Kalman filter (SEKF), which uses finite differences from perturbed simulations to generate flow dependence between the observations and the model control variables. The latter include LAI and seven layers of soil (from 1 to 100 cm depth). A sensitivity test of the Jacobians over 2000-2012 exhibits effects related to both depth and season. It also suggests that observations of both LAI and SSM have an impact on the different control variables. From the assimilation of SSM, the LDAS is more effective in modifying soil moisture (SM) from the top layers of soil, as model sensitivity to SSM decreases with depth and has almost no impact from 60 cm downwards. From the assimilation of LAI, a strong impact on LAI itself is found. The LAI assimilation impact is more pronounced in SM layers that contain the highest fraction of roots (from 10 to 60 cm). The assimilation is more efficient in summer and autumn than in winter and spring. Results shows that the LDAS works well constraining the model to the observations and that stronger corrections are applied to LAI than to SM. A comprehensive evaluation of the assimilation impact is conducted using (i) agricultural statistics over France, (ii) river discharge observations, (iii) satellite-derived estimates of land evapotranspiration from the Global Land Evaporation Amsterdam Model (GLEAM) project and (iv) spatially gridded observation-based estimates of upscaled gross primary production and evapotranspiration from the FLUXNET network. Comparisons with those four datasets highlight neutral to highly positive improvement.

Land system change and food security: towards multi-scale land system solutions☆

PubMed Central

Verburg, Peter H; Mertz, Ole; Erb, Karl-Heinz; Haberl, Helmut; Wu, Wenbin

2013-01-01

Land system changes are central to the food security challenge. Land system science can contribute to sustainable solutions by an integrated analysis of land availability and the assessment of the tradeoffs associated with agricultural expansion and land use intensification. A land system perspective requires local studies of production systems to be contextualised in a regional and global context, while global assessments should be confronted with local realities. Understanding of land governance structures will help to support the development of land use policies and tenure systems that assist in designing more sustainable ways of intensification. Novel land systems should be designed that are adapted to the local context and framed within the global socio-ecological system. Such land systems should explicitly account for the role of land governance as a primary driver of land system change and food production. PMID:24143158

Software for a GPS-Reflection Remote-Sensing System

NASA Technical Reports Server (NTRS)

Lowe, Stephen

2003-01-01

A special-purpose software Global Positioning System (GPS) receiver designed for remote sensing with reflected GPS signals is described in Delay/Doppler-Mapping GPS-Reflection Remote-Sensing System (NPO-30385), which appears elsewhere in this issue of NASA Tech Briefs. The input accepted by this program comprises raw (open-loop) digitized GPS signals sampled at a rate of about 20 MHz. The program processes the data samples to perform the following functions: detection of signals; tracking of phases and delays; mapping of delay, Doppler, and delay/Doppler waveforms; dual-frequency processing; coherent integrations as short as 125 s; decoding of navigation messages; and precise time tagging of observable quantities. The software can perform these functions on all detectable satellite signals without dead time. Open-loop data collected over water, land, or ice and processed by this software can be further processed to extract geophysical information. Possible examples include mean sea height, wind speed and direction, and significant wave height (for observations over the ocean); bistatic-radar terrain images and measures of soil moisture and biomass (for observations over land); and estimates of ice age, thickness, and surface density (for observations over ice).

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.

The carbon cycle in the Australian Community Climate and Earth System Simulator (ACCESS-ESM1) - Part 1: Model description and pre-industrial simulation

NASA Astrophysics Data System (ADS)

Law, Rachel M.; Ziehn, Tilo; Matear, Richard J.; Lenton, Andrew; Chamberlain, Matthew A.; Stevens, Lauren E.; Wang, Ying-Ping; Srbinovsky, Jhan; Bi, Daohua; Yan, Hailin; Vohralik, Peter F.

2017-07-01

Earth system models (ESMs) that incorporate carbon-climate feedbacks represent the present state of the art in climate modelling. Here, we describe the Australian Community Climate and Earth System Simulator (ACCESS)-ESM1, which comprises atmosphere (UM7.3), land (CABLE), ocean (MOM4p1), and sea-ice (CICE4.1) components with OASIS-MCT coupling, to which ocean and land carbon modules have been added. The land carbon model (as part of CABLE) can optionally include both nitrogen and phosphorous limitation on the land carbon uptake. The ocean carbon model (WOMBAT, added to MOM) simulates the evolution of phosphate, oxygen, dissolved inorganic carbon, alkalinity and iron with one class of phytoplankton and zooplankton. We perform multi-centennial pre-industrial simulations with a fixed atmospheric CO2 concentration and different land carbon model configurations (prescribed or prognostic leaf area index). We evaluate the equilibration of the carbon cycle and present the spatial and temporal variability in key carbon exchanges. Simulating leaf area index results in a slight warming of the atmosphere relative to the prescribed leaf area index case. Seasonal and interannual variations in land carbon exchange are sensitive to whether leaf area index is simulated, with interannual variations driven by variability in precipitation and temperature. We find that the response of the ocean carbon cycle shows reasonable agreement with observations. While our model overestimates surface phosphate values, the global primary productivity agrees well with observations. Our analysis highlights some deficiencies inherent in the carbon models and where the carbon simulation is negatively impacted by known biases in the underlying physical model and consequent limits on the applicability of this model version. We conclude the study with a brief discussion of key developments required to further improve the realism of our model simulation.

Integrating remotely sensed land cover observations and a biogeochemical model for estimating forest ecosystem carbon dynamics

USGS Publications Warehouse

Liu, J.; Liu, S.; Loveland, Thomas R.; Tieszen, L.L.

2008-01-01

Land cover change is one of the key driving forces for ecosystem carbon (C) dynamics. We present an approach for using sequential remotely sensed land cover observations and a biogeochemical model to estimate contemporary and future ecosystem carbon trends. We applied the General Ensemble Biogeochemical Modelling System (GEMS) for the Laurentian Plains and Hills ecoregion in the northeastern United States for the period of 1975-2025. The land cover changes, especially forest stand-replacing events, were detected on 30 randomly located 10-km by 10-km sample blocks, and were assimilated by GEMS for biogeochemical simulations. In GEMS, each unique combination of major controlling variables (including land cover change history) forms a geo-referenced simulation unit. For a forest simulation unit, a Monte Carlo process is used to determine forest type, forest age, forest biomass, and soil C, based on the Forest Inventory and Analysis (FIA) data and the U.S. General Soil Map (STATSGO) data. Ensemble simulations are performed for each simulation unit to incorporate input data uncertainty. Results show that on average forests of the Laurentian Plains and Hills ecoregion have been sequestrating 4.2 Tg C (1 teragram = 1012 gram) per year, including 1.9 Tg C removed from the ecosystem as the consequences of land cover change. ?? 2008 Elsevier B.V.

An analysis of human-induced land transformations in the San Francisco Bay/Sacramento area

USGS Publications Warehouse

Kirtland, David A.; Gaydos, L.J.; Clarke, Keith; DeCola, Lee; Acevedo, William; Bell, Cindy

1994-01-01

Part of the U.S. Geological Survey's Global Change Research Program involvesstudying the area from the Pacific Ocean to the Sierra foothills to enhance understanding ofthe role that human activities play in global change. The study investigates the ways thathumans transform the land and the effects that changing the landscape may have on regionaland global systems. To accomplish this research, scientists are compiling records ofhistorical transformations in the region's land cover over the last 140 years, developing asimulation model to predict land cover change, and assembling a digital data set to analyzeand describe land transformations. The historical data regarding urban growth focusattention on the significant change the region underwent from 1850 to 1990. Animation isused to visualize a time series of the change in land cover. The historical change is beingused to calibrate a prototype cellular automata model, developed to predict changes in urbanland cover 100 years into the future. Future urban growth scenarios will be developed foranalyzing possible human-induced impacts on land cover at a regional scale. These data aidin documenting and understanding human-induced land transformations from both historical andpredictive perspectives. A descriptive analysis of the region is used to investigate therelationships among data characteristic of the region. These data consist of multilayertopography, climate, vegetation, and population data for a 256-km2 region of centralCalifornia. A variety of multivariate analysis tools are used to integrate the data inraster format from map contours, interpolated climate observations, satellite observations,and population estimates.

Diagnosing the Nature of Land-Atmosphere Coupling During the 2006-7 Dry/Wet Extremes in the U. S. Southern Great Plains

NASA Technical Reports Server (NTRS)

Santanello, Joseph A.; Peters-Lidard, Christa D.; Kennedy, Aaron D.; Kumar, Sujay; Dong, Xiquan

2011-01-01

Land-atmosphere (L-A) interactions play a critical role in determining the diurnal evolution of land surface and planetary boundary layer (PBL) temperature and moisture states and fluxes. In turn, these interactions regulate the strength of the connection between surface moisture and precipitation in a coupled system. To address deficiencies in numerical weather prediction and climate models due to improper treatment of L-A interactions, recent studies have focused on development of diagnostics to quantify the strength and accuracy of the land-PBL coupling at the process-level. In this study, a diagnosis of the nature and impacts of local land-atmosphere coupling (LoCo) during dry and wet extreme conditions is presented using a combination of models and observations during the summers of2006-7 in the U.S. Southern Great Plains. Specifically, the Weather Research and Forecasting (WRF) model has been coupled to NASA's Land Information System (LIS), which provides a flexible and high resolution representation and initialization of land surface physics and states. A range of diagnostics exploring the links and feedbacks between soil moisture and precipitation are examined for the dry/wet regimes of this region, along with the behavior and accuracy of different land-PBL scheme couplings under these conditions. Results demonstrate how LoCo diagnostics can be applied to coupled model components in the context of their integrated impacts on the process-chain connecting the land surface to the PBL and support of hydrological anomalies.

The GLAS Algorithm Theoretical Basis Document for Precision Attitude Determination (PAD)

NASA Technical Reports Server (NTRS)

Bae, Sungkoo; Smith, Noah; Schutz, Bob E.

2013-01-01

The Geoscience Laser Altimeter System (GLAS) was the sole instrument for NASAs Ice, Cloud and land Elevation Satellite (ICESat) laser altimetry mission. The primary purpose of the ICESat mission was to make ice sheet elevation measurements of the polar regions. Additional goals were to measure the global distribution of clouds and aerosols and to map sea ice, land topography and vegetation. ICESat was the benchmark Earth Observing System (EOS) mission to be used to determine the mass balance of the ice sheets, as well as for providing cloud property information, especially for stratospheric clouds common over polar areas.

Assessing the drivers of gully formation and development using participatory geographic information systems (PGIS) in Suswa Catchment, Narok County

NASA Astrophysics Data System (ADS)

Konana, Charity

2017-04-01

This study investigated drivers of gully formation and development using participatory geographic information systems (PGIS) with the local communities. Changes in land use and land cover for 1985-2000, 2000-2011 and 1985-2011 were determined using PGIS. The results showed that land use and land cover changes occurred in the 4 villages (Eluai, Olepolos, Olesharo and Enkiloriti) in the study area. There were significant changes in shrubland which decreased in Eluai village (p < 0.002) and no significant changes in built up areas, bareland, agricultural land, waterbodies, grassland and shrubland in the 3 villages (Enkiloriti, Olepolos and Olesharo). It was observed that between 1985 and 2011 (26 years), there was an overall increase in built up area and bareland and decrease in shrubland and grassland in the 4 villages (Olepolos, Enkiloriti, Eluai and Olesharo). Land use change benefits noted by communities included increased access to grazing areas and firewood. Undesirable land use change effects noted were a decrease in shrubland, food production, grazing area and rainfall, and an increase in wind erosion, gully formation and flooding. Community recommendations included afforestation programmes, construction of terraces for water harvesting, training on soil conservation measures and use of appropriate alternative sources of energy other than charcoal. PGIS maps produced will help to understand the driving forces of gully erosion (built up areas, bareland, agricultural land, grassland and shrubland) that are heavily affecting the study area over the years. Participatory mapping of land use and land cover changes is therefore useful for targeting land management interventions. Key words: Land use and cover change, Soil Erosion, Narok County, PGIS

Making the City Observable.

ERIC Educational Resources Information Center

Wurman, Richard Saul

Explored in this special issue of "Design Quarterly" are some of the existing data systems which describe, in visual terms, various urban entities: transportation systems, roadways, public buildings, land patterns, historical structures, as well as some new methods for developing physical information that will be widely used in the future. Through…

Operational Derivation of Surface Albedo and Down-Welling Short-Wave Radiation in the Satellite Application Facility for Land Surface Analysis

NASA Astrophysics Data System (ADS)

Geiger, B.; Carrer, D.; Meurey, C.; Roujean, J.-L.

2006-08-01

The Satellite Application Facility for Land Surface Anal- ysis hosted by the Portuguese Meteorological Institute in Lisbon generates and distributes value added satellite products for numerical weather prediction and environ- mental applications in near-real time. Within the project consortium M´et´eo-France is responsible for the land sur- face albedo and down-welling short-wave radiation flux products. Since the beginning of the year 2005 Meteosat Second Generation data are routinely processed by the Land-SAF operational system. In general the validation studies carried out so far show a good consistency with in-situ observations or equivalent products derived from other satellites. After one year of operations a summary of the product characteristics and performances is given. Key words: Surface Albedo; Down-welling Radiation; Land-SAF.

STS-121: Discovery Entry Flight Director Post Landing Press Conference

NASA Technical Reports Server (NTRS)

2006-01-01

Steve Stitch, STS-121 Entry Flight Director, and Wayne Hale, Space Shuttle Program is shown in this post landing press conference. Steve Stitch begins with discussing the following topics: 1) Weather at Kennedy Space Center; 2) Gap filler protrusion; 3) De-orbit burn; 4) Space Shuttle Landing; 5) Global Position Satellite System (GPSS) performance; and 6) Post-landing rain showers. Wayne Hale discusses external tank observations at launch and the goals that were obtained by this flight, which are to deliver 4000 pounds of scientific equipment, increase the crew members to three on the International Space Station (ISS), and repair the ISS. Questions from the press on lessons learned from the Auxiliary Power Unit (APU) leak, and flight readiness reviews are addressed.

Land processes distributed active archive center product lifecycle plan

USGS Publications Warehouse

Daucsavage, John C.; Bennett, Stacie D.

2014-01-01

The U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center and the National Aeronautics and Space Administration (NASA) Earth Science Data System Program worked together to establish, develop, and operate the Land Processes (LP) Distributed Active Archive Center (DAAC) to provide stewardship for NASA’s land processes science data. These data are critical science assets that serve the land processes science community with potential value beyond any immediate research use, and therefore need to be accounted for and properly managed throughout their lifecycle. A fundamental LP DAAC objective is to enable permanent preservation of these data and information products. The LP DAAC accomplishes this by bridging data producers and permanent archival resources while providing intermediate archive services for data and information products.

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

Consistency of Estimated Global Water Cycle Variations Over the Satellite Era

NASA Technical Reports Server (NTRS)

Robertson, F. R.; Bosilovich, M. G.; Roberts, J. B.; Reichle, R. H.; Adler, R.; Ricciardulli, L.; Berg, W.; Huffman, G. J.

2013-01-01

Motivated by the question of whether recent indications of decadal climate variability and a possible "climate shift" may have affected the global water balance, we examine evaporation minus precipitation (E-P) variability integrated over the global oceans and global land from three points of view-remotely sensed retrievals / objective analyses over the oceans, reanalysis vertically-integrated moisture convergence (MFC) over land, and land surface models forced with observations-based precipitation, radiation and near-surface meteorology. Because monthly variations in area-averaged atmospheric moisture storage are small and the global integral of moisture convergence must approach zero, area-integrated E-P over ocean should essentially equal precipitation minus evapotranspiration (P-ET) over land (after adjusting for ocean and land areas). Our analysis reveals considerable uncertainty in the decadal variations of ocean evaporation when integrated to global scales. This is due to differences among datasets in 10m wind speed and near-surface atmospheric specific humidity (2m qa) used in bulk aerodynamic retrievals. Precipitation variations, all relying substantially on passive microwave retrievals over ocean, still have uncertainties in decadal variability, but not to the degree present with ocean evaporation estimates. Reanalysis MFC and P-ET over land from several observationally forced diagnostic and land surface models agree best on interannual variations. However, upward MFC (i.e. P-ET) reanalysis trends are likely related in part to observing system changes affecting atmospheric assimilation models. While some evidence for a low-frequency E-P maximum near 2000 is found, consistent with a recent apparent pause in sea-surface temperature (SST) rise, uncertainties in the datasets used here remain significant. Prospects for further reducing uncertainties are discussed. The results are interpreted in the context of recent climate variability (Pacific Decadal Oscillation, Atlantic Meridional Overturning), and efforts to distinguish these modes from longer-term trends.

Effects of terracing on soil and water conservation in China: A meta-analysis

NASA Astrophysics Data System (ADS)

Chen, Die; Wei, Wei

2017-04-01

Terracing has long been considered a powerful strategy for soil and water conservation. However, the efficiency is limited by many factors, such as climate, soil properties, topography, land use, population and socioeconomic status. The aim of this critical review was to discuss the effects of terracing on soil and water conservation in China, using a systematic approach to select peer-reviewed articles published in English and Chinese. 46 individual studies were analyzed, involving six terracing structures (level terraces, slope-separated terraces, slope terraces, reverse-slope terraces, fanya juu terraces and half-moon terraces), a wide geographical range (Northeastern China, Southeastern hilly areas, Southwestern mountain areas and Northwestern-central China), and six land use types (forest, crop trees, cropland, shrub land, grassland and bare land) as well as a series of slope gradients ranging from 3° to 35°. Statistical meta-analysis with runoff for 593 observations and sediment for 636 observations confirmed that terracing had a significant effect on water erosion control. In terms of different terrace structures, runoff and sediment reduction were uppermost on slope-separated terraces. Land use in terraces also played a crucial role in the efficiency of conservation, and tree crops and forest were detected as the most powerful land covers in soil and water conservation due to large aboveground biomass and strong root systems below the ground, which directly reduces the pressure of terraces on rainwater redistribution. In addition, a significant positive correlation between slope gradients (3° 15° and 16° 35°) and terracing efficiency on soil and water conservation was observed. This study revealed the effectiveness and variation of terracing on water erosion control on the national scale, which can serve as a scientific basis to land managers and decision-makers.

Effects of Land Use Changes on the Water and Energy Balance Over South America

NASA Astrophysics Data System (ADS)

Nascimento, M.; Herdies, D. L.; Angelis, C.

2013-05-01

With the objective of analyzing the effects of land use changes in the Amazon and its consequences on the main components of the water and energy balance over South America, with emphasis on the Amazon and La Plata Basin, two experiments were carried for 10-year period (1999-2008), in which the land use conditions were modified, representing conditions for the 90s (CONTROL Experiment) and current conditions over land use in the Amazon region (Experiment 1). Changes in land use were observed mainly in the Amazon region and southern Brazil. The numerical model used to perform the simulations was the ETA in its climate version, using as an initial and boundary condition the CFSR/NCEP reanalysis datasets. The results show for the analyzed period that there was a reduction of 3.3 mm/month in average rainfall rates in the La Plata Basin and 4.2 mm/month in the Amazon region, with some places where this reduction was more pronounced. Seasonally was observed that during the summer there is an average reduction of 3.9 mm/month in the Amazon region. Already on the La Plata Basin was observed an average increase of 11.7 mm/month in the La Plata Basin during the summer and an reduction in winter season. Through the overall result was also possible to conclude that the changes in land use for more realistic conditions, there were significant reductions in evapotranspiration and latent heat fluxes, as well as an increase in sensible heat fluxes, especially over the regions where the changes were more pronounced. Through the analyzes it can be observed that in general the La Plata Basin is sensitive to changes in land use over the Amazon and adjacent regions, allowing to conclude that such changes can influence the amount of rainfall, the intensity of the major meteorological systems, as well as temperature trends on the regions analyzed.

GLEAM version 3: Global Land Evaporation Datasets and Model

NASA Astrophysics Data System (ADS)

Martens, B.; Miralles, D. G.; Lievens, H.; van der Schalie, R.; de Jeu, R.; Fernandez-Prieto, D.; Verhoest, N.

2015-12-01

Terrestrial evaporation links energy, water and carbon cycles over land and is therefore a key variable of the climate system. However, the global-scale magnitude and variability of the flux, and the sensitivity of the underlying physical process to changes in environmental factors, are still poorly understood due to limitations in in situ measurements. As a result, several methods have risen to estimate global patterns of land evaporation from satellite observations. However, these algorithms generally differ in their approach to model evaporation, resulting in large differences in their estimates. One of these methods is GLEAM, the Global Land Evaporation: the Amsterdam Methodology. GLEAM estimates terrestrial evaporation based on daily satellite observations of meteorological variables, vegetation characteristics and soil moisture. Since the publication of the first version of the algorithm (2011), the model has been widely applied to analyse trends in the water cycle and land-atmospheric feedbacks during extreme hydrometeorological events. A third version of the GLEAM global datasets is foreseen by the end of 2015. Given the relevance of having a continuous and reliable record of global-scale evaporation estimates for climate and hydrological research, the establishment of an online data portal to host these data to the public is also foreseen. In this new release of the GLEAM datasets, different components of the model have been updated, with the most significant change being the revision of the data assimilation algorithm. In this presentation, we will highlight the most important changes of the methodology and present three new GLEAM datasets and their validation against in situ observations and an alternative dataset of terrestrial evaporation (ERA-Land). Results of the validation exercise indicate that the magnitude and the spatiotemporal variability of the modelled evaporation agree reasonably well with the estimates of ERA-Land and the in situ observations. It is also shown that the performance of the revised model is higher compared to the original one.

Monterey Bay study. [analysis of Landsat 1 multispectral band scanner data

NASA Technical Reports Server (NTRS)

Bizzell, R. M.; Wade, L. C.

1975-01-01

The multispectral scanner capabilities of LANDSAT 1 were tested over California's Monterey Bay area and portions of the San Joaquin Valley. Using both computer aided and image interpretive processing techniques, the LANDSAT 1 data were analyzed to determine their potential application in terms of land use and agriculture. Utilizing LANDSAT 1 data, analysts were able to provide the identifications and areal extent of the individual land use categories ranging from very general to highly specific levels (e.g., from agricultural lands to specific field crop types and even the different stages of growth). It is shown that the LANDSAT system is useful in the identification of major crop species and the delineation of numerous land use categories on a global basis and that repeated surveillance would permit the monitoring of changes in seasonal growth characteristics of crops as well as the assessment of various cultivation practices with a minimum of onsite observation. The LANDSAT system is demonstrated to be useful in the planning and development of resource programs on earth.

An engineering optimization method with application to STOL-aircraft approach and landing trajectories

NASA Technical Reports Server (NTRS)

Jacob, H. G.

1972-01-01

An optimization method has been developed that computes the optimal open loop inputs for a dynamical system by observing only its output. The method reduces to static optimization by expressing the inputs as series of functions with parameters to be optimized. Since the method is not concerned with the details of the dynamical system to be optimized, it works for both linear and nonlinear systems. The method and the application to optimizing longitudinal landing paths for a STOL aircraft with an augmented wing are discussed. Noise, fuel, time, and path deviation minimizations are considered with and without angle of attack, acceleration excursion, flight path, endpoint, and other constraints.

Local Scale Radiobrightness Modeling During the Intensive Observing Period-4 of the Cold Land Processes Experiment-1

NASA Astrophysics Data System (ADS)

Kim, E.; Tedesco, M.; de Roo, R.; England, A. W.; Gu, H.; Pham, H.; Boprie, D.; Graf, T.; Koike, T.; Armstrong, R.; Brodzik, M.; Hardy, J.; Cline, D.

2004-12-01

The NASA Cold Land Processes Field Experiment (CLPX-1) was designed to provide microwave remote sensing observations and ground truth for studies of snow and frozen ground remote sensing, particularly issues related to scaling. CLPX-1 was conducted in 2002 and 2003 in Colorado, USA. One of the goals of the experiment was to test the capabilities of microwave emission models at different scales. Initial forward model validation work has concentrated on the Local-Scale Observation Site (LSOS), a 0.8~ha study site consisting of open meadows separated by trees where the most detailed measurements were made of snow depth and temperature, density, and grain size profiles. Results obtained in the case of the 3rd Intensive Observing Period (IOP3) period (February, 2003, dry snow) suggest that a model based on Dense Medium Radiative Transfer (DMRT) theory is able to model the recorded brightness temperatures using snow parameters derived from field measurements. This paper focuses on the ability of forward DMRT modelling, combined with snowpack measurements, to reproduce the radiobrightness signatures observed by the University of Michigan's Truck-Mounted Radiometer System (TMRS) at 19 and 37~GHz during the 4th IOP (IOP4) in March, 2003. Unlike in IOP3, conditions during IOP4 include both wet and dry periods, providing a valuable test of DMRT model performance. In addition, a comparison will be made for the one day of coincident observations by the University of Tokyo's Ground-Based Microwave Radiometer-7 (GBMR-7) and the TMRS. The plot-scale study in this paper establishes a baseline of DMRT performance for later studies at successively larger scales. And these scaling studies will help guide the choice of future snow retrieval algorithms and the design of future Cold Lands observing systems.

Federal Aviation Administration weather program to improve aviation safety

NASA Technical Reports Server (NTRS)

Wedan, R. W.

1983-01-01

The implementation of the National Airspace System (NAS) will improve safety services to aviation. These services include collision avoidance, improved landing systems and better weather data acquisition and dissemination. The program to improve the quality of weather information includes the following: Radar Remote Weather Display System; Flight Service Automation System; Automatic Weather Observation System; Center Weather Processor, and Next Generation Weather Radar Development.

Geospatial tools for assessing land degradation in Budgam district, Kashmir Himalaya, India

NASA Astrophysics Data System (ADS)

Rashid, Mehnaz; Lone, Mahjoor Ahmad; Romshoo, Shakil Ahmad

2011-06-01

Land degradation reduces the ability of the land to perform many biophysical and chemical functions. The main aim of this study was to determine the status of land degradation in the Budgam area of Kashmir Himalaya using remote sensing and geographic information system. The satellite data together with other geospatial datasets were used to quantify different categories of land degradation. The results were validated in the field and an accuracy of 85% was observed. Land use/land cover of the study area was determined in order to know the effect of land use on the rate of land degradation. Normalized differential vegetation index (NDVI) and slope of the area were determined using LANDSAT-enhanced thematic mapper plus (ETM+) data, advanced space borne thermal emission and reflection radiometer, and digital elevation model along with other secondary data were analysed to create various thematic maps, viz., land use/land cover, geology, NDVI and slopes used in modelling land degradation in the Kashmir Himalayan region. The vegetation condition, elevation and land use/land cover information of the area were integrated to assess the land degradation scenario in the area using the ArcGIS `Spatial Analyst Module'. The results reveal that about 13.19% of the study area has undergone moderate to high degradation, whereas about 44.12% of the area has undergone slight degradation.

A vision for an ultra-high resolution integrated water cycle observation and prediction system

NASA Astrophysics Data System (ADS)

Houser, P. R.

2013-05-01

Society's welfare, progress, and sustainable economic growth—and life itself—depend on the abundance and vigorous cycling and replenishing of water throughout the global environment. The water cycle operates on a continuum of time and space scales and exchanges large amounts of energy as water undergoes phase changes and is moved from one part of the Earth system to another. We must move toward an integrated observation and prediction paradigm that addresses broad local-to-global science and application issues by realizing synergies associated with multiple, coordinated observations and prediction systems. A central challenge of a future water and energy cycle observation strategy is to progress from single variable water-cycle instruments to multivariable integrated instruments in electromagnetic-band families. The microwave range in the electromagnetic spectrum is ideally suited for sensing the state and abundance of water because of water's dielectric properties. Eventually, a dedicated high-resolution water-cycle microwave-based satellite mission may be possible based on large-aperture antenna technology that can harvest the synergy that would be afforded by simultaneous multichannel active and passive microwave measurements. A partial demonstration of these ideas can even be realized with existing microwave satellite observations to support advanced multivariate retrieval methods that can exploit the totality of the microwave spectral information. The simultaneous multichannel active and passive microwave retrieval would allow improved-accuracy retrievals that are not possible with isolated measurements. Furthermore, the simultaneous monitoring of several of the land, atmospheric, oceanic, and cryospheric states brings synergies that will substantially enhance understanding of the global water and energy cycle as a system. The multichannel approach also affords advantages to some constituent retrievals—for instance, simultaneous retrieval of vegetation biomass would improve soil-moisture retrieval by avoiding the need for auxiliary vegetation information. This multivariable water-cycle observation system must be integrated with high-resolution, application relevant prediction systems to optimize their information content and utility is addressing critical water cycle issues. One such vision is a real-time ultra-high resolution locally-moasiced global land modeling and assimilation system, that overlays regional high-fidelity information over a baseline global land prediction system. Such a system would provide the best possible local information for use in applications, while integrating and sharing information globally for diagnosing larger water cycle variability. In a sense, this would constitute a hydrologic telecommunication system, where the best local in-situ gage, Doppler radar, and weather station can be shared internationally, and integrated in a consistent manner with global observation platforms like the multivariable water cycle mission. To realize such a vision, large issues must be addressed, such as international data sharing policy, model-observation integration approaches that maintain local extremes while achieving global consistency, and methods for establishing error estimates and uncertainty.

Science and applications-driven OSSE platform for terrestrial hydrology using NASA Land Information System

NASA Astrophysics Data System (ADS)

Kumar, S.; Peters-Lidard, C. D.; Harrison, K.; Santanello, J. A.; Bach Kirschbaum, D.

2014-12-01

Observing System Simulation Experiments (OSSEs) are often conducted to evaluate the worth of existing data and data yet to be collected from proposed new missions. As missions increasingly require a broader ``Earth systems'' focus, it is important that the OSSEs capture the potential benefits of the observations on end-use applications. Towards this end, the results from the OSSEs must also be evaluated with a suite of metrics that capture the value, uncertainty, and information content of the observations while factoring in both science and societal impacts. In this presentation, we present the development of an end-to-end and end-use application oriented OSSE platform using the capabilities of the NASA Land Information System (LIS) developed for terrestrial hydrology. Four case studies that demonstrate the capabilities of the system will be presented: (1) A soil moisture OSSE that employs simulated L-band measurements and examines their impacts towards applications such as floods and droughts. The experiment also uses a decision-theory based analysis to assess the economic utility of observations towards improving drought and flood risk estimates, (2) A GPM-relevant study quantifies the impact of improved precipitation retrievals from GPM towards improving landslide forecasts, (3) A case study that examines the utility of passive microwave soil moisture observations towards weather prediction, and (4) OSSEs used for developing science requirements for the GRACE-2 mission. These experiments also demonstrate the value of a comprehensive modeling environment such as LIS for conducting end-to-end OSSEs by linking satellite observations, physical models, data assimilation algorithms and end-use application models in a single integrated framework.

The South American Land Data Assimilation System (SALDAS) 5-Year Retrospective Atmospheric Forcing Datasets

NASA Technical Reports Server (NTRS)

deGoncalves, Luis Gustavo G.; Shuttleworth, William J.; Vila, Daniel; Larroza, Elaine; Bottino, Marcus J.; Herdies, Dirceu L.; Aravequia, Jose A.; De Mattos, Joao G. Z.; Toll, David L.; Rodell, Matthew;

Assimilation of SMOS Soil Moisture Retrievals in the Land Information System

NASA Technical Reports Server (NTRS)

Blankenship, Clay; Case, Jonathan L.; Zavodsky, Brad

2014-01-01

Soil moisture is a crucial variable for weather prediction because of its influence on evaporation. It is of critical importance for drought and flood monitoring and prediction and for public health applications. The NASA Short-term Prediction Research and Transition Center (SPoRT) has implemented a new module in the NASA Land Information System (LIS) to assimilate observations from the ESA's Soil Moisture and Ocean Salinity (SMOS) satellite. SMOS Level 2 retrievals from the Microwave Imaging Radiometer using Aperture Synthesis (MIRAS) instrument are assimilated into the Noah LSM within LIS via an Ensemble Kalman Filter. The retrievals have a target volumetric accuracy of 4% at a resolution of 35-50 km. Parallel runs with and without SMOS assimilation are performed with precipitation forcing from intentionally degraded observations, and then validated against a model run using the best available precipitation data, as well as against selected station observations. The goal is to demonstrate how SMOS data assimilation can improve modeled soil states in the absence of dense rain gauge and radar networks.

Complex Adaptive Systems, soil degradation and land sensitivity to desertification: A multivariate assessment of Italian agro-forest landscape.

PubMed

Salvati, Luca; Mavrakis, Anastasios; Colantoni, Andrea; Mancino, Giuseppe; Ferrara, Agostino

2015-07-15

Degradation of soils and sensitivity of land to desertification are intensified in last decades in the Mediterranean region producing heterogeneous spatial patterns determined by the interplay of factors such as climate, land-use changes, and human pressure. The present study hypothesizes that rising levels of soil degradation and land sensitivity to desertification are reflected into increasingly complex (and non-linear) relationships between environmental and socioeconomic variables. To verify this hypothesis, the Complex Adaptive Systems (CAS) framework was used to explore the spatiotemporal dynamics of eleven indicators derived from a standard assessment of soil degradation and land sensitivity to desertification in Italy. Indicators were made available on a detailed spatial scale (773 agricultural districts) for various years (1960, 1990, 2000 and 2010) and analyzed through a multi-dimensional exploratory data analysis. Our results indicate that the number of significant pair-wise correlations observed between indicators increased with the level of soil and land degradation, although with marked differences between northern and southern Italy. 'Fast' and 'slow' factors underlying soil and land degradation, and 'rapidly-evolving' or 'locked' agricultural districts were identified according to the rapidity of change estimated for each of the indicators studied. In southern Italy, 'rapidly-evolving' districts show a high level of soil degradation and land sensitivity to desertification during the whole period of investigation. On the contrary, those districts in northern Italy are those experiencing a moderate soil degradation and land sensitivity to desertification with the highest increase in the level of sensitivity over time. The study framework contributes to the assessment of complex local systems' dynamics in affluent but divided countries. Results may inform thematic strategies for the mitigation of land and soil degradation in the framework of action plans to combat desertification. Copyright © 2015 Elsevier B.V. All rights reserved.

Maize Cropping Systems Mapping Using RapidEye Observations in Agro-Ecological Landscapes in Kenya.

PubMed

Richard, Kyalo; Abdel-Rahman, Elfatih M; Subramanian, Sevgan; Nyasani, Johnson O; Thiel, Michael; Jozani, Hosein; Borgemeister, Christian; Landmann, Tobias

2017-11-03

Cropping systems information on explicit scales is an important but rarely available variable in many crops modeling routines and of utmost importance for understanding pests and disease propagation mechanisms in agro-ecological landscapes. In this study, high spatial and temporal resolution RapidEye bio-temporal data were utilized within a novel 2-step hierarchical random forest (RF) classification approach to map areas of mono- and mixed maize cropping systems. A small-scale maize farming site in Machakos County, Kenya was used as a study site. Within the study site, field data was collected during the satellite acquisition period on general land use/land cover (LULC) and the two cropping systems. Firstly, non-cropland areas were masked out from other land use/land cover using the LULC mapping result. Subsequently an optimized RF model was applied to the cropland layer to map the two cropping systems (2nd classification step). An overall accuracy of 93% was attained for the LULC classification, while the class accuracies (PA: producer's accuracy and UA: user's accuracy) for the two cropping systems were consistently above 85%. We concluded that explicit mapping of different cropping systems is feasible in complex and highly fragmented agro-ecological landscapes if high resolution and multi-temporal satellite data such as 5 m RapidEye data is employed. Further research is needed on the feasibility of using freely available 10-20 m Sentinel-2 data for wide-area assessment of cropping systems as an important variable in numerous crop productivity models.

Solar Powered Automated Pipe Water Management System, Water Footprint and Carbon Footprint in Soybean Production

NASA Astrophysics Data System (ADS)

Satyanto, K. S.; Abang, Z. E.; Arif, C.; Yanuar, J. P. M.

2018-05-01

An automatic water management system for agriculture land was developed based on mini PC as controller to manage irrigation and drainage. The system was integrated with perforated pipe network installed below the soil surface to enable water flow in and out through the network, and so water table of the land can be set at a certain level. The system was operated by using solar power electricity supply to power up water level and soil moisture sensors, Raspberry Pi controller and motorized valve actuator. This study aims to implement the system in controlling water level at a soybean production land, and further to observe water footprint and carbon footprint contribution of the soybean production process with application of the automated system. The water level of the field can be controlled around 19 cm from the base. Crop water requirement was calculated using Penman-Monteith approach, with the productivity of soybean 3.57t/ha, total water footprint in soybean production is 872.01 m3/t. Carbon footprint was calculated due to the use of solar power electric supply system and during the soybean production emission was estimated equal to 1.85 kg of CO2.

Design and development of a community carbon cycle benchmarking system for CMIP5 models

NASA Astrophysics Data System (ADS)

Mu, M.; Hoffman, F. M.; Lawrence, D. M.; Riley, W. J.; Keppel-Aleks, G.; Randerson, J. T.

2013-12-01

Benchmarking has been widely used to assess the ability of atmosphere, ocean, sea ice, and land surface models to capture the spatial and temporal variability of observations during the historical period. For the carbon cycle and terrestrial ecosystems, the design and development of an open-source community platform has been an important goal as part of the International Land Model Benchmarking (ILAMB) project. Here we designed and developed a software system that enables the user to specify the models, benchmarks, and scoring systems so that results can be tailored to specific model intercomparison projects. We used this system to evaluate the performance of CMIP5 Earth system models (ESMs). Our scoring system used information from four different aspects of climate, including the climatological mean spatial pattern of gridded surface variables, seasonal cycle dynamics, the amplitude of interannual variability, and long-term decadal trends. We used this system to evaluate burned area, global biomass stocks, net ecosystem exchange, gross primary production, and ecosystem respiration from CMIP5 historical simulations. Initial results indicated that the multi-model mean often performed better than many of the individual models for most of the observational constraints.

Modelling environmental variables for geohazards and georesources assessment to support sustainable land-use decisions in Zaragoza (Spain)

NASA Astrophysics Data System (ADS)

Lamelas, M. T.; Hoppe, A.; de la Riva, J.; Marinoni, O.

2009-10-01

Land-use decisions are usually made on the basis of a variety of criteria. While it is common practice to integrate economic, ecological and social (triple bottom line) criteria, explicit geoscientific factors are relatively rarely considered. If a planned land use involves an interaction with the geosphere, geoscientific aspects should be playing a more important role in the process. With the objective to facilitate a sustainable land-use decision-making a research project was initiated. The area around the city of Zaragoza, in the Ebro Basin of northern Spain, was chosen due to its high degree of industrialisation and urbanization. The area is exposed to several geohazards (e.g., sinkholes and erosion) that may have significant negative effects on current and future land uses. Geographical Information System (GIS) technologies are used to process the complex geoscientific information. Further GIS analysis comprised the creation of an erosion susceptibility map that follows the ITC (International Institute for Geo-Information Science and Earth Observation) system of terrain analysis. The agricultural capability of the soil was determined using the Microleis System. We identify geomorphologic units that show high susceptibility to erosion and high agricultural potential and suggest a method to implement this information in a land-use planning process. Degraded slopes developed upon Tertiary rocks show the highest susceptibility to erosion and low values of agricultural capability, whereas the flat valley bottoms and irrigated flood plains have the highest values of agricultural capability.

Landsat surface reflectance data

USGS Publications Warehouse

,

2015-01-01

Landsat satellite data have been produced, archived, and distributed by the U.S. Geological Survey since 1972. Users rely on these data for historical study of land surface change and require consistent radiometric data processed to the highest science standards. In support of the guidelines established through the Global Climate Observing System, the U.S. Geological Survey has embarked on production of higher-level Landsat data products to support land surface change studies. One such product is Landsat surface reflectance.

Assessing land ownership as a driver of change in the distribution, structure, and composition of California's forests.

NASA Astrophysics Data System (ADS)

Easterday, K.; Kelly, M.; McIntyre, P. J.

2015-12-01

Climate change is forecasted to have considerable influence on the distribution, structure, and function of California's forests. However, human interactions with forested landscapes (e.g. fire suppression, resource extraction and etc.) have complicated scientific understanding of the relative contributions of climate change and anthropogenic land management practices as drivers of change. Observed changes in forest structure towards smaller, denser forests across California have been attributed to both climate change (e.g. increased temperatures and declining water availability) and management practices (e.g. fire suppression and logging). Disentangling how these drivers of change act both together and apart is important to developing sustainable policy and land management practices as well as enhancing knowledge of human and natural system interactions. To that end, a comprehensive historical dataset - the Vegetation Type Mapping project (VTM) - and a modern forest inventory dataset (FIA) are used to analyze how spatial variations in vegetation composition and structure over a ~100 year period can be explained by land ownership.Climate change is forecasted to have considerable influence on the distribution, structure, and function of California's forests. However, human interactions with forested landscapes (e.g. fire suppression, resource extraction and etc.) have complicated scientific understanding of the relative contributions of climate change and anthropogenic land management practices as drivers of change. Observed changes in forest structure towards smaller, denser forests across California have been attributed to both climate change (e.g. increased temperatures and declining water availability) and management practices (e.g. fire suppression and logging). Disentangling how these drivers of change act both together and apart is important to developing sustainable policy and land management practices as well as enhancing knowledge of human and natural system interactions. To that end, a comprehensive historical dataset - the Vegetation Type Mapping project (VTM) - and a modern forest inventory dataset (FIA) are used to analyze how spatial variations in vegetation composition and structure over a ~100 year period can be explained by land ownership.

Sensitivity of Land Surface Parameters on Thunderstorm Simulation through HRLDAS-WRF Coupling Mode

NASA Astrophysics Data System (ADS)

Kumar, Dinesh; Kumar, Krishan; Mohanty, U. C.; Kisore Osuri, Krishna

2016-07-01

Land surface characteristics play an important role in large scale, regional and mesoscale atmospheric process. Representation of land surface characteristics can be improved through coupling of mesoscale atmospheric models with land surface models. Mesoscale atmospheric models depend on Land Surface Models (LSM) to provide land surface variables such as fluxes of heat, moisture, and momentum for lower boundary layer evolution. Studies have shown that land surface properties such as soil moisture, soil temperature, soil roughness, vegetation cover, have considerable effect on lower boundary layer. Although, the necessity to initialize soil moisture accurately in NWP models is widely acknowledged, monitoring soil moisture at regional and global scale is a very tough task due to high spatial and temporal variability. As a result, the available observation network is unable to provide the required spatial and temporal data for the most part of the globe. Therefore, model for land surface initializations rely on updated land surface properties from LSM. The solution for NWP land-state initialization can be found by combining data assimilation techniques, satellite-derived soil data, and land surface models. Further, it requires an intermediate step to use observed rainfall, satellite derived surface insolation, and meteorological analyses to run an uncoupled (offline) integration of LSM, so that the evolution of modeled soil moisture can be forced by observed forcing conditions. Therefore, for accurate land-state initialization, high resolution land data assimilation system (HRLDAS) is used to provide the essential land surface parameters. Offline-coupling of HRLDAS-WRF has shown much improved results over Delhi, India for four thunder storm events. The evolution of land surface variables particularly soil moisture, soil temperature and surface fluxes have provided more realistic condition. Results have shown that most of domain part became wetter and warmer after assimilation of soil moisture and soil temperature at the initial condition which helped to improve the exchange fluxes at lower atmospheric level. Mixing ratio were increased along with elevated theta-e at lower level giving a signature of improvement in LDAS experiment leading to a suitable condition for convection. In the analysis, moisture convergence, mixing ratio and vertical velocities have improved significantly in terms of intensity and time lag. Surface variables like soil moisture, soil temperature, sensible heat flux and latent heat flux have progressed in a possible realistic pattern. Above discussion suggests that assimilation of soil moisture and soil temperature improves the overall simulations significantly.

LIDAR-Aided Inertial Navigation with Extended Kalman Filtering for Pinpoint Landing

NASA Technical Reports Server (NTRS)

Busnardo, David M.; Aitken, Matthew L.; Tolson, Robert H.; Pierrottet, Diego; Amzajerdian, Farzin

2011-01-01

In support of NASA s Autonomous Landing and Hazard Avoidance Technology (ALHAT) project, an extended Kalman filter routine has been developed for estimating the position, velocity, and attitude of a spacecraft during the landing phase of a planetary mission. The proposed filter combines measurements of acceleration and angular velocity from an inertial measurement unit (IMU) with range and Doppler velocity observations from an onboard light detection and ranging (LIDAR) system. These high-precision LIDAR measurements of distance to the ground and approach velocity will enable both robotic and manned vehicles to land safely and precisely at scientifically interesting sites. The filter has been extensively tested using a lunar landing simulation and shown to improve navigation over flat surfaces or rough terrain. Experimental results from a helicopter flight test performed at NASA Dryden in August 2008 demonstrate that LIDAR can be employed to significantly improve navigation based exclusively on IMU integration.

Impacts of land use/cover classification accuracy on regional climate simulations

NASA Astrophysics Data System (ADS)

Ge, Jianjun; Qi, Jiaguo; Lofgren, Brent M.; Moore, Nathan; Torbick, Nathan; Olson, Jennifer M.

2007-03-01

Land use/cover change has been recognized as a key component in global change. Various land cover data sets, including historically reconstructed, recently observed, and future projected, have been used in numerous climate modeling studies at regional to global scales. However, little attention has been paid to the effect of land cover classification accuracy on climate simulations, though accuracy assessment has become a routine procedure in land cover production community. In this study, we analyzed the behavior of simulated precipitation in the Regional Atmospheric Modeling System (RAMS) over a range of simulated classification accuracies over a 3 month period. This study found that land cover accuracy under 80% had a strong effect on precipitation especially when the land surface had a greater control of the atmosphere. This effect became stronger as the accuracy decreased. As shown in three follow-on experiments, the effect was further influenced by model parameterizations such as convection schemes and interior nudging, which can mitigate the strength of surface boundary forcings. In reality, land cover accuracy rarely obtains the commonly recommended 85% target. Its effect on climate simulations should therefore be considered, especially when historically reconstructed and future projected land covers are employed.

Skin Temperature Analysis and Bias Correction in a Coupled Land-Atmosphere Data Assimilation System

NASA Technical Reports Server (NTRS)

Bosilovich, Michael G.; Radakovich, Jon D.; daSilva, Arlindo; Todling, Ricardo; Verter, Frances

2006-01-01

In an initial investigation, remotely sensed surface temperature is assimilated into a coupled atmosphere/land global data assimilation system, with explicit accounting for biases in the model state. In this scheme, an incremental bias correction term is introduced in the model's surface energy budget. In its simplest form, the algorithm estimates and corrects a constant time mean bias for each gridpoint; additional benefits are attained with a refined version of the algorithm which allows for a correction of the mean diurnal cycle. The method is validated against the assimilated observations, as well as independent near-surface air temperature observations. In many regions, not accounting for the diurnal cycle of bias caused degradation of the diurnal amplitude of background model air temperature. Energy fluxes collected through the Coordinated Enhanced Observing Period (CEOP) are used to more closely inspect the surface energy budget. In general, sensible heat flux is improved with the surface temperature assimilation, and two stations show a reduction of bias by as much as 30 Wm(sup -2) Rondonia station in Amazonia, the Bowen ratio changes direction in an improvement related to the temperature assimilation. However, at many stations the monthly latent heat flux bias is slightly increased. These results show the impact of univariate assimilation of surface temperature observations on the surface energy budget, and suggest the need for multivariate land data assimilation. The results also show the need for independent validation data, especially flux stations in varied climate regimes.

Earth Observation in Support of Sustainable Urban Planning: Results of the Dragon-3 Monitor Project

NASA Astrophysics Data System (ADS)

Cartalis, C.; Polydoros, A.; Mavrakou, T.; Asimakopoulos, D. N.

2016-08-01

Sustainable urban planning increasingly demands innovative concepts and techniques to obtain up-to-date and area-wide information on the characteristics and development of the urban system. In this paper, a thorough and conclusive presentation is made in terms of the results of the DRAGON-3 MONITOR project as based on the use of Earth Observation. Results refer in particular to a set of EO based dynamic urban indicators (i.e. urban form and expansion, land use/land cover changes, land surface temperature distribution, the presence and strength of urban heat island) with the capacity to describe the state, dynamic changes and interaction of the land and thermal environment in urban areas. Furthermore results are assessed in terms of their potential to operationally support sustainable urban planning and bridge the gap between EO scientists and urban planners. Constraints related to the spatial resolution and revisit time of satellite sensors are discussed as they influence the accuracy and applicability of the indicators. Methodologies to improve the applicability of the indicators are also discussed along with the presentation of the respective results.

Assimilation of Satellite-Derived Skin Temperature Observations into Land Surface Models

NASA Technical Reports Server (NTRS)

Reichle, Rolf H.; Kumar, Sujay V.; Mahanama, P. P.; Koster, Randal D.; Liu, Q.

2010-01-01

Land surface (or "skin") temperature (LST) lies at the heart of the surface energy balance and is a key variable in weather and climate models. Here we assimilate LST retrievals from the International Satellite Cloud Climatology Project (ISCCP) into the Noah and Catchment (CLSM) land surface models using an ensemble-based, off-line land data assimilation system. LST is described very differently in the two models. A priori scaling and dynamic bias estimation approaches are applied because satellite and model LST typically exhibit different mean values and variability. Performance is measured against 27 months of in situ measurements from the Coordinated Energy and Water Cycle Observations Project at 48 stations. LST estimates from Noah and CLSM without data assimilation ("open loop") are comparable to each other and superior to that of ISCCP retrievals. For LST, RMSE values are 4.9 K (CLSM), 5.6 K (Noah), and 7.6 K (ISCCP), and anomaly correlation coefficients (R) are 0.62 (CLSM), 0.61 (Noah), and 0.52 (ISCCP). Assimilation of ISCCP retrievals provides modest yet statistically significant improvements (over open loop) of up to 0.7 K in RMSE and 0.05 in anomaly R. The skill of surface turbulent flux estimates from the assimilation integrations is essentially identical to the corresponding open loop skill. Noah assimilation estimates of ground heat flux, however, can be significantly worse than open loop estimates. Provided the assimilation system is properly adapted to each land model, the benefits from the assimilation of LST retrievals are comparable for both models.

Assimilation of SMOS Retrievals in the Land Information System

NASA Technical Reports Server (NTRS)

Blankenship, Clay B.; Case, Jonathan L.; Zavodsky, Bradley T.; Crosson, William L.

2016-01-01

The Soil Moisture and Ocean Salinity (SMOS) satellite provides retrievals of soil moisture in the upper 5 cm with a 30-50 km resolution and a mission accuracy requirement of 0.04 cm(sub 3 cm(sub -3). These observations can be used to improve land surface model soil moisture states through data assimilation. In this paper, SMOS soil moisture retrievals are assimilated into the Noah land surface model via an Ensemble Kalman Filter within the NASA Land Information System. Bias correction is implemented using Cumulative Distribution Function (CDF) matching, with points aggregated by either land cover or soil type to reduce sampling error in generating the CDFs. An experiment was run for the warm season of 2011 to test SMOS data assimilation and to compare assimilation methods. Verification of soil moisture analyses in the 0-10 cm upper layer and root zone (0-1 m) was conducted using in situ measurements from several observing networks in the central and southeastern United States. This experiment showed that SMOS data assimilation significantly increased the anomaly correlation of Noah soil moisture with station measurements from 0.45 to 0.57 in the 0-10 cm layer. Time series at specific stations demonstrate the ability of SMOS DA to increase the dynamic range of soil moisture in a manner consistent with station measurements. Among the bias correction methods, the correction based on soil type performed best at bias reduction but also reduced correlations. The vegetation-based correction did not produce any significant differences compared to using a simple uniform correction curve.

Assimilation of SMOS Retrievals in the Land Information System

PubMed Central

Blankenship, Clay B.; Case, Jonathan L.; Zavodsky, Bradley T.; Crosson, William L.

2018-01-01

The Soil Moisture and Ocean Salinity (SMOS) satellite provides retrievals of soil moisture in the upper 5 cm with a 30-50 km resolution and a mission accuracy requirement of 0.04 cm3 cm−3. These observations can be used to improve land surface model soil moisture states through data assimilation. In this paper, SMOS soil moisture retrievals are assimilated into the Noah land surface model via an Ensemble Kalman Filter within the NASA Land Information System. Bias correction is implemented using Cumulative Distribution Function (CDF) matching, with points aggregated by either land cover or soil type to reduce sampling error in generating the CDFs. An experiment was run for the warm season of 2011 to test SMOS data assimilation and to compare assimilation methods. Verification of soil moisture analyses in the 0-10 cm upper layer and root zone (0-1 m) was conducted using in situ measurements from several observing networks in the central and southeastern United States. This experiment showed that SMOS data assimilation significantly increased the anomaly correlation of Noah soil moisture with station measurements from 0.45 to 0.57 in the 0-10 cm layer. Time series at specific stations demonstrate the ability of SMOS DA to increase the dynamic range of soil moisture in a manner consistent with station measurements. Among the bias correction methods, the correction based on soil type performed best at bias reduction but also reduced correlations. The vegetation-based correction did not produce any significant differences compared to using a simple uniform correction curve. PMID:29367795

Fires and Smoke Observed from the Earth Observing System MODIS Instrument: Products, Validation, and Operational Use

NASA Technical Reports Server (NTRS)

Kaufman, Y. J.; Ichoku, C.; Giglio, L.; Korontzi, S.; Chu, D. A.; Hao, W. M.; Justice, C. O.; Lau, William K. M. (Technical Monitor)

2001-01-01

The MODIS sensor, launched on NASA's Terra satellite at the end of 1999, was designed with 36 spectral channels for a wide array of land, ocean, and atmospheric investigations. MODIS has a unique ability to observe fires, smoke, and burn scars globally. Its main fire detection channels saturate at high brightness temperatures: 500 K at 4 microns and 400 K at 11 microns, which can only be attained in rare circumstances at the I kin fire detection spatial resolution. Thus, unlike other polar orbiting satellite sensors with similar thermal and spatial resolutions, but much lower saturation temperatures (e.g. AVHRR and ATSR), MODIS can distinguish between low intensity ground surface fires and high intensity crown forest fires. Smoke column concentration over land is for the first time being derived from the MOMS solar channels, extending from 0.41 microns to 2.1 microns. The smoke product has been provisionally validated both globally and regionally over southern Africa and central and south America. Burn scars are observed from MODIS even in the presence of smoke, using the 1.2 to 2.1 micron channels. MODIS burned area information is used to estimate pyrogenic emissions. A wide range of these fire and related products and validation are demonstrated for the wild fires that occurred in northwestern United States in the summer of 2000. The MODIS rapid response system and direct broadcast capability is being developed to enable users to obtain and generate data in near real time. It is expected that health and land management organizations will use these systems for monitoring the occurrence of fires and the dispersion of smoke within two to six hours after data acquisition.

A comprehensive assessment of different evapotranspiration products using the site-level FLUXNET database

NASA Astrophysics Data System (ADS)

Liu, J.

2017-12-01

Accurately estimate of ET is crucial for studies of land-atmosphere interactions. A series of ET products have been developed recently relying on various simulation methods, however, uncertainties in accuracy of products limit their implications. In this study, accuracies of total 8 popular global ET products simulated based on satellite retrieves (ETMODIS and ETZhang), reanalysis (ETJRA55), machine learning method (ETJung) and land surface models (ETCLM, ETMOS, ETNoah and ETVIC) forcing by Global Land Data Assimilation System (GLDAS), respectively, were comprehensively evaluated against observations from eddy covariance FLUXNET sites by yearly, land cover and climate zones. The result shows that all simulated ET products tend to underestimate in the lower ET ranges or overestimate in higher ET ranges compared with ET observations. Through the examining of four statistic criterias, the root mean square error (RMSE), mean bias error (MBE), R2, and Taylor skill score (TSS), ETJung provided a high performance whether yearly or land cover or climatic zones. Satellite based ET products also have impressive performance. ETMODIS and ETZhang present comparable accuracy, while were skilled for different land cover and climate zones, respectively. Generally, the ET products from GLDAS show reasonable accuracy, despite ETCLM has relative higher RMSE and MBE for yearly, land cover and climate zones comparisons. Although the ETJRA55 shows comparable R2 with other products, its performance was constraint by the high RMSE and MBE. Knowledge from this study is crucial for ET products improvement and selection when they were used.

Modeling habitat dynamics accounting for possible misclassification

USGS Publications Warehouse

Veran, Sophie; Kleiner, Kevin J.; Choquet, Remi; Collazo, Jaime; Nichols, James D.

2012-01-01

Land cover data are widely used in ecology as land cover change is a major component of changes affecting ecological systems. Landscape change estimates are characterized by classification errors. Researchers have used error matrices to adjust estimates of areal extent, but estimation of land cover change is more difficult and more challenging, with error in classification being confused with change. We modeled land cover dynamics for a discrete set of habitat states. The approach accounts for state uncertainty to produce unbiased estimates of habitat transition probabilities using ground information to inform error rates. We consider the case when true and observed habitat states are available for the same geographic unit (pixel) and when true and observed states are obtained at one level of resolution, but transition probabilities estimated at a different level of resolution (aggregations of pixels). Simulation results showed a strong bias when estimating transition probabilities if misclassification was not accounted for. Scaling-up does not necessarily decrease the bias and can even increase it. Analyses of land cover data in the Southeast region of the USA showed that land change patterns appeared distorted if misclassification was not accounted for: rate of habitat turnover was artificially increased and habitat composition appeared more homogeneous. Not properly accounting for land cover misclassification can produce misleading inferences about habitat state and dynamics and also misleading predictions about species distributions based on habitat. Our models that explicitly account for state uncertainty should be useful in obtaining more accurate inferences about change from data that include errors.

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.

Contrasting land uses in Mediterranean agro-silvo-pastoral systems generated patchy diversity patterns of vascular plants and below-ground microorganisms.

PubMed

Bagella, Simonetta; Filigheddu, Rossella; Caria, Maria Carmela; Girlanda, Mariangela; Roggero, Pier Paolo

2014-12-01

The aims of this paper were (i) to define how contrasting land uses affected plant biodiversity in Mediterranean agro-silvo-pastoral-systems across a gradient of disturbance regimes: cork oak forests, secondary grasslands, hay crops, grass covered vineyards, tilled vineyards; (ii) to determine whether these patterns mirrored those of below-ground microorganisms and whether the components of γ-diversity followed a similar model. The disturbance regimes affected plant assemblage composition. Species richness decreased with increasing land use intensity, the Shannon index showed the highest values in grasslands and hay crops. Plant assemblage composition patterns mirrored those of Basidiomycota and Ascomycota. Richness in Basidiomycota, denitrifying bacteria and microbial biomass showed the same trend as that observed for vascular plant richness. The Shannon index pattern of below-ground microorganisms was different from that of plants. The plant γ-diversity component model weakly mirrored those of Ascomycota. Patchy diversity patterns suggest that the maintenance of contrasting land uses associated with different productions typical of agro-silvo-pastoral-systems can guarantee the conservation of biodiversity. Copyright © 2014 Académie des sciences. Published by Elsevier SAS. All rights reserved.

Analysis On Land Cover In Municipality Of Malang With Landsat 8 Image Through Unsupervised Classification

NASA Astrophysics Data System (ADS)

Nahari, R. V.; Alfita, R.

2018-01-01

Remote sensing technology has been widely used in the geographic information system in order to obtain data more quickly, accurately and affordably. One of the advantages of using remote sensing imagery (satellite imagery) is to analyze land cover and land use. Satellite image data used in this study were images from the Landsat 8 satellite combined with the data from the Municipality of Malang government. The satellite image was taken in July 2016. Furthermore, the method used in this study was unsupervised classification. Based on the analysis towards the satellite images and field observations, 29% of the land in the Municipality of Malang was plantation, 22% of the area was rice field, 12% was residential area, 10% was land with shrubs, and the remaining 2% was water (lake/reservoir). The shortcoming of the methods was 25% of the land in the area was unidentified because it was covered by cloud. It is expected that future researchers involve cloud removal processing to minimize unidentified area.

Overview of the Pre-YMC2015 campaign over the southwestern coastal land and adjacent sea of Sumatera Island, Indonesia

NASA Astrophysics Data System (ADS)

Mori, Shuichi; Katsumata, Masaki; Yoneyama, Kunio; Suzuki, Kenji; Hayati, Noer; Syamsudin, Fadli

2016-04-01

An international research project named Years of the Maritime Continent (YMC) is planned during 2017-2019 to expedite the progress of improving understanding and prediction of local multi-scale variability of the Maritime Continent (MC) weather-climate system and its global impact through observations and modeling exercises. We carried out a campaign observation over the southwestern coastal land and adjacent sea of Sumatera Island, Indonesia, during November-December 2015 as a pilot study of the YMC to examine land-ocean coupling processes in mechanisms of coastal heavy rain band (CHeR) along Sumatera Island and further potential scientific themes in the coming YMC. We deployed two land observation sites at Bengkulu city (3.86S, 102.34E) in the southwestern coast of Sumatera Island with various kinds of instruments including an X-band dual polarimetric (DP) radar and a C-band Doppler radar, and the R/V Mirai approximately 50 km southwest (4.07S, 101.90E) of the land stations with a C-band DP radar. We made 3 hourly soundings at Bengkulu and the R/V Mirai during 09 November - 25 December (47 days) and 24 November - 17 December (24 days), respectively. In addition, 18 videosondes observations, which could identify precipitation particles by an onboard camera in and out of rainclouds, were performed under heavy rainfall condition to examine cloud microphysical processes as well as simultaneous RHI observations with the Mirai DP radar. Whereas rainfall amount during the period was less than that of climatological view due to the Godzilla El-Nino event in this rainy season, we found concrete diurnal variation with thunderstorms in the evening along the foothills of coastal land and widely spread stratiform precipitation mainly over the adjacent sea due to the passage of Madden-Julian Oscillation (MJO) convection with strong westerly wind in the lower troposphere during the former and latter halves of the campaign period, respectively. Diurnally developed thunderstorms and their lifecycles which formed CHeR were examined based on simultaneous sounding and DP radar observations both on and off the Sumatera Island as well as their interaction with the ocean mixing layer over the coastal water. In addition, logistical difficulties we encountered to carry out in situ observations over the Indonesian water and land are briefly introduced for discussing an observational strategy of the coming YMC campaign in 2017-2019.

Can we use Earth Observations to improve monthly water level forecasts?

NASA Astrophysics Data System (ADS)

Slater, L. J.; Villarini, G.

2017-12-01

Dynamical-statistical hydrologic forecasting approaches benefit from different strengths in comparison with traditional hydrologic forecasting systems: they are computationally efficient, can integrate and `learn' from a broad selection of input data (e.g., General Circulation Model (GCM) forecasts, Earth Observation time series, teleconnection patterns), and can take advantage of recent progress in machine learning (e.g. multi-model blending, post-processing and ensembling techniques). Recent efforts to develop a dynamical-statistical ensemble approach for forecasting seasonal streamflow using both GCM forecasts and changing land cover have shown promising results over the U.S. Midwest. Here, we use climate forecasts from several GCMs of the North American Multi Model Ensemble (NMME) alongside 15-minute stage time series from the National River Flow Archive (NRFA) and land cover classes extracted from the European Space Agency's Climate Change Initiative 300 m annual Global Land Cover time series. With these data, we conduct systematic long-range probabilistic forecasting of monthly water levels in UK catchments over timescales ranging from one to twelve months ahead. We evaluate the improvement in model fit and model forecasting skill that comes from using land cover classes as predictors in the models. This work opens up new possibilities for combining Earth Observation time series with GCM forecasts to predict a variety of hazards from space using data science techniques.

An integrated approach for estimating global glacio isostatic adjustment, land ice, hydrology and ocean mass trends within a complete coupled Earth system framework

NASA Astrophysics Data System (ADS)

Schumacher, M.; Bamber, J. L.; Martin, A.

2016-12-01

Future sea level rise (SLR) is one of the most serious consequences of climate change. Therefore, understanding the drivers of past sea level change is crucial for improving predictions. SLR integrates many Earth system components including oceans, land ice, terrestrial water storage, as well as solid Earth effects. Traditionally, each component have been tackled separately, which has often lead to inconsistencies between discipline-specific estimates of each part of the sea level budget. To address these issues, the European Research Council has funded a five year project aimed at producing a physically-based, data-driven solution for the complete coupled land-ocean-solid Earth system that is consistent with the full suite of observations, prior knowledge and fundamental geophysical constraints. The project is called "GlobalMass" and based at University of Bristol. Observed mass movement from the GRACE mission plus vertical land motion from a global network of permanent GPS stations will be utilized in a data-driven approach to estimate glacial isostatic adjustment (GIA) without introducing any assumptions about the Earth structure or ice loading history. A Bayesian Hierarchical Model (BHM) will be used as the framework to combine the satellite and in-situ observations alongside prior information that incorporates the physics of the coupled system such as conservation of mass and characteristic length scales of different processes in both space and time. The BHM is used to implement a simultaneous solution at a global scale. It will produce a consistent partitioning of the integrated SLR signal into its steric (thermal) and barystatic (mass) component for the satellite era. The latter component is induced by hydrological mass trends and melting of land ice. The BHM was developed and tested on Antarctica, where it has been used to separate surface, ice dynamic and GIA signals simultaneously. We illustrate the approach and concepts with examples from this test case. We discuss how the BHM, constraints and data will be developed in the "GlobalMass" project to tackle geophysical, computational, and statistical challenges on a global scale and how the methods and obtained data sets will be applied to re-evaluate the 20th Century sea level record, for which tide gauges provide only spatially limited information.

New and Improved GLDAS Data Sets and Data Services at NASA GES DISC

NASA Technical Reports Server (NTRS)

Rui, Hualan; Beaudoing, Hiroko; Teng, William; Vollmer, Bruce; Rodell, Matthew; Lei, Guang-Dih

2012-01-01

The goal of a Land Data Assimilation System (LDAS) is to ingest satellite- and ground-based observational data products, using advanced land surface modeling and data assimilation techniques, in order to generate optimal fields of land surface states and fluxes data and, thereby, facilitate hydrology and climate modeling, research, and forecast. With the motivation of creating more climatologically consistent data sets, NASA GSFC's Hydrological Sciences Laboratory has generated more than 60 years (Jan. 1948-- Dec. 2008) of Global LDAS Version 2 (GLDAS-2) data, by using the Princeton Forcing Data Set and upgraded versions of Land Surface Models (LSMs). GLDAS data and data services are provided at NASA GES DISC Hydrology Data and Information Services Center (HDISC), in collaboration with HSL and LDAS.

SMAP Level 4 Surface and Root Zone Soil Moisture

NASA Technical Reports Server (NTRS)

Reichle, R.; De Lannoy, G.; Liu, Q.; Ardizzone, J.; Kimball, J.; Koster, R.

2017-01-01

The SMAP Level 4 soil moisture (L4_SM) product provides global estimates of surface and root zone soil moisture, along with other land surface variables and their error estimates. These estimates are obtained through assimilation of SMAP brightness temperature observations into the Goddard Earth Observing System (GEOS-5) land surface model. The L4_SM product is provided at 9 km spatial and 3-hourly temporal resolution and with about 2.5 day latency. The soil moisture and temperature estimates in the L4_SM product are validated against in situ observations. The L4_SM product meets the required target uncertainty of 0.04 m(exp. 3)m(exp. -3), measured in terms of unbiased root-mean-square-error, for both surface and root zone soil moisture.

From Environmental Risks, As Problems, To Earth Observations As Solutions To Those Problems

NASA Astrophysics Data System (ADS)

Rycroft, M. J.

This paper introduces the topic of space techniquesfor environmental risks. It does this by giving someexamples of the damage and havoc wrought in recent tragic events -mudslides, floods, cyclones, earthquakes and theChernobyl disaster. It introduces the concept ofa Geographic Information System where informationderived from remote sensing observations made fromspace is combined with other types of informationand processed in a computer.Seven examples are then considered in more detail -the early 1995 flood in The Netherlands and otherhydrological issues, land use studies for agriculture,the Vegetation Index and land degradation ordesertification, hurricane Fran over South andNorth Carolina in September 1996, change detection,ocean catastrophes and atmospheric disasters. Theyillustrate some ways in which information derivedfrom space observations can be used to benefitthe Earth's population.

Interpretation of aeromagnetic data in the Jameson Land Basin, central East Greenland: Structures and related mineralized systems

NASA Astrophysics Data System (ADS)

Brethes, Anaïs; Guarnieri, Pierpaolo; Rasmussen, Thorkild Maack; Bauer, Tobias Erich

2018-01-01

This paper provides a detailed interpretation of several aeromagnetic datasets over the Jameson Land Basin in central East Greenland. The interpretation is based on texture and lineament analysis of magnetic data and derivatives of these, in combination with geological field observations. Numerous faults and Cenozoic intrusions were identified and a chronological interpretation of the events responsible for the magnetic features is proposed built on crosscutting relationships and correlated with absolute ages. Lineaments identified in enhanced magnetic data are compared with structures controlling the mineralized systems occurring in the area and form the basis for the interpretations presented in this paper. Several structures associated with base metal mineralization systems that were known at a local scale are here delineated at a larger scale; allowing the identification of areas displaying favorable geological settings for mineralization. This study demonstrates the usefulness of high-resolution airborne magnetic data for detailed structural interpretation and mineral exploration in geological contexts such as the Jameson Land Basin.

Quantifying changes in water use and groundwater availability in a megacity using novel integrated systems modeling

NASA Astrophysics Data System (ADS)

Hyndman, D. W.; Xu, T.; Deines, J. M.; Cao, G.; Nagelkirk, R.; Viña, A.; McConnell, W.; Basso, B.; Kendall, A. D.; Li, S.; Luo, L.; Lupi, F.; Ma, D.; Winkler, J. A.; Yang, W.; Zheng, C.; Liu, J.

2017-08-01

Water sustainability in megacities is a growing challenge with far-reaching effects. Addressing sustainability requires an integrated, multidisciplinary approach able to capture interactions among hydrology, population growth, and socioeconomic factors and to reflect changes due to climate variability and land use. We developed a new systems modeling framework to quantify the influence of changes in land use, crop growth, and urbanization on groundwater storage for Beijing, China. This framework was then used to understand and quantify causes of observed decreases in groundwater storage from 1993 to 2006, revealing that the expansion of Beijing's urban areas at the expense of croplands has enhanced recharge while reducing water lost to evapotranspiration, partially ameliorating groundwater declines. The results demonstrate the efficacy of such a systems approach to quantify the impacts of changes in climate and land use on water sustainability for megacities, while providing a quantitative framework to improve mitigation and adaptation strategies that can help address future water challenges.

Research on Decision-Making Support of Chineserural Land Tenure Information System

NASA Astrophysics Data System (ADS)

Tan, Jun; Su, Hongyou

Since 1949, the information of land tenure has a positive effect on defining the scope of collective land and state-owned land, implementing the system of cultivated land protection and land use control, designing general land use planning, etc. But as the economic and social development, the existing land tenure information is not appropriate anymore and results in many problems. The emphasis in the near future should be placed on establishing rural land tenure information system including cadastral management system, the uniform property registration system and cadastral management information system, defining the scope and content of various collective land ownership, securing peasants' land tenure rights, shortening the gap between urban and rural areas, all of which will guarantee the effective use of information of land tenure for the government's decision-making.

Irrigated lands: Monitoring by remote sensing

NASA Technical Reports Server (NTRS)

Epiphanio, J. C. N.; Vitorelli, I.

1983-01-01

The use of remote sensing for irrigated areas, especially in the region of Guaira, Brazil (state of Sao Paulo), is examined. Major principles of utilizing LANDSAT data for the detection and mapping of irrigated lands are discussed. In addition, initial results obtained by computer processing of digital data, use of MSS (Multispectral Scanner System)/LANDSAT products, and the availability of new remote sensing products are highlighted. Future activities include the launching of the TM (Thematic Mapper)/LANDSAT 4 with 30 meters of resolution and SPOT (Systeme Probatorie d'Observation de la Terre) with 10 to 20 meters of resolution, to be operational in 1984 and 1986 respectively.

Mechanics of aeolian processes: Soil erosion and dust production

NASA Technical Reports Server (NTRS)

Mehrabadi, M. M.

1989-01-01

Aeolian (wind) processes occur as a result of atmosphere/land-surface system interactions. A thorough understanding of these processes and their physical/mechanical characterization on a global scale is essential to monitoring global change and, hence, is imperative to the fundamental goal of the Earth observing system (Eos) program. Soil erosion and dust production by wind are of consequence mainly in arid and semi arid regions which cover 36 percent of the Earth's land surface. Some recent models of dust production due to wind erosion of agricultural soils and the mechanics of wind erosion in deserts are reviewed and the difficulties of modeling the aeolian transport are discussed.

Annual report to the NASA Administrator by the Aerospace Safety Advisory Panel on the space shuttle program. Part 1: Observations and conclusions

NASA Technical Reports Server (NTRS)

1977-01-01

The panel reviewed the following areas of major significance for the Approach and Landing Test program: mission planning and crew training, flight-readiness of the Carrier Aircraft and the Orbiter, including its flight control and avionics system, facilities, and communications and ground support equipment. The management system for risk assessment was investigated. The Orbital Flight Test Program was also reviewed. Observations and recommendations are presented.

Impacts of Climate and Land-cover Changes on Water Resources in a Humid Subtropical Watershed: a Case Study from East Texas, USA

NASA Astrophysics Data System (ADS)

Heo, J.

2015-12-01

This study investigates an interconnected system of climate change - land cover - water resources for a watershed in humid subtropical climate from 1970 to 2009. A 0.7°C increase in temperature and a 16.3% increase in precipitation were observed in our study area where temperature had no obvious increase trend and precipitation showed definite increasing trend compared to previous studies. The main trend of land-cover change was conversion of vegetation and barren lands to developed and crop lands affected by human intervention, and forest and grass to bush/shrub which considered to be caused by natural climate system. Precipitation contribution to the other hydrologic parameters for a humid subtropical basin is estimated to be 51.9% of evapotranspiration, 16.3% of surface runoff, 0.9% of groundwater discharge, 19.3% of soil water content, and 11.6% of water storage. It shows little higher evapotranspiration and considerably lower surface runoff compare to other humid climate area due to vegetation dominance of land cover. Hydrologic responses to climate and land cover changes are increases of surface runoff, soil water content, evapotranspiration by 15.0%, 2.7%, and 20.1%, respectively, and decrease of groundwater discharge decreased by 9.2%. Surface runoff is relatively stable with precipitation while groundwater discharge and soil water content are sensitive to land cover changes especially human intervention. If temperature is relatively stable, it is considered to be land cover plays important role in evapotranspiration. Citation: Heo, J., J. Yu, J. R. Giardino, and H. Cho (2015), Impacts of climate and land-cover changes on water resources in a humid subtropical watershed: a case study from East Texas, USA, Water Environ. J., 29, doi:10.1111/wej.12096

Diagnosing the Nature of Land-Atmosphere Coupling: A Case Study of Dry/Wet Extremes in the U. S. Southern Great Plains

NASA Technical Reports Server (NTRS)

Santanello, Joseph A. Jr.; Peters-Lidard, Christa D.; Kennedy, Aaron; Kumar, Sujay V.

2012-01-01

Land-atmosphere (L-A) interactions play a critical role in determining the diurnal evolution of land surface and planetary boundary layer (PBL) temperature and moisture states and fluxes. In turn, these interactions regulate the strength of the connection between surface moisture and precipitation in a coupled system. To address model deficiencies, recent studies have focused on development of diagnostics to quantify the strength and accuracy of the land- PBL coupling at the process-level. In this paper, a diagnosis of the nature and impacts of local land-atmosphere coupling (LoCo) during dry and wet extreme conditions is presented using a combination of models and observations during the summers of 2006 and 2007 in the U.S. Southern Great Plains. A range of diagnostics exploring the links and feedbacks between soil moisture and precipitation are applied to the dry/wet regimes exhibited in this region, and in the process a thorough evaluation of nine different land-PBL scheme couplings is conducted under the umbrella of a high-resolution regional modeling testbed. Results show that the sign and magnitude of errors in land surface energy balance components are sensitive to the choice of land surface model, regime type, and running mode. In addition, LoCo diagnostics show that the sensitivity of L-A coupling is stronger towards the land during dry conditions, while the PBL scheme coupling becomes more important during the wet regime. Results also demonstrate how LoCo diagnostics can be applied to any modeling system (e.g. reanalysis products) in the context of their integrated impacts on the process-chain connecting the land surface to the PBL and in support of hydrological anomalies.

Diagnosing the Nature of Land-Atmosphere Coupling: A Case Study of Dry/Wet Extremes in the U.S. Southern Great Plains

NASA Technical Reports Server (NTRS)

Santanello, Joseph A., Jr.; Peters-Lidard, Christa D.; Kennedy, Aaron; Kumar, Sujay V.

2012-01-01

Land-atmosphere (L-A) interactions play a critical role in determining the diurnal evolution of land surface and planetary boundary layer (PBL) temperature and moisture states and fluxes. In turn, these interactions regulate the strength of the connection between surface moisture and precipitation in a coupled system. To address model deficiencies, recent studies have focused on development of diagnostics to quantify the strength and accuracy of the land-PBL coupling at the process level. In this paper, a diagnosis of the nature and impacts of local land-atmosphere coupling (LoCo) during dry and wet extreme conditions is presented using a combination of models and observations during the summers of 2006 and 2007 in the U.S. southern Great Plains. A range of diagnostics exploring the links and feedbacks between soil moisture and precipitation is applied to the dry/wet regimes exhibited in this region, and in the process, a thorough evaluation of nine different land-PBL scheme couplings is conducted under the umbrella of a high-resolution regional modeling test bed. Results show that the sign and magnitude of errors in land surface energy balance components are sensitive to the choice of land surface model, regime type, and running mode. In addition, LoCo diagnostics show that the sensitivity of L-A coupling is stronger toward the land during dry conditions, while the PBL scheme coupling becomes more important during the wet regime. Results also demonstrate how LoCo diagnostics can be applied to any modeling system (e.g., reanalysis products) in the context of their integrated impacts on the process chain connecting the land surface to the PBL and in support of hydrological anomalies.

Examining Environmental Gradients with satellite data in permafrost regions - the current state of the ESA GlobPermafrost initative

NASA Astrophysics Data System (ADS)

Grosse, G.; Bartsch, A.; Kääb, A.; Westermann, S.; Strozzi, T.; Wiesmann, A.; Duguay, C. R.; Seifert, F. M.; Obu, J.; Nitze, I.; Heim, B.; Haas, A.; Widhalm, B.

2017-12-01

Permafrost cannot be directly detected from space, but many surface features of permafrost terrains and typical periglacial landforms are observable with a variety of EO sensors ranging from very high to medium resolution at various wavelengths. In addition, landscape dynamics associated with permafrost changes and geophysical variables relevant for characterizing the state of permafrost, such as land surface temperature or freeze-thaw state can be observed with spaceborne Earth Observation. Suitable regions to examine environmental gradients across the Arctic have been defined in a community white paper (Bartsch et al. 2014, hdl:10013/epic.45648.d001). These transects have been revised and adjusted within the DUE GlobPermafrost initiative of the European Space Agency. The ESA DUE GlobPermafrost project develops, validates and implements Earth Observation (EO) products to support research communities and international organisations in their work on better understanding permafrost characteristics and dynamics. Prototype product cases will cover different aspects of permafrost by integrating in situ measurements of subsurface and surface properties, Earth Observation, and modelling to provide a better understanding of permafrost today. The project will extend local process and permafrost monitoring to broader spatial domains, support permafrost distribution modelling, and help to implement permafrost landscape and feature mapping in a GIS framework. It will also complement active layer and thermal observing networks. Both lowland (latitudinal) and mountain (altitudinal) permafrost issues are addressed. The status of the Permafrost Information System and first results will be presented. Prototypes of GlobPermafrost datasets include: Modelled mean annual ground temperature by use of land surface temperature and snow water equivalent from satellites Land surface characterization including shrub height, land cover and parameters related to surface roughness Trends from Landsat time-series over selected transects For selected sites: subsidence, ground fast lake ice, land surface features and rock glacier monitoring

Monitoring land use/land cover changes using CORINE land cover data: a case study of Silivri coastal zone in Metropolitan Istanbul.

PubMed

Yilmaz, Rüya

2010-06-01

The objective of the present study was to assess changes in land use/land cover patterns in the coastal town of Silivri, a part of greater Istanbul administratively. In the assessment, remotely sensed data, in the form of satellite images, and geographic information systems were used. Types of land use/land cover were designated as the percentage of the total area studied. Results calculated from the satellite data for land cover classification were compared successfully with the database Coordination of Information on the Environment (CORINE). This served as a reference to appraise the reliability of the study presented here. The CORINE Program was established by the European Commission to create a harmonized Geographical Information System on the state of the environment in the European Community. Unplanned urbanization is causing land use changes mainly in developing countries such as Turkey. This situation in Turkey is frequently observed in the city of Istanbul. There are only a few studies of land use-land cover changes which provide an integrated assessment of the biophysical and societal causes and consequences of environmental degradation in Istanbul. The research area comprised greater Silivri Town which is situated by the coast of Marmara Sea, and it is located approximately 60 km west of Istanbul. The city of Istanbul is one of the largest metropolises in Europe with ca. 15 million inhabitants. Additionally, greater Silivri is located near the terminal point of the state highway connecting Istanbul with Europe. Measuring of changes occurring in land use would help control future planning of settlements; hence, it is of importance for the Greater Silivri and Silivri Town. Following our evaluations, coastal zone of Silivri was classified into the land use groups of artificial surfaces agricultural areas and forests and seminatural areas with 47.1%, 12.66%, and 22.62%, respectively.

Department of Defense meteorological and environmental inputs to aviation systems

NASA Technical Reports Server (NTRS)

Try, P. D.

1983-01-01

Recommendations based on need, cost, and achievement of flight safety are offered, and the re-evaluation of weather parameters needed for safe landing operations that lead to reliable and consistent automated observation capabilities are considered.

Monitoring conservation effectiveness in a global biodiversity hotspot: the contribution of land cover change assessment.

PubMed

Joseph, Shijo; Blackburn, George Alan; Gharai, Biswadip; Sudhakar, S; Thomas, A P; Murthy, M S R

2009-11-01

Tropical forests, which play critical roles in global biogeochemical cycles, radiation budgets and biodiversity, have undergone rapid changes in land cover in the last few decades. This study examines the complex process of land cover change in the biodiversity hotspot of Western Ghats, India, specifically investigating the effects of conservation measures within the Indira Gandhi Wildlife Sanctuary. Current vegetation patterns were mapped using an IRS P6 LISS III image and this was used together with Landsat MSS data from 1973 to map land cover transitions. Two major and divergent trends were observed. A dominant degradational trend can be attributed to agricultural expansion and infrastructure development while a successional trend, resulting from protection of the area, showed the resilience of the system after prolonged disturbances. The sanctuary appears susceptible to continuing disturbances under the current management regime but at lower rates than in surrounding unprotected areas. The study demonstrates that remotely sensed land cover assessments can have important contributions to monitoring land management strategies, understanding processes underpinning land use changes and helping to inform future conservation strategies.

Assessing land leveling needs and performance with unmanned aerial system

NASA Astrophysics Data System (ADS)

Enciso, Juan; Jung, Jinha; Chang, Anjin; Chavez, Jose Carlos; Yeom, Junho; Landivar, Juan; Cavazos, Gabriel

2018-01-01

Land leveling is the initial step for increasing irrigation efficiencies in surface irrigation systems. The objective of this paper was to evaluate potential utilization of an unmanned aerial system (UAS) equipped with a digital camera to map ground elevations of a grower's field and compare them with field measurements. A secondary objective was to use UAS data to obtain a digital terrain model before and after land leveling. UAS data were used to generate orthomosaic images and three-dimensional (3-D) point cloud data by applying the structure for motion algorithm to the images. Ground control points (GCPs) were established around the study area, and they were surveyed using a survey grade dual-frequency GPS unit for accurate georeferencing of the geospatial data products. A digital surface model (DSM) was then generated from the 3-D point cloud data before and after laser leveling to determine the topography before and after the leveling. The UAS-derived DSM was compared with terrain elevation measurements acquired from land surveying equipment for validation. Although 0.3% error or root mean square error of 0.11 m was observed between UAS derived and ground measured ground elevation data, the results indicated that UAS could be an efficient method for determining terrain elevation with an acceptable accuracy when there are no plants on the ground, and it can be used to assess the performance of a land leveling project.

Land-surface parameter optimisation using data assimilation techniques: the adJULES system V1.0

NASA Astrophysics Data System (ADS)

Raoult, Nina M.; Jupp, Tim E.; Cox, Peter M.; Luke, Catherine M.

2016-08-01

Land-surface models (LSMs) are crucial components of the Earth system models (ESMs) that are used to make coupled climate-carbon cycle projections for the 21st century. The Joint UK Land Environment Simulator (JULES) is the land-surface model used in the climate and weather forecast models of the UK Met Office. JULES is also extensively used offline as a land-surface impacts tool, forced with climatologies into the future. In this study, JULES is automatically differentiated with respect to JULES parameters using commercial software from FastOpt, resulting in an analytical gradient, or adjoint, of the model. Using this adjoint, the adJULES parameter estimation system has been developed to search for locally optimum parameters by calibrating against observations. This paper describes adJULES in a data assimilation framework and demonstrates its ability to improve the model-data fit using eddy-covariance measurements of gross primary production (GPP) and latent heat (LE) fluxes. adJULES also has the ability to calibrate over multiple sites simultaneously. This feature is used to define new optimised parameter values for the five plant functional types (PFTs) in JULES. The optimised PFT-specific parameters improve the performance of JULES at over 85 % of the sites used in the study, at both the calibration and evaluation stages. The new improved parameters for JULES are presented along with the associated uncertainties for each parameter.

Design and Impacts of Land-Biogenic-Atmosphere Coupling in the NASA-Unified WRF (NU-WRF) Modeling System

NASA Technical Reports Server (NTRS)

Tan, Qian; Santanello, Joseph A., Jr.; Zhou, Shujia; Tao, Zhining; Peters-Lidard, Christa d.; Chn, Mian

2011-01-01

Land-Atmosphere coupling is typically designed and implemented independently for physical (e.g. water and energy) and chemical (e.g. biogenic emissions and surface depositions)-based models and applications. Differences in scale, data requirements, and physics thus limit the ability of Earth System models to be fully coupled in a consistent manner. In order for the physical-chemical-biological coupling to be complete, treatment of the land in terms of surface classification, condition, fluxes, and emissions must be considered simultaneously and coherently across all components. In this study, we investigate a coupling strategy for the NASA-Unified Weather Research and Forecasting (NU-WRF) model that incorporates the traditionally disparate fluxes of water and energy through NASA's LIS (Land Information System) and biogenic emissions through BEIS (Biogenic Emissions Inventory System) and MEGAN (Model of Emissions of Gases and Aerosols from Nature) into the atmosphere. In doing so, inconsistencies across model inputs and parameter data are resolved such that the emissions from a particular plant species are consistent with the heat and moisture fluxes calculated for that land cover type. In turn, the response of the atmospheric turbulence and mixing in the planetary boundary layer (PBL) acts on the identical surface type, fluxes, and emissions for each. In addition, the coupling of dust emission within the NU-WRF system is performed in order to ensure consistency and to maximize the benefit of high-resolution land representation in LIS. The impacts of those self-consistent components on' the simulation of atmospheric aerosols are then evaluated through the WRF-Chem-GOCART (Goddard Chemistry Aerosol Radiation and Transport) model. Overall, this ambitious project highlights the current difficulties and future potential of fully coupled. components. in Earth System models, and underscores the importance of the iLEAPS community in supporting improved knowledge of processes and innovative approaches for models and observations.

Effect of microgravity on several visual functions during STS shuttle missions

NASA Technical Reports Server (NTRS)

Oneal, Melvin R.; Task, H. Lee; Genco, Louis V.

1992-01-01

Changes in the acuity of astronaut vision during flight are discussed. Parameters such as critical flicker vision, stereopsis to 10 seconds of arc, visual acuity in small steps to 20/7.7, cyclophoria, lateral and vertical phoria and retinal rivalry were tested using a visual function tester. Twenty-three Space Transportation System (STS) astronauts participated in the experiments. Their vision was assessed twice before launch and after landing, and three to four times while on-orbit and landing. No significant differences during space flight were observed for any of the visual parameters tested. In some cases, slight changes in acuity and stereopsis were observed with a subsequent return to normal vision after flight.

The Shale Hills Sensorium for Embedded Sensors, Simulation, & Visualization: A Prototype for Land-Vegetation-Atmosphere Interactions

NASA Astrophysics Data System (ADS)

Duffy, C.

2008-12-01

The future of environmental observing systems will utilize embedded sensor networks with continuous real- time measurement of hydrologic, atmospheric, biogeochemical, and ecological variables across diverse terrestrial environments. Embedded environmental sensors, benefitting from advances in information sciences, networking technology, materials science, computing capacity, and data synthesis methods, are undergoing revolutionary change. It is now possible to field spatially-distributed, multi-node sensor networks that provide density and spatial coverage previously accessible only via numerical simulation. At the same time, computational tools are advancing rapidly to the point where it is now possible to simulate the physical processes controlling individual parcels of water and solutes through the complete terrestrial water cycle. Our goal for the Penn State Critical Zone Observatory is to apply environmental sensor arrays, integrated hydrologic models, and state-of-the-art visualization deployed and coordinated at a testbed within the Penn State Experimental Forest. The Shale Hills Hydro_Sensorium prototype proposed here is designed to observe land-atmosphere interactions in four-dimensional (space and time). The term Hydro_Sensorium implies the totality of physical sensors, models and visualization tools that allow us to perceive the detailed space and time complexities of the water and energy cycle for a watershed or river basin for all physical states and fluxes (groundwater, soil moisture, temperature, streamflow, latent heat, snowmelt, chemistry, isotopes etc.). This research will ultimately catalyze the study of complex interactions between the land surface, subsurface, biological and atmospheric systems over a broad range of scales. The sensor array would be real-time and fully controllable by remote users for "computational steering" and data fusion. Presently fully-coupled physical models are being developed that link the atmosphere-land-vegetation-subsurface system into a fully-coupled distributed system. During the last 5 years the Penn State Integrated Hydrologic Modeling System has been under development as an open-source community modeling project funded by NSF EAR/GEO and NSF CBET/ENG. PIHM represents a strategy for the formulation and solution of fully-coupled process equations at the watershed and river basin scales, and includes a tightly coupled GIS tool for data handling, domain decomposition, optimal unstructured grid generation, and model parameterization. The sensor and simulation system has the following elements: 1) extensive, spatially-distributed, non- invasive, smart sensor networks to gather massive geologic, hydrologic, and geochemical data; 2) stochastic information fusion methods; 3) spatially-explicit multiphysics models/solutions of the land-vegetation- atmosphere system; and 4) asynchronous, parallel/distributed, adaptive algorithms for rapidly simulating the states of a basin at high resolution, 5) signal processing tools for data mining and parameter estimation, and 6) visualization tools. The prototype proposed sensor array and simulation system proposed here will offer a coherent new approach to environmental predictions with a fully integrated observing system design. We expect that the Shale Hills Hydro_Sensorium may provide the needed synthesis of information and conceptualization necessary to advance predictive understanding in complex hydrologic systems.

Clarifying uncertainty in biogeochemical response to land management

NASA Astrophysics Data System (ADS)

Tonitto, C.; Gurwick, N. P.; Woodbury, P. B.

2013-12-01

We examined the ability of contemporary simulation and empirical modeling tools to describe net greenhouse gas (GHG) emissions as a result of agricultural and forest ecosystem land management, and we looked at how key policy institutions use these tools. We focused on quantification of nitrous oxide (N2O) emissions from agricultural systems, as agriculture is the dominant source of anthropogenic N2O emissions. Agricultural management impact on N2O emissions is especially challenging because controls on N2O emissions (soil aerobic status, inorganic N availability, and C substrate availability) vary as a function of site soil type, climate, and cropping system; available measurements do not cover all relevant combinations of these controlling system features. Furthermore, N2O emissions are highly non-linear, and threshold values of controlling soil environmental conditions are not defined across most agricultural site properties. We also examined the multi-faceted challenges regarding the quantification of increased soil organic carbon (SOC) storage as a result of land management in both agricultural and forest systems. Quantifying changes in SOC resulting from land management is difficult because mechanisms of SOC stabilization are not fully understood, SOC measurements have been concentrated in the upper 30cm of soil, erosion is often ignored when estimating SOC, and few long-term studies exist to track system response to diverse management practices. Furthermore, the permanence of SOC accumulating management practices is not easily established. For instance, under the Regional Greenhouse Gas Initiative (RGGI), forest land managed for SOC accumulation must remain under permanent conservation easement to ensure that SOC accumulation is not reversed due to changes in land cover. For agricultural protocols, given that many farmers rent land and that agriculture is driven by an annual management time scale, the ability to ensure SOC-accumulating land management would be maintained indefinitely has delayed the implementation of SOC accumulating practices for compliance with the California Global Warming Solutions Act (AB 32). GHG accounting tools are increasingly applied to implement GHG reduction policies. In this policy context, data limitation has impacted the implementation of GHG accounting strategies. For example, protocol design in support of AB 32 initially sought to apply simulation models to determine N2O emissions across all major U.S. agricultural landscapes. After discussion with ecosystem scientists, the lack of observations and model validation in most U.S. arable landscapes led to protocol definition based on simple empirical models and limited to corn management in 12 states. The distribution of protocol participants is also a potential source of inaccuracy in GHG accounting. Land management protocols are often structured assuming that in the aggregate policy achieves an average improvement by promoting specific management. However it is unclear that current policy incentives promote participation from a truly random distribution of landscapes. Participation in policy development to support improved land management challenges ecosystem scientists with making recommendations based on best-available information while acknowledging that uncertainty limits accurate quantification of impacts via analysis using either observations or simulation modeling.

Prediction of biological integrity based on environmental similarity--revealing the scale-dependent link between study area and top environmental predictors.

PubMed

Bedoya, David; Manolakos, Elias S; Novotny, Vladimir

2011-03-01

Indices of Biological integrity (IBI) are considered valid indicators of the overall health of a water body because the biological community is an endpoint within natural systems. However, prediction of biological integrity using information from multi-parameter environmental observations is a challenging problem due to the hierarchical organization of the natural environment, the existence of nonlinear inter-dependencies among variables as well as natural stochasticity and measurement noise. We present a method for predicting the Fish Index of Biological Integrity (IBI) using multiple environmental observations at the state-scale in Ohio. Instream (chemical and physical quality) and offstream parameters (regional and local upstream land uses, stream fragmentation, and point source density and intensity) are used for this purpose. The IBI predictions are obtained using the environmental site-similarity concept and following a simple to implement leave-one-out cross validation approach. An IBI prediction for a sampling site is calculated by averaging the observed IBI scores of observations clustered in the most similar branch of a dendrogram--a hierarchical clustering tree of environmental observations--built using the rest of the observations. The standardized Euclidean distance is used to assess dissimilarity between observations. The constructed predictive model was able to explain 61% of the IBI variability statewide. Stream fragmentation and regional land use explained 60% of the variability; the remaining 1% was explained by instream habitat quality. Metrics related to local land use, water quality, and point source density and intensity did not improve the predictive model at the state-scale. The impact of local environmental conditions was evaluated by comparing local characteristics between well- and mispredicted sites. Significant differences in local land use patterns and upstream fragmentation density explained some of the model's over-predictions. Local land use conditions explained some of the model's IBI under-predictions at the state-scale since none of the variables within this group were included in the best final predictive model. Under-predicted sites also had higher levels of downstream fragmentation. The proposed variables ranking and predictive modeling methodology is very well suited for the analysis of hierarchical environments, such as natural fresh water systems, with many cross-correlated environmental variables. It is computationally efficient, can be fully automated, does not make any pre-conceived assumptions on the variables interdependency structure (such as linearity), and it is able to rank variables in a database and generate IBI predictions using only non-parametric easy to implement hierarchical clustering. Copyright © 2011 Elsevier Ltd. All rights reserved.

Vegetation and terrain mapping in Alaska using Landsat MSS and digital terrain data

USGS Publications Warehouse

Shasby, Mark; Carneggie, David M.

1986-01-01

During the past 5 years, the U.S. Geological Survey's (USGS) Earth Resources Observation Systems (EROS) Data Center Field Office in Anchorage, Alaska has worked cooperatively with Federal and State resource management agencies to produce land-cover and terrain maps for 245 million acres of Alaska. The need for current land-cover information in Alaska comes principally from the mandates of the Alaska National Interest Lands Conservation Act (ANILCA), December 1980, which requires major land management agencies to prepare comprehensive management plans. The land-cover mapping projects integrate digital Landsat data, terrain data, aerial photographs, and field data. The resultant land-cover and terrain maps and associated data bases are used for resource assessment, management, and planning by many Alaskan agencies including the U.S. Fish and Wildlife Service, U.S. Forest Service, Bureau of Land Management, and Alaska Department of Natural Resources. Applications addressed through use of the digital land-cover and terrain data bases range from comprehensive refuge planning to multiphased sampling procedures designed to inventory vegetation statewide. The land-cover mapping programs in Alaska demonstrate the operational utility of digital Landsat data and have resulted in a new land-cover mapping program by the USGS National Mapping Division to compile 1:250,000-scale land-cover maps in Alaska using a common statewide land-cover map legend.

Evaluation of GLI Reflectance and Vegetation Indices With MODIS Products

DTIC Science & Technology

2005-07-25

collective picture of a warming world and other changes in the climate system . Vegetation over land surfaces contains carbon that is re- leased to atmosphere...irradiance based on Thuiller 2002 (Thuiller et al., 2003), Lsat[W/m2/str/µm] is GLI observed radiance, and θs[rad] is solor zenith angle. The GLI Project...longer wavelength than 2500nm, MODTRAN4.0 IR solor irradiance is used. GLI atmospheric correction for land is conducted for Rayleigh scattering and

Land And Forest Area Changes In The Vicinity Of The Mississippi River Gulf Outlet, Central Wetlands Region, 1935-2010

DTIC Science & Technology

2012-03-01

Abstract: As part of the overall Mississippi River Gulf Outlet (MRGO) Ecosystem Restoration Study , the Central Wetlands Unit (CWU) is a critical coastal...The CWU AU data set was digitized in a vector polygon format using ESRI ArcGIS ® software (Environmental Systems Research Institute, Redlands, CA). The...Terrebonne, and Mississippi River Delta basins . The majority of land loss observed in the CWU occurred within the 1935-1958, 1965-1978, and 2004-2006

A Dynamic Approach to Addressing Observation-Minus-Forecast Mean Differences in a Land Surface Skin Temperature Data Assimilation System

NASA Technical Reports Server (NTRS)

Draper, Clara; Reichle, Rolf; De Lannoy, Gabrielle; Scarino, Benjamin

2015-01-01

In land data assimilation, bias in the observation-minus-forecast (O-F) residuals is typically removed from the observations prior to assimilation by rescaling the observations to have the same long-term mean (and higher-order moments) as the corresponding model forecasts. Such observation rescaling approaches require a long record of observed and forecast estimates, and an assumption that the O-F mean differences are stationary. A two-stage observation bias and state estimation filter is presented, as an alternative to observation rescaling that does not require a long data record or assume stationary O-F mean differences. The two-stage filter removes dynamic (nonstationary) estimates of the seasonal scale O-F mean difference from the assimilated observations, allowing the assimilation to correct the model for synoptic-scale errors without adverse effects from observation biases. The two-stage filter is demonstrated by assimilating geostationary skin temperature (Tsk) observations into the Catchment land surface model. Global maps of the O-F mean differences are presented, and the two-stage filter is evaluated for one year over the Americas. The two-stage filter effectively removed the Tsk O-F mean differences, for example the GOES-West O-F mean difference at 21:00 UTC was reduced from 5.1 K for a bias-blind assimilation to 0.3 K. Compared to independent in situ and remotely sensed Tsk observations, the two-stage assimilation reduced the unbiased Root Mean Square Difference (ubRMSD) of the modeled Tsk by 10 of the open-loop values.

Evolution of Mesoscale Convective System over the South Western Peninsular India: Observations from Microwave Radiometer and Simulations using WRF

NASA Astrophysics Data System (ADS)

Uma, K. N.; Krishna Moorthy, K.; Sijikumar, S.; Renju, R.; Tinu, K. A.; Raju, Suresh C.

2012-07-01

Meso-scale Convective Systems (MCS) are important in view of their large cumulous build-up, vertical extent, short horizontal extent and associated thundershowers. The Microwave Radiometer Profiler (MRP) over the equatorial coastal station Thiruvanathapuram (Trivandrum, 8.55oN, 76.9oE), has been utilized to understand the genesis of Mesoscale convective system (MCS), that occur frequently during the pre-monsoon season. Examination of the measurement of relative humidity, temperature and cloud liquid water measurements, over the zenith and two scanning elevation angles (15o) viewing both over the land and the sea respectively revealed that the MCS generally originate over the land during early afternoon hours, propagate seawards over the observational site and finally dissipate over the sea, with accompanying rainfall and latent heat release. The simulations obtained using Advanced Research-Weather Research and Forecast (WRF-ARW) model effectively reproduces the thermodynamical and microphysical properties of the MCS. The time duration and quantity of rainfall obtained by the simulations also well compared with the observations. Analysis also suggests that wind shear in the upper troposphere is responsible for the growth and the shape of the convective cloud.

Rational Use of Land Resource During the Implementation of Transportless System of Coal Strata Surface Mining

NASA Astrophysics Data System (ADS)

Gvozdkova, T.; Tyulenev, M.; Zhironkin, S.; Trifonov, V. A.; Osipov, Yu M.

2017-01-01

Surface mining and open pits engineering affect the environment in a very negative way. Among other pollutions that open pits make during mineral deposits exploiting, particular problem is the landscape changing. Along with converting the land into pits, surface mining is connected with pilling dumps that occupy large ground. The article describes an analysis of transportless methods of several coal seams strata surface mining, applied for open pits of South Kuzbass coal enterprises (Western Siberia, Russia). To improve land-use management of open pit mining enterprises, the characteristics of transportless technological schemes for several coal seams strata surface mining are highlighted and observed. These characteristics help to systematize transportless open mining technologies using common criteria that characterize structure of the bottom part of a strata and internal dumping schemes. The schemes of transportless systems of coal strata surface mining implemented in South Kuzbass are given.

Assessing attainable intensification of global pasture systems at the 5 min x 5 min scale

NASA Astrophysics Data System (ADS)

Sheehan, J. J.; Lynd, L. R.; Allee, A.; Campbell, E. E.; Herrero, M.; Jaiswal, D.; Mueller, N. D.; Lamparelli, R.; Soares, J.

2017-12-01

Two-thirds of the world's agricultural land consist of pastures grazed by livestock. We use a recently published global dataset with information on feed consumption, animal stocks and productivity to analyze the intensification potential of pasture (grazing only) based production of meat and milk. Here we show that global output from pastures occupied by livestock circa 2000 could increase more than five-fold by simply raising their performance to the maximum achieved, climate-adjusted levels observed globally. The largest increases are in South America and sub Saharan Africa, where pasture systems are also more economically important. Furthermore, 40% of the land classified as pasture in the year 2000 had no animals on it. While pastureland currently contributes only a small fraction of total meat and milk production globally, such increases potentially offer an important new degree of freedom in addressing the challenge of sustainable stewardship of the earth's land resources.

Downscaling of Remotely Sensed Land Surface Temperature with multi-sensor based products

NASA Astrophysics Data System (ADS)

Jeong, J.; Baik, J.; Choi, M.

2016-12-01

Remotely sensed satellite data provides a bird's eye view, which allows us to understand spatiotemporal behavior of hydrologic variables at global scale. Especially, geostationary satellite continuously observing specific regions is useful to monitor the fluctuations of hydrologic variables as well as meteorological factors. However, there are still problems regarding spatial resolution whether the fine scale land cover can be represented with the spatial resolution of the satellite sensor, especially in the area of complex topography. To solve these problems, many researchers have been trying to establish the relationship among various hydrological factors and combine images from multi-sensor to downscale land surface products. One of geostationary satellite, Communication, Ocean and Meteorological Satellite (COMS), has Meteorological Imager (MI) and Geostationary Ocean Color Imager (GOCI). MI performing the meteorological mission produce Rainfall Intensity (RI), Land Surface Temperature (LST), and many others every 15 minutes. Even though it has high temporal resolution, low spatial resolution of MI data is treated as major research problem in many studies. This study suggests a methodology to downscale 4 km LST datasets derived from MI in finer resolution (500m) by using GOCI datasets in Northeast Asia. Normalized Difference Vegetation Index (NDVI) recognized as variable which has significant relationship with LST are chosen to estimate LST in finer resolution. Each pixels of NDVI and LST are separated according to land cover provided from MODerate resolution Imaging Spectroradiometer (MODIS) to achieve more accurate relationship. Downscaled LST are compared with LST observed from Automated Synoptic Observing System (ASOS) for assessing its accuracy. The downscaled LST results of this study, coupled with advantage of geostationary satellite, can be applied to observe hydrologic process efficiently.

Using landscape ecology to test hypotheses about large-scale abundance patterns in migratory birds

USGS Publications Warehouse

Flather, C.H.; Sauer, J.R.

1996-01-01

The hypothesis that Neotropical migrant birds may be undergoing widespread declines due to land use activities on the breeding grounds has been examined primarily by synthesizing results from local studies. Growing concern for the cumulative influence of land use activities on ecological systems has heightened the need for large-scale studies to complement what has been observed at local scales. We investigated possible landscape effects on Neotropical migrant bird populations for the eastern United States by linking two large-scale inventories designed to monitor breeding-bird abundances and land use patterns. The null hypothesis of no relation between landscape structure and Neotropical migrant abundance was tested by correlating measures of landscape structure with bird abundance, while controlling for the geographic distance among samples. Neotropical migrants as a group were more 'sensitive' to landscape structure than either temperate migrants or permanent residents. Neotropical migrants tended to be more abundant in landscapes with a greater proportion of forest and wetland habitats, fewer edge habitats, large forest patches, and with forest habitats well dispersed throughout the scene. Permanent residents showed few correlations with landscape structure and temperate migrants were associated with habitat diversity and edge attributes rather than with the amount, size, and dispersion of forest habitats. The association between Neotropical migrant abundance and forest fragmentation differed among physiographic strata, suggesting that land-scape context affects observed relations between bird abundance and landscape structure. Finally, associations between landscape structure and temporal trends in Neotropical migrant abundance were negatively correlated with forest habitats. These results suggest that extrapolation of patterns observed in some landscapes is not likely to hold regionally, and that conservation policies must consider the variation in landscape structure associations observed among different types of bird species and in physiographic strata with varying land use histories.

43 CFR 2650.4-6 - National wildlife refuge system lands.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 43 Public Lands: Interior 2 2011-10-01 2011-10-01 false National wildlife refuge system lands... SELECTIONS Alaska Native Selections: Generally § 2650.4-6 National wildlife refuge system lands. (a) Every conveyance which includes lands within the national wildlife refuge system shall, as to such lands, provide...

43 CFR 2650.4-6 - National wildlife refuge system lands.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 43 Public Lands: Interior 2 2013-10-01 2013-10-01 false National wildlife refuge system lands... SELECTIONS Alaska Native Selections: Generally § 2650.4-6 National wildlife refuge system lands. (a) Every conveyance which includes lands within the national wildlife refuge system shall, as to such lands, provide...

43 CFR 2650.4-6 - National wildlife refuge system lands.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 43 Public Lands: Interior 2 2012-10-01 2012-10-01 false National wildlife refuge system lands... SELECTIONS Alaska Native Selections: Generally § 2650.4-6 National wildlife refuge system lands. (a) Every conveyance which includes lands within the national wildlife refuge system shall, as to such lands, provide...

43 CFR 2650.4-6 - National wildlife refuge system lands.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 43 Public Lands: Interior 2 2014-10-01 2014-10-01 false National wildlife refuge system lands... SELECTIONS Alaska Native Selections: Generally § 2650.4-6 National wildlife refuge system lands. (a) Every conveyance which includes lands within the national wildlife refuge system shall, as to such lands, provide...

Global Soil Moisture Estimation through a Coupled CLM4-RTM-DART Land Data Assimilation System

NASA Astrophysics Data System (ADS)

Zhao, L.; Yang, Z. L.; Hoar, T. J.

2016-12-01

Very few frameworks exist that estimate global-scale soil moisture through microwave land data assimilation (DA). Toward this goal, we have developed such a framework by linking the Community Land Model version 4 (CLM4) and a microwave radiative transfer model (RTM) with the Data Assimilation Research Testbed (DART). The deterministic Ensemble Adjustment Kalman Filter (EAKF) within the DART is utilized to estimate global multi-layer soil moisture by assimilating brightness temperature observations from the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E). A 40-member of Community Atmosphere Model version 4 (CAM4) reanalysis is adopted to drive CLM4 simulations. Spatial-specific time-invariant microwave parameters are pre-calibrated to minimize uncertainties in RTM. Besides, various methods are designed in consideration of computational efficiency. A series of experiments are conducted to quantify the DA sensitivity to microwave parameters, choice of assimilated observations, and different CLM4 updating schemes. Evaluation results indicate that the newly established CLM4-RTM-DART framework improves the open-loop CLM4 simulated soil moisture. Pre-calibrated microwave parameters, rather than their default values, can ensure a more robust global-scale performance. In addition, updating near-surface soil moisture is capable of improving soil moisture in deeper layers, while simultaneously updating multi-layer soil moisture fails to obtain intended improvements. We will show in this presentation the architecture of the CLM4-RTM-DART system and the evaluations on AMSR-E DA. Preliminary results on multi-sensor DA that integrates various satellite observations including GRACE, MODIS, and AMSR-E will also be presented. ReferenceZhao, L., Z.-L. Yang, and T. J. Hoar, 2016. Global Soil Moisture Estimation by Assimilating AMSR-E Brightness Temperatures in a Coupled CLM4-RTM-DART System. Journal of Hydrometeorology, DOI: 10.1175/JHM-D-15-0218.1.

SCS-CN parameter determination using rainfall-runoff data in heterogeneous watersheds - the two-CN system approach

NASA Astrophysics Data System (ADS)

Soulis, K. X.; Valiantzas, J. D.

2012-03-01

The Soil Conservation Service Curve Number (SCS-CN) approach is widely used as a simple method for predicting direct runoff volume for a given rainfall event. The CN parameter values corresponding to various soil, land cover, and land management conditions can be selected from tables, but it is preferable to estimate the CN value from measured rainfall-runoff data if available. However, previous researchers indicated that the CN values calculated from measured rainfall-runoff data vary systematically with the rainfall depth. Hence, they suggested the determination of a single asymptotic CN value observed for very high rainfall depths to characterize the watersheds' runoff response. In this paper, the hypothesis that the observed correlation between the calculated CN value and the rainfall depth in a watershed reflects the effect of soils and land cover spatial variability on its hydrologic response is being tested. Based on this hypothesis, the simplified concept of a two-CN heterogeneous system is introduced to model the observed CN-rainfall variation by reducing the CN spatial variability into two classes. The behaviour of the CN-rainfall function produced by the simplified two-CN system is approached theoretically, it is analysed systematically, and it is found to be similar to the variation observed in natural watersheds. Synthetic data tests, natural watersheds examples, and detailed study of two natural experimental watersheds with known spatial heterogeneity characteristics were used to evaluate the method. The results indicate that the determination of CN values from rainfall runoff data using the proposed two-CN system approach provides reasonable accuracy and it over performs the previous methods based on the determination of a single asymptotic CN value. Although the suggested method increases the number of unknown parameters to three (instead of one), a clear physical reasoning for them is presented.

Recent decline in the global land evapotranspiration trend due to limited moisture supply.

PubMed

Jung, Martin; Reichstein, Markus; Ciais, Philippe; Seneviratne, Sonia I; Sheffield, Justin; Goulden, Michael L; Bonan, Gordon; Cescatti, Alessandro; Chen, Jiquan; de Jeu, Richard; Dolman, A Johannes; Eugster, Werner; Gerten, Dieter; Gianelle, Damiano; Gobron, Nadine; Heinke, Jens; Kimball, John; Law, Beverly E; Montagnani, Leonardo; Mu, Qiaozhen; Mueller, Brigitte; Oleson, Keith; Papale, Dario; Richardson, Andrew D; Roupsard, Olivier; Running, Steve; Tomelleri, Enrico; Viovy, Nicolas; Weber, Ulrich; Williams, Christopher; Wood, Eric; Zaehle, Sönke; Zhang, Ke

2010-10-21

More than half of the solar energy absorbed by land surfaces is currently used to evaporate water. Climate change is expected to intensify the hydrological cycle and to alter evapotranspiration, with implications for ecosystem services and feedback to regional and global climate. Evapotranspiration changes may already be under way, but direct observational constraints are lacking at the global scale. Until such evidence is available, changes in the water cycle on land−a key diagnostic criterion of the effects of climate change and variability−remain uncertain. Here we provide a data-driven estimate of global land evapotranspiration from 1982 to 2008, compiled using a global monitoring network, meteorological and remote-sensing observations, and a machine-learning algorithm. In addition, we have assessed evapotranspiration variations over the same time period using an ensemble of process-based land-surface models. Our results suggest that global annual evapotranspiration increased on average by 7.1 ± 1.0 millimetres per year per decade from 1982 to 1997. After that, coincident with the last major El Niño event in 1998, the global evapotranspiration increase seems to have ceased until 2008. This change was driven primarily by moisture limitation in the Southern Hemisphere, particularly Africa and Australia. In these regions, microwave satellite observations indicate that soil moisture decreased from 1998 to 2008. Hence, increasing soil-moisture limitations on evapotranspiration largely explain the recent decline of the global land-evapotranspiration trend. Whether the changing behaviour of evapotranspiration is representative of natural climate variability or reflects a more permanent reorganization of the land water cycle is a key question for earth system science.

"Global warming, continental drying? Interpreting projected aridity changes over land under climate change"

NASA Astrophysics Data System (ADS)

Berg, Alexis

2017-04-01

In recent years, a number of studies have suggested that, as climate warms, the land surface will globally become more arid. Such results usually rely on drought or aridity diagnostics, such as the Palmer Drought Severity Index or the Aridity Index (ratio of precipitation over potential evapotranspiration, PET), applied to climate model projections of surface climate. From a global perspective, the projected widespread drying of the land surface is generally interpreted as the result of the dominant, ubiquitous warming-induced PET increase, which overwhelms the slight overall precipitation increase projected over land. However, several lines of evidence, based on (paleo)observations and climate model projections, raise questions regarding this interpretation of terrestrial climate change. In this talk, I will review elements of the literature supporting these different perspectives, and will present recent results based on CMIP5 climate model projections regarding changes in aridity over land that shed some light on this discussion. Central to the interpretation of projected land aridity changes is the understanding of projected PET trends over land and their link with changes in other variables of the terrestrial water cycle (ET, soil moisture) and surface climate in the context of the coupled land-atmosphere system.

Validation of Land-Surface Mosaic Heterogeneity in the GEOS DAS

NASA Technical Reports Server (NTRS)

Bosilovich, Michael G.; Molod, Andrea; Houser, Paul R.; Schubert, Siegfried

1999-01-01

The Mosaic Land-surface Model (LSM) has been included into the current GEOS Data Assimilation System (DAS). The LSM uses a more advanced representation of physical processes than previous versions of the GEOS DAS, including the representation of sub-grid heterogeneity of the land-surface through the Mosaic approach. As a first approximation, Mosaic assumes that all similar surface types within a grid-cell can be lumped together as a single'tile'. Within one GCM grid-cell, there might be 1 - 5 different tiles or surface types. All tiles are subjected to the grid-scale forcing (radiation, air temperature and specific humidity, and precipitation), and the sub-grid variability is a function of the tile characteristics. In this paper, we validate the LSM sub-grid scale variability (tiles) using a variety of surface observing stations from the Southern Great Plains (SGP) site of the Atmospheric Radiation Measurement (ARM) Program. One of the primary goals of SGP ARM is to study the variability of atmospheric radiation within a G,CM grid-cell. Enough surface data has been collected by ARM to extend this goal to sub-grid variability of the land-surface energy and water budgets. The time period of this study is the Summer of 1998 (June I - September 1). The ARM site data consists of surface meteorology, energy flux (eddy correlation and bowen ratio), soil water observations spread over an area similar to the size of a G-CM grid-cell. Various ARM stations are described as wheat and alfalfa crops, pasture and range land. The LSM tiles considered at the grid-space (2 x 2.5) nearest the ARM site include, grassland, deciduous forests, bare soil and dwarf trees. Surface energy and water balances for each tile type are compared with observations. Furthermore, we will discuss the land-surface sub-grid variability of both the ARM observations and the DAS.

Evaluation of multiple forcing data sets for precipitation and shortwave radiation over major land areas of China

NASA Astrophysics Data System (ADS)

Yang, Fan; Lu, Hui; Yang, Kun; He, Jie; Wang, Wei; Wright, Jonathon S.; Li, Chengwei; Han, Menglei; Li, Yishan

2017-11-01

Precipitation and shortwave radiation play important roles in climatic, hydrological and biogeochemical cycles. Several global and regional forcing data sets currently provide historical estimates of these two variables over China, including the Global Land Data Assimilation System (GLDAS), the China Meteorological Administration (CMA) Land Data Assimilation System (CLDAS) and the China Meteorological Forcing Dataset (CMFD). The CN05.1 precipitation data set, a gridded analysis based on CMA gauge observations, also provides high-resolution historical precipitation data for China. In this study, we present an intercomparison of precipitation and shortwave radiation data from CN05.1, CMFD, CLDAS and GLDAS during 2008-2014. We also validate all four data sets against independent ground station observations. All four forcing data sets capture the spatial distribution of precipitation over major land areas of China, although CLDAS indicates smaller annual-mean precipitation amounts than CN05.1, CMFD or GLDAS. Time series of precipitation anomalies are largely consistent among the data sets, except for a sudden decrease in CMFD after August 2014. All forcing data indicate greater temporal variations relative to the mean in dry regions than in wet regions. Validation against independent precipitation observations provided by the Ministry of Water Resources (MWR) in the middle and lower reaches of the Yangtze River indicates that CLDAS provides the most realistic estimates of spatiotemporal variability in precipitation in this region. CMFD also performs well with respect to annual mean precipitation, while GLDAS fails to accurately capture much of the spatiotemporal variability and CN05.1 contains significant high biases relative to the MWR observations. Estimates of shortwave radiation from CMFD are largely consistent with station observations, while CLDAS and GLDAS greatly overestimate shortwave radiation. All three forcing data sets capture the key features of the spatial distribution, but estimates from CLDAS and GLDAS are systematically higher than those from CMFD over most of mainland China. Based on our evaluation metrics, CLDAS slightly outperforms GLDAS. CLDAS is also closer than GLDAS to CMFD with respect to temporal variations in shortwave radiation anomalies, with substantial differences among the time series. Differences in temporal variations are especially pronounced south of 34° N. Our findings provide valuable guidance for a variety of stakeholders, including land-surface modelers and data providers.

Earth Observing System. Volume 1, Part 2: Science and Mission Requirements. Working Group Report Appendix

NASA Technical Reports Server (NTRS)

1984-01-01

Areas of global hydrologic cycles, global biogeochemical cycles geophysical processes are addressed including biological oceanography, inland aquatic resources, land biology, tropospheric chemistry, oceanic transport, polar glaciology, sea ice and atmospheric chemistry.

Results of scatterometer systems analysis for NASA/MSC Earth Observation Sensor Evaluation Program.

NASA Technical Reports Server (NTRS)

Krishen, K.; Vlahos, N.; Brandt, O.; Graybeal, G.

1971-01-01

Radar scatterometers have applications in the NASA/MSC Earth Observation Aircraft Program. Over a period of several years, several missions have been flown over both land and ocean. In this paper a system evaluation of the NASA/MSC 13.3-GHz Scatterometer System is presented. The effects of phase error between the Scatterometer channels, antenna pattern deviations, aircraft attitude deviations, environmental changes, and other related factors such as processing errors, system repeatability, and propeller modulation, were established. Furthermore, the reduction in system errors and calibration improvement was investigated by taking into account these parameter deviations. Typical scatterometer data samples are presented.

System study of the carbon dioxide observational platform system (CO-OPS): Project overview

NASA Technical Reports Server (NTRS)

Stephens, J. Briscoe; Thompson, Wilbur E.

1987-01-01

The resulting options from a system study for a near-space, geo-stationary, observational monitoring platform system for use in the Department of Energy's (DOE) National Carbon Dioxide Observational Platform System (CO-OPS) on the greenhouse effect are discussed. CO-OPS is being designed to operate continuously for periods of up to 3 months in quasi-fixed position over most global regional targets of interest and could make horizon observations over a land-sea area of circular diameter up to about 600 to 800 statute miles. This affords the scientific and engineering community a low-cost means of operating their payloads for monitoring the regional parameters they deem relevant to their investigations of the carbon dioxide greenhouse effect at one-tenth the cost of most currently utilized comparable remote sensing techniques.

Assessing the Regional/Diurnal Bias between Satellite Retrievals and GEOS-5/MERRA Model Estimates of Land Surface Temperature

NASA Astrophysics Data System (ADS)

Scarino, B. R.; Smith, W. L., Jr.; Minnis, P.; Bedka, K. M.

2017-12-01

Atmospheric models rely on high-accuracy, high-resolution initial radiometric and surface conditions for better short-term meteorological forecasts, as well as improved evaluation of global climate models. Continuous remote sensing of the Earth's energy budget, as conducted by the Clouds and Earth's Radiant Energy System (CERES) project, allows for near-realtime evaluation of cloud and surface radiation properties. It is unfortunately common for there to be bias between atmospheric/surface radiation models and Earth-observations. For example, satellite-observed surface skin temperature (Ts), an important parameter for characterizing the energy exchange at the ground/water-atmosphere interface, can be biased due to atmospheric adjustment assumptions and anisotropy effects. Similarly, models are potentially biased by errors in initial conditions and regional forcing assumptions, which can be mitigated through assimilation with true measurements. As such, when frequent, broad-coverage, and accurate retrievals of satellite Ts are available, important insights into model estimates of Ts can be gained. The Satellite ClOud and Radiation Property retrieval System (SatCORPS) employs a single-channel thermal-infrared method to produce anisotropy-corrected Ts over clear-sky land and ocean surfaces from data taken by geostationary Earth orbit (GEO) satellite imagers. Regional and diurnal changes in model land surface temperature (LST) performance can be assessed owing to the somewhat continuous measurements of the LST offered by GEO satellites - measurements which are accurate to within 0.2 K. A seasonal, hourly comparison of satellite-observed LST with the NASA Goddard Earth Observing System Version 5 (GEOS-5) and the Modern-Era Retrospective Analysis for Research and Applications (MERRA) LST estimates is conducted to reveal regional and diurnal biases. This assessment is an important first step for evaluating the effectiveness of Ts assimilation, as well for determining the impact anisotropy correction has on observation - model bias, and is of critical importance for CERES.

Exploring Agricultural Livelihood Transitions with an Agent-Based Virtual Laboratory: Global Forces to Local Decision-Making

PubMed Central

Magliocca, Nicholas R.; Brown, Daniel G.; Ellis, Erle C.

2013-01-01

Rural populations are undergoing rapid changes in both their livelihoods and land uses, with associated impacts on ecosystems, global biogeochemistry, and climate change. A primary challenge is, thus, to explain these shifts in terms of the actors and processes operating within a variety of land systems in order to understand how land users might respond locally to future changes in broader-scale environmental and economic conditions. Using ‘induced intensification’ theory as a benchmark, we develop a generalized agent-based model to investigate mechanistic explanations of relationships between agricultural intensity and population density, environmental suitability, and market influence. Land-use and livelihood decisions modeled from basic micro-economic theories generated spatial and temporal patterns of agricultural intensification consistent with predictions of induced intensification theory. Further, agent actions in response to conditions beyond those described by induced intensification theory were explored, revealing that interactions among environmental constraints, population pressure, and market influence may produce transitions to multiple livelihood regimes of varying market integration. The result is new hypotheses that could modify and enrich understanding of the classic relationship between agricultural intensity and population density. The strength of this agent-based model and the experimental results is the generalized form of the decision-making processes underlying land-use and livelihood transitions, creating the prospect of a virtual laboratory for systematically generating hypotheses of how agent decisions and interactions relate to observed land-use and livelihood patterns across diverse land systems. PMID:24039892

Disentangling Climate and Land-use Impacts on Grassland Carbon and Water Fluxes

NASA Astrophysics Data System (ADS)

Brunsell, N. A.; Nippert, J. B.

2014-12-01

Regional climate and land cover interact in a complex, non-linear manner to alter the local cycling of mass and energy. It is often difficult to isolate the role of either mechanism on the resultant fluxes. Here, we attempt to isolate these mechanisms through the use of network of 4 Ameriflux eddy covariance towers installed over different land cover and land use classes along a pronounced rainfall gradient. The land cover types include: annually burned C4 grassland, a 4 year burn site experiencing woody encroachment, an abandoned agricultural field and a new perennial agricultural site. We investigated the impact of rainfall variability, drought, and heat waves on the water and carbon budgets using data analysis, remote sensing, and modeling approaches. In addition, we have established a network of mini-meteorological stations at the annually and 4-year burn sites to assess micro-scale variability within the footprints of the towers as a function of topographic position, soil depth and soil water availability. Through the use of a wavelet multiscale decomposition and information theory metrics, we have isolated the role of environmental factors (temperature, humidity, soil moisture, etc.) on the fluxes across the different sites. By applying a similar analysis to model output, we can assess the ability of land-surface models to recreate the observed sensitity. Results indicate the utility of a network of measurement systems used in conjunction with land surface modeling and time series analysis to assess differential impacts to similar regional scale climate forcings. Implications for the role of land cover class in regional and global scale modeling systems will also be discussed.

Hydraulic and mechanical properties affecting ground-water flow and aquifer-system compaction, San Joaquin Valley, California

USGS Publications Warehouse

Sneed, Michelle

2001-01-01

This report summarizes hydraulic and mechanical properties affecting ground-water flow and aquifer-system compaction in the San Joaquin Valley, a broad alluviated intermontane structural trough that constitutes the southern two-thirds of the Central Valley of California. These values will be used to constrain a coupled ground-water flow and aquifer-system compaction model of the western San Joaquin Valley called WESTSIM. A main objective of the WESTSIM model is to evaluate potential future land subsidence that might occur under conditions in which deliveries of imported surface water for agricultural use are reduced and ground-water pumping is increased. Storage values generally are components of the total aquifer-system storage and include inelastic and elastic skeletal storage values of the aquifers and the aquitards that primarily govern the potential amount of land subsidence. Vertical hydraulic conductivity values generally are for discrete thicknesses of sediments, usually aquitards, that primarily govern the rate of land subsidence. The data were compiled from published sources and include results of aquifer tests, stress-strain analyses of borehole extensometer observations, laboratory consolidation tests, and calibrated models of aquifer-system compaction.

Arctic transitions in the Land - Atmosphere System (ATLAS): Background, objectives, results, and future directions

USGS Publications Warehouse

McGuire, A.D.; Sturm, M.; Chapin, F. S.

2003-01-01

This paper briefly reviews the background, objectives, and results of the Arctic Transitions in the Land-Atmosphere System (ATLAS) Project to date and provides thoughts on future directions. The key goal of the ATLAS Project is to improve understanding of controls over spatial and temporal variability of terrestrial processes in the Arctic that have potential consequences for the climate system, i.e., processes that affect the exchange of water and energy with the atmosphere, the exchange of radiatively active gases with the atmosphere, and the delivery of freshwater to the Arctic Ocean. Three important conclusions have emerged from research associated with the ATLAS Project. First, associated with the observation that the Alaskan Arctic has warmed significantly in the last 30 years, permafrost is warming, shrubs are expanding, and there has been a temporary release of carbon dioxide from tundra soils. Second, the winter is a more important period of biological activity than previously appreciated. Biotic processes, including shrub expansion and decomposition, affect snow structure and accumulation and affect the annual carbon budget of tundra ecosystems. Third, observed vegetation changes can have a significant positive feedback to regional warming. These vegetation effects are, however, less strong than those exerted by land-ocean heating contrasts and the topographic constraints on air mass movements. The papers of this special section provide additional insights related to these conclusions and to the overall goal of ATLAS.

Estimation of ICBM (Intercontinental Ballistic Missile) Performance Parameters

DTIC Science & Technology

1985-12-01

Formulation . . . . . 42 Staging Event Detection . . . . . . 43 Staging Estimator for Two State System . 46 * Staging Time and Vehicle Parameter...6 4. Land Based Sensor Coordinate System . . . . 10 5. Radar Site Geometry . . . . . . . . . 1 6. Observation Geometry . . . . . . . . . 12 7...Ve dm mi + dmi+d Figure 3. Rocket Thrust of fuel, the equation of motion of the rocket can be devel--S oped. This is a closed system of particles

Overview of NASA's Carbon Monitoring System Flux-Pilot Project

NASA Technical Reports Server (NTRS)

Pawson, Steven; Gunson, Michael R.; Jucks, Kenneth

2011-01-01

NASA's space-based observations of physical, chemical and biological parameters in the Earth System along with state-of-the-art modeling capabilities provide unique capabilities for analyses of the carbon cycle. The Carbon Monitoring System is developing an exploratory framework for detecting carbon in the environment and its changes, with a view towards contributing to national and international monitoring activities. The Flux-Pilot Project aims to provide a unified view of land-atmosphere and ocean-atmosphere carbon exchange, using observation-constrained models. Central to the project is the application of NASA's satellite observations (especially MODIS), the ACOS retrievals of the JAXA-GOSAT observations, and the "MERRA" meteorological reanalysis produced with GEOS-S. With a primary objective of estimating uncertainty in computed fluxes, two land- and two ocean-systems are run for 2009-2010 and compared with existing flux estimates. An transport model is used to evaluate simulated CO2 concentrations with in-situ and space-based observations, in order to assess the realism of the fluxes and how uncertainties in fluxes propagate into atmospheric concentrations that can be more readily evaluated. Finally, the atmospheric partial CO2 columns observed from space are inverted to give new estimates of surface fluxes, which are evaluated using the bottom-up estimates and independent datasets. The focus of this presentation will be on the science goals and current achievements of the pilot project, with emphasis on how policy-relevant questions help focus the scientific direction. Examples include the issue of what spatio-temporal resolution of fluxes can be detected from polar-orbiting satellites and whether it is possible to use space-based observations to separate contributions to atmospheric concentrations of (say) fossil-fuel and biological activity

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.

Development of a WRF-RTFDDA-based high-resolution hybrid data-assimilation and forecasting system toward to operation in the Middle East

NASA Astrophysics Data System (ADS)

Liu, Y.; Wu, W.; Zhang, Y.; Kucera, P. A.; Liu, Y.; Pan, L.

2012-12-01

Weather forecasting in the Middle East is challenging because of its complicated geographical nature including massive coastal area and heterogeneous land, and regional spare observational network. Strong air-land-sea interactions form multi-scale weather regimes in the area, which require a numerical weather prediction model capable of properly representing multi-scale atmospheric flow with appropriate initial conditions. The WRF-based Real-Time Four Dimensional Data Assimilation (RTFDDA) system is one of advanced multi-scale weather analysis and forecasting facilities developed at the Research Applications Laboratory (RAL) of NCAR. The forecasting system is applied for the Middle East with careful configuration. To overcome the limitation of the very sparsely available conventional observations in the region, we develop a hybrid data assimilation algorithm combining RTFDDA and WRF-3DVAR, which ingests remote sensing data from satellites and radar. This hybrid data assimilation blends Newtonian nudging FDDA and 3DVAR technology to effectively assimilate both conventional observations and remote sensing measurements and provide improved initial conditions for the forecasting system. For brevity, the forecasting system is called RTF3H (RTFDDA-3DVAR Hybrid). In this presentation, we will discuss the hybrid data assimilation algorithm, and its implementation, and the applications for high-impact weather events in the area. Sensitivity studies are conducted to understand the strength and limitations of this hybrid data assimilation algorithm.

SEARCH Workshop on Large-Scale Atmosphere/Cryosphere Observations

NASA Technical Reports Server (NTRS)

2002-01-01

The purpose of the workshop held in Seattle during 27-29 November 2001 was to review existing land, sea ice, and atmospheric observations and the prospect for an Arctic System Reanalysis, through white papers, invited speakers, and panels. A major task for SEARCH was to determine how existing observation systems can be best used and enhanced to understand and anticipate the course of the ongoing changes in the Arctic. The primary workshop conclusion is that there is no cohesion among various Arctic disciplines and data types to form a complete observation set of Arctic change; a second workshop conclusion is that present data sets are vastly underutilized in understanding Arctic change; a third conclusion is that a distributed observing system must accommodate a wide range of spatial patterns of variability.

Asymptotic Parachute Performance Sensitivity

NASA Technical Reports Server (NTRS)

Way, David W.; Powell, Richard W.; Chen, Allen; Steltzner, Adam D.

2006-01-01

In 2010, the Mars Science Laboratory mission will pioneer the next generation of robotic Entry, Descent, and Landing systems by delivering the largest and most capable rover to date to the surface of Mars. In addition to landing more mass than any other mission to Mars, Mars Science Laboratory will also provide scientists with unprecedented access to regions of Mars that have been previously unreachable. By providing an Entry, Descent, and Landing system capable of landing at altitudes as high as 2 km above the reference gravitational equipotential surface, or areoid, as defined by the Mars Orbiting Laser Altimeter program, Mars Science Laboratory will demonstrate sufficient performance to land on 83% of the planet s surface. By contrast, the highest altitude landing to date on Mars has been the Mars Exploration Rover at 1.3 km below the areoid. The coupling of this improved altitude performance with latitude limits as large as 60 degrees off of the equator and a precise delivery to within 10 km of a surface target, will allow the science community to select the Mars Science Laboratory landing site from thousands of scientifically interesting possibilities. In meeting these requirements, Mars Science Laboratory is extending the limits of the Entry, Descent, and Landing technologies qualified by the Mars Viking, Mars Pathfinder, and Mars Exploration Rover missions. Specifically, the drag deceleration provided by a Viking-heritage 16.15 m supersonic Disk-Gap-Band parachute in the thin atmosphere of Mars is insufficient, at the altitudes and ballistic coefficients under consideration by the Mars Science Laboratory project, to maintain necessary altitude performance and timeline margin. This paper defines and discusses the asymptotic parachute performance observed in Monte Carlo simulation and performance analysis and its effect on the Mars Science Laboratory Entry, Descent, and Landing architecture.

Integrating in-situ, Landsat, and MODIS data for mapping in Southern African savannas: experiences of LCCS-based land-cover mapping in the Kalahari in Namibia.

PubMed

Hüttich, Christian; Herold, Martin; Strohbach, Ben J; Dech, Stefan

2011-05-01

Integrated ecosystem assessment initiatives are important steps towards a global biodiversity observing system. Reliable earth observation data are key information for tracking biodiversity change on various scales. Regarding the establishment of standardized environmental observation systems, a key question is: What can be observed on each scale and how can land cover information be transferred? In this study, a land cover map from a dry semi-arid savanna ecosystem in Namibia was obtained based on the UN LCCS, in-situ data, and MODIS and Landsat satellite imagery. In situ botanical relevé samples were used as baseline data for the definition of a standardized LCCS legend. A standard LCCS code for savanna vegetation types is introduced. An object-oriented segmentation of Landsat imagery was used as intermediate stage for downscaling in-situ training data on a coarse MODIS resolution. MODIS time series metrics of the growing season 2004/2005 were used to classify Kalahari vegetation types using a tree-based ensemble classifier (Random Forest). The prevailing Kalahari vegetation types based on LCCS was open broadleaved deciduous shrubland with an herbaceous layer which differs from the class assignments of the global and regional land-cover maps. The separability analysis based on Bhattacharya distance measurements applied on two LCCS levels indicated a relationship of spectral mapping dependencies of annual MODIS time series features due to the thematic detail of the classification scheme. The analysis of LCCS classifiers showed an increased significance of life-form composition and soil conditions to the mapping accuracy. An overall accuracy of 92.48% was achieved. Woody plant associations proved to be most stable due to small omission and commission errors. The case study comprised a first suitability assessment of the LCCS classifier approach for a southern African savanna ecosystem.

Improving land surface emissivty parameter for land surface models using portable FTIR and remote sensing observation in Taklimakan Desert

NASA Astrophysics Data System (ADS)

Liu, Yongqiang; Mamtimin, Ali; He, Qing

2014-05-01

Because land surface emissivity (ɛ) has not been reliably measured, global climate model (GCM) land surface schemes conventionally set this parameter as simply assumption, for example, 1 as in the National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Prediction (NCEP) model, 0.96 for soil and wetland in the Global and Regional Assimilation and Prediction System (GRAPES) Common Land Model (CoLM). This is the so-called emissivity assumption. Accurate broadband emissivity data are needed as model inputs to better simulate the land surface climate. It is demonstrated in this paper that the assumption of the emissivity induces errors in modeling the surface energy budget over Taklimakan Desert where ɛ is far smaller than original value. One feasible solution to this problem is to apply the accurate broadband emissivity into land surface models. The Moderate Resolution Imaging Spectroradiometer (MODIS) instrument has routinely measured spectral emissivities in six thermal infrared bands. The empirical regression equations have been developed in this study to convert these spectral emissivities to broadband emissivity required by land surface models. In order to calibrate the regression equations, using a portable Fourier Transform infrared (FTIR) spectrometer instrument, crossing Taklimakan Desert along with highway from north to south, to measure the accurate broadband emissivity. The observed emissivity data show broadband ɛ around 0.89-0.92. To examine the impact of improved ɛ to radiative energy redistribution, simulation studies were conducted using offline CoLM. The results illustrate that large impacts of surface ɛ occur over desert, with changes up in surface skin temperature, as well as evident changes in sensible heat fluxes. Keywords: Taklimakan Desert, surface broadband emissivity, Fourier Transform infrared spectrometer, MODIS, CoLM

Global Land Product Validation Protocols: An Initiative of the CEOS Working Group on Calibration and Validation to Evaluate Satellite-derived Essential Climate Variables

NASA Astrophysics Data System (ADS)

Guillevic, P. C.; Nickeson, J. E.; Roman, M. O.; camacho De Coca, F.; Wang, Z.; Schaepman-Strub, G.

2016-12-01

The Global Climate Observing System (GCOS) has specified the need to systematically produce and validate Essential Climate Variables (ECVs). The Committee on Earth Observation Satellites (CEOS) Working Group on Calibration and Validation (WGCV) and in particular its subgroup on Land Product Validation (LPV) is playing a key coordination role leveraging the international expertise required to address actions related to the validation of global land ECVs. The primary objective of the LPV subgroup is to set standards for validation methods and reporting in order to provide traceable and reliable uncertainty estimates for scientists and stakeholders. The Subgroup is comprised of 9 focus areas that encompass 10 land surface variables. The activities of each focus area are coordinated by two international co-leads and currently include leaf area index (LAI) and fraction of absorbed photosynthetically active radiation (FAPAR), vegetation phenology, surface albedo, fire disturbance, snow cover, land cover and land use change, soil moisture, land surface temperature (LST) and emissivity. Recent additions to the focus areas include vegetation indices and biomass. The development of best practice validation protocols is a core activity of CEOS LPV with the objective to standardize the evaluation of land surface products. LPV has identified four validation levels corresponding to increasing spatial and temporal representativeness of reference samples used to perform validation. Best practice validation protocols (1) provide the definition of variables, ancillary information and uncertainty metrics, (2) describe available data sources and methods to establish reference validation datasets with SI traceability, and (3) describe evaluation methods and reporting. An overview on validation best practice components will be presented based on the LAI and LST protocol efforts to date.

Uncertainty assessment of future land use in Brazil under increasing demand for bioenergy

NASA Astrophysics Data System (ADS)

van der Hilst, F.; Verstegen, J. A.; Karssenberg, D.; Faaij, A.

2013-12-01

Environmental impacts of a future increase in demand for bioenergy depend on the magnitude, location and pattern of the direct and indirect land use change of energy cropland expansion. Here we aim at 1) projecting the spatio-temporal pattern of sugar cane expansion and the effect on other land uses in Brazil towards 2030, and 2) assessing the uncertainty herein. For the spatio-temporal projection, three model components are used: 1) an initial land use map that shows the initial amount and location of sugar cane and all other relevant land use classes in the system, 2) a model to project the quantity of change of all land uses, and 3) a spatially explicit land use model that determines the location of change of all land uses. All three model components are sources of uncertainty, which is quantified by defining error models for all components and their inputs and propagating these errors through the chain of components. No recent accurate land use map is available for Brazil, so municipal census data and the global land cover map GlobCover are combined to create the initial land use map. The census data are disaggregated stochastically using GlobCover as a probability surface, to obtain a stochastic land use raster map for 2006. Since bioenergy is a global market, the quantity of change in sugar cane in Brazil depends on dynamics in both Brazil itself and other parts of the world. Therefore, a computable general equilibrium (CGE) model, MAGNET, is run to produce a time series of the relative change of all land uses given an increased future demand for bioenergy. A sensitivity analysis finds the upper and lower boundaries hereof, to define this component's error model. An initial selection of drivers of location for each land use class is extracted from literature. Using a Bayesian data assimilation technique and census data from 2007 to 2011 as observational data, the model is identified, meaning that the final selection and optimal relative importance of the drivers of location are determined. The data assimilation technique takes into account uncertainty in the observational data and yields a stochastic representation of the identified model. Using all stochastic inputs, this land use change model is run to find at which locations the future land use changes occur and to quantify the associated uncertainty. The results indicate that in the initial land use map especially the locations of pastures are uncertain. Since the dynamics in the livestock sector play a major role in the land use development of Brazil, the effect of this uncertainty on the model output is large. Results of the data assimilation indicate that the drivers of location of the land uses vary over time (variations up to 50% in the importance of the drivers) making it difficult to find a solid stationary system representation. Overall, we conclude that projection up to 2030 is only of use for quantifying impacts that act on a larger aggregation level, because at local level uncertainty is too large.

Informing Carbon Dynamics in the Community Land Model with Observations from Across Timescales

NASA Astrophysics Data System (ADS)

Fox, A. M.; Hoar, T. J.

2014-12-01

Correct simulation of carbon dynamics in Earth System Models is required to accurately predict both short and long-term land carbon-cycle climate and concentration feedbacks. As new model structures and parameterizations of increasing complexity are introduced there is an ever present need for data to inform these developments, either indirectly through benchmarking activities, or directly through model-data fusion techniques. Here we briefly describe a very rich source of data that will come from the National Ecological Observatory Network (NEON), a continental-scale facility that will collect freely available biogeochemical and biophysical data from 60 sites representative of a full range of ecosystems across the USA over 30 years. Relevant data at each site include a full suite of micrometeorology measurements, profiles of CO2 and H2O vapor isotopes, soil temperature, moisture and CO2 flux, fine root images, and plot-based NPP, leaf area and litterfall estimates. This is accompanied by Lidar and hyperspectral derived biomass, leaf area and canopy chemistry at < 1m resolution of 100s km2. Critically, these observations are well calibrated and highly standardized across sites allowing comparisons, whilst plot and site selection has been designed to optimize representativeness and spatial scaling opportunities. To illustrate the potential utility of these data in constraining models, we show the range of Community Land Model (CLM) output at NEON site locations, and in model-space look at a number of different functional responses that characterize the model in space and time and could be tested with data. These observations can be used most directly through a data assimilation (DA) system and we demonstrate how we have developed support for CLM within the Data Assimilation Research Testbed (DART) that uses ensemble techniques for state estimation. Using an observing system experiment, we investigate how infrequent observations of carbon stocks constrain model dynamics and how these observations types can be used with more frequently available flux and leaf area index observations. We demonstrate the use of the latter with real Ameriflux and MODIS data.

43 CFR 3101.5 - National Wildlife Refuge System lands.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 43 Public Lands: Interior 2 2012-10-01 2012-10-01 false National Wildlife Refuge System lands. 3101.5 Section 3101.5 Public Lands: Interior Regulations Relating to Public Lands (Continued) BUREAU OF... Leases § 3101.5 National Wildlife Refuge System lands. ...

43 CFR 3101.5 - National Wildlife Refuge System lands.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 43 Public Lands: Interior 2 2013-10-01 2013-10-01 false National Wildlife Refuge System lands. 3101.5 Section 3101.5 Public Lands: Interior Regulations Relating to Public Lands (Continued) BUREAU OF... Leases § 3101.5 National Wildlife Refuge System lands. ...

43 CFR 3101.5 - National Wildlife Refuge System lands.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 43 Public Lands: Interior 2 2011-10-01 2011-10-01 false National Wildlife Refuge System lands. 3101.5 Section 3101.5 Public Lands: Interior Regulations Relating to Public Lands (Continued) BUREAU OF... Leases § 3101.5 National Wildlife Refuge System lands. ...

43 CFR 3101.5 - National Wildlife Refuge System lands.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 43 Public Lands: Interior 2 2014-10-01 2014-10-01 false National Wildlife Refuge System lands. 3101.5 Section 3101.5 Public Lands: Interior Regulations Relating to Public Lands (Continued) BUREAU OF... Leases § 3101.5 National Wildlife Refuge System lands. ...

Land-atmosphere coupling and climate prediction over the U.S. Southern Great Plains

NASA Astrophysics Data System (ADS)

Williams, I. N.; Lu, Y.; Kueppers, L. M.; Riley, W. J.; Biraud, S.; Bagley, J. E.; Torn, M. S.

2016-12-01

Biases in land-atmosphere coupling in climate models can contribute to climate prediction biases, but land models are rarely evaluated in the context of this coupling. We tested land-atmosphere coupling and explored effects of land surface parameterizations on climate prediction in a single-column version of the NCAR Community Earth System Model (CESM1.2.2) and an offline Community Land Model (CLM4.5). The correlation between leaf area index (LAI) and surface evaporative fraction (ratio of latent to total turbulent heat flux) was substantially underpredicted compared to observations in the U.S. Southern Great Plains, while the correlation between soil moisture and evaporative fraction was overpredicted by CLM4.5. These correlations were improved by prescribing observed LAI, increasing soil resistance to evaporation, increasing minimum stomatal conductance, and increasing leaf reflectance. The modifications reduced the root mean squared error (RMSE) in daytime 2 m air temperature from 3.6 C to 2 C in summer (JJA), and reduced RMSE in total JJA precipitation from 133 to 84 mm. The modifications had the largest effect on prediction of summer drought in 2006, when a warm bias in daytime 2 m air temperature was reduced from +6 C to a smaller cold bias of -1.3 C, and a corresponding dry bias in total JJA precipitation was reduced from -111 mm to -23 mm. Thus, the role of vegetation in droughts and heat waves is likely underpredicted in CESM1.2.2, and improvements in land surface models can improve prediction of climate extremes.

Surface Landing Site Weather Analysis for Constellation Program

NASA Technical Reports Server (NTRS)

Altino, Karen M.; Burns, K. Lee

2008-01-01

Weather information is an important asset for NASA's Constellation Program in developing the next generation space transportation system to fly to the International Space Station, the Moon and, eventually, to Mars. Weather conditions can affect vehicle safety and performance during multiple mission phases ranging from pre-launch ground processing to landing and recovery operations, including all potential abort scenarios. Meteorological analysis is an important contributor, not only to the development and verification of system design requirements but also to mission planning and active ground operations. Of particular interest are the surface atmospheric conditions at both nominal and abort landing sites for the manned Orion capsule. Weather parameters such as wind, rain, and fog all play critical roles in the safe landing of the vehicle and subsequent crew and vehicle recovery. The Marshall Space Flight Center Natural Environments Branch has been tasked by the Constellation Program with defining the natural environments at potential landing zones. Climatological time series of operational surface weather observations are used to calculate probabilities of occurrence of various sets of hypothetical vehicle constraint thresholds, Data are available for numerous geographical locations such that statistical analysis can be performed for single sites as well as multiple-site network configurations. Results provide statistical descriptions of how often certain weather conditions are observed at the site(s) and the percentage that specified criteria thresholds are matched or exceeded. Outputs are tabulated by month and hour of day to show both seasonal and diurnal variation. This paper will describe the methodology used for data collection and quality control, detail the types of analyses performed, and provide a sample of the results that can be obtained,

Planetary entry, descent, and landing technologies

NASA Astrophysics Data System (ADS)

Pichkhadze, K.; Vorontsov, V.; Polyakov, A.; Ivankov, A.; Taalas, P.; Pellinen, R.; Harri, A.-M.; Linkin, V.

2003-04-01

Martian meteorological lander (MML) is intended for landing on the Martian surface in order to monitor the atmosphere at landing point for one Martian year. MMLs shall become the basic elements of a global network of meteorological mini-landers, observing the dynamics of changes of the atmospheric parameters on the Red Planet. The MML main scientific tasks are as follows: (1) Study of vertical structure of the Martian atmosphere throughout the MML descent; (2) On-surface meteorological observations for one Martian year. One of the essential factors influencing the lander's design is its entry, descent, and landing (EDL) sequence. During Phase A of the MML development, five different options for the lander's design were carefully analyzed. All of these options ensure the accomplishment of the above-mentioned scientific tasks with high effectiveness. CONCEPT A (conventional approach): Two lander options (with a parachute system + airbag and an inflatable airbrake + airbag) were analyzed. They are similar in terms of fulfilling braking phases and completely analogous in landing by means of airbags. CONCEPT B (innovative approach): Three lander options were analyzed. The distinguishing feature is the presence of inflatable braking units (IBU) in their configurations. SELECTED OPTION (innovative approach): Incorporating a unique design approach and modern technologies, the selected option of the lander represents a combination of the options analyzed in the framework of Concept B study. Currently, the selected lander option undergoes systems testing (Phase D1). Several MMLs can be delivered to Mars in frameworks of various missions as primary or piggybacking payload: (1) USA-led "Mars Scout" (2007); (2) France-led "NetLander" (2007/2009); (3) Russia-led "Mars-Deimos-Phobos sample return" (2007); (4) Independent mission (currently under preliminary study); etc.

Management-focused approach to investigating coastal water-quality drivers and impacts in the Baltic Sea

NASA Astrophysics Data System (ADS)

Vigouroux, G.; Destouni, G.; Chen, Y.; Bring, A.; Jönsson, A.; Cvetkovic, V.

2017-12-01

Coastal areas link human-driven conditions on land with open sea conditions, and include crucial and vulnerable ecosystems that provide a variety of ecosystem services. Eutrophication is a common problem that is not least observed in the Baltic Sea, where coastal water quality is influenced both by land-based nutrient loading and by partly eutrophic open sea conditions. Robust and adaptive management of coastal systems is essential and necessitates integration of large scale catchment-coastal-marine systems as well as consideration of anthropogenic drivers and impacts, and climate change. To address this coastal challenge, relevant methodological approaches are required for characterization of coupled land, local coastal, and open sea conditions under an adaptive management framework for water quality. In this paper we present a new general and scalable dynamic characterization approach, developed for and applied to the Baltic Sea and its coastal areas. A simple carbon-based water quality model is implemented, dividing the Baltic Sea into main management basins that are linked to corresponding hydrological catchments on land, as well as to each other though aggregated three-dimensional marine hydrodynamics. Relevant hydrodynamic variables and associated water quality results have been validated on the Baltic Sea scale and show good accordance with available observation data and other modelling approaches. Based on its scalability, this methodology is further used on coastal zone scale to investigate the effects of hydrodynamic, hydro-climatic and nutrient load drivers on water quality and management implications for coastal areas in the Baltic Sea.

Design and implementation of land reservation system

NASA Astrophysics Data System (ADS)

Gao, Yurong; Gao, Qingqiang

2009-10-01

Land reservation is defined as a land management policy for insuring the government to control primary land market. It requires the government to obtain the land first, according to plan, by purchase, confiscation and exchanging, and then exploit and consolidate the land for reservation. Underlying this policy, it is possible for the government to satisfy and manipulate the needs of land for urban development. The author designs and develops "Land Reservation System for Eastern Lake Development District" (LRSELDD), which deals with the realistic land requirement problems in Wuhan Eastern Lake Development Districts. The LRSELDD utilizes modern technologies and solutions of computer science and GIS to process multiple source data related with land. Based on experiments on the system, this paper will first analyze workflow land reservation system and design the system structure based on its principles, then illustrate the approach of organization and management of spatial data, describe the system functions according to the characteristics of land reservation and consolidation finally. The system is running to serve for current work in Eastern Lake Development Districts. It is able to scientifically manage both current and planning land information, as well as the information about land supplying. We use the LRSELDD in our routine work, and with such information, decisions on land confiscation and allocation will be made wisely and scientifically.

Utility of a Two-source Energy Balance Approach for Daily Mapping of Landsat-scale Fluxes Over Irrigated Agriculture in a Desert Environment

NASA Astrophysics Data System (ADS)

Houborg, R.; McCabe, M. F.; Rosas Aguilar, J.; Anderson, M. C.; Hain, C.

2014-12-01

The Middle East and North Africa (MENA) region is an area characterized by limited fresh water resources, an often inefficient use of these, and relatively poor in-situ monitoring as a result of sparse meteorological observations. Enhanced satellite-based monitoring systems are needed for aiding local water resource and agricultural management activities in these data poor arid environments. A multi-sensor and multi-scale land-surface flux monitoring capacity is being implemented over parts of MENA in order to provide meaningful decision support at relevant spatiotemporal scales. The integrated modeling system uses the Atmosphere-Land Exchange Inverse (ALEXI) model and associated flux disaggregation scheme (DisALEXI), and the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) in conjunction with model reanalysis data and remotely sensed data from polar orbiting (Landsat and MODIS; MODerate resolution Imaging Spectroradiometer) and geostationary (MSG; Meteosat Second Generation) satellite platforms to facilitate daily estimates of land surface fluxes down to sub-field scale (i.e. 30 m). Within this modeling system, thermal infrared satellite data provide information about the sub-surface moisture status and plant stress, obviating the need for precipitation input and error-prone soil surface characterizations. In this study, the integrated ALEXI-DisALEXI-STARFM framework is applied over an irrigated agricultural region in Saudi Arabia, and the daily estimates of Landsat scale water, energy and carbon fluxes are evaluated against available flux tower observations and other independent in-situ and satellite-based records. The study addresses the challenges associated with time-continuous sub-field scale mapping of land-surface fluxes in a harsh desert environment, and looks into the optimization of model descriptions and parameterizations and meteorological forcing and vegetation inputs for application over these regions.

Systems Analysis of Amphibious Landing Craft: Comparisons of Revised Designs of Advanced Landing Craft.

DTIC Science & Technology

AALC(AMPHIBIOUS ASSAULT LANDING CRAFT), AMPHIBIOUS ASSAULT LANDING CRAFT, DEBARKING, GAMUT MODEL, GENERAL PURPOSE SIMULATION SYSTEM, GPSS(GENERAL PURPOSE SIMULATION SYSTEM), IBM 360 COMPUTERS, LANDING CRAFT MIXES.

An international land-biosphere model benchmarking activity for the IPCC Fifth Assessment Report (AR5)

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

Hoffman, Forrest M; Randerson, James T; Thornton, Peter E

2009-12-01

The need to capture important climate feedbacks in general circulation models (GCMs) has resulted in efforts to include atmospheric chemistry and land and ocean biogeochemistry into the next generation of production climate models, called Earth System Models (ESMs). While many terrestrial and ocean carbon models have been coupled to GCMs, recent work has shown that such models can yield a wide range of results (Friedlingstein et al., 2006). This work suggests that a more rigorous set of global offline and partially coupled experiments, along with detailed analyses of processes and comparisons with measurements, are needed. The Carbon-Land Model Intercomparison Projectmore » (C-LAMP) was designed to meet this need by providing a simulation protocol and model performance metrics based upon comparisons against best-available satellite- and ground-based measurements (Hoffman et al., 2007). Recently, a similar effort in Europe, called the International Land Model Benchmark (ILAMB) Project, was begun to assess the performance of European land surface models. These two projects will now serve as prototypes for a proposed international land-biosphere model benchmarking activity for those models participating in the IPCC Fifth Assessment Report (AR5). Initially used for model validation for terrestrial biogeochemistry models in the NCAR Community Land Model (CLM), C-LAMP incorporates a simulation protocol for both offline and partially coupled simulations using a prescribed historical trajectory of atmospheric CO2 concentrations. Models are confronted with data through comparisons against AmeriFlux site measurements, MODIS satellite observations, NOAA Globalview flask records, TRANSCOM inversions, and Free Air CO2 Enrichment (FACE) site measurements. Both sets of experiments have been performed using two different terrestrial biogeochemistry modules coupled to the CLM version 3 in the Community Climate System Model version 3 (CCSM3): the CASA model of Fung, et al., and the carbon-nitrogen (CN) model of Thornton. Comparisons of the CLM3 offline results against observational datasets have been performed and are described in Randerson et al. (2009). CLM version 4 has been evaluated using C-LAMP, showing improvement in many of the metrics. Efforts are now underway to initiate a Nitrogen-Land Model Intercomparison Project (N-LAMP) to better constrain the effects of the nitrogen cycle in biosphere models. Presented will be new results from C-LAMP for CLM4, initial N-LAMP developments, and the proposed land-biosphere model benchmarking activity.« less

Operational and LIS-Based North American Land Data Assimilation Systems at National Centers for Environmental Prediction: Capability in Simulating Water and Energy Budget over the Western United States

NASA Astrophysics Data System (ADS)

Mitchell, K.; Xia, Y.; Ek, M. B.; Mocko, D. M.; Kumar, S.; Peters-Lidard, C. D.

2016-12-01

NLDAS is a multi-institutional collaborative project sponsored by NOAA's Climate Program Office and NASA's Terrestrial Hydrological Program. NLDAS has a long successful history of producing soil moisture, snow cover, total runoff and streamflow products via application of surface meteorology and precipitation datasets to drive four land-surface models (i.e., Noah, Mosaic, SAC, VIC). The purpose of the NLDAS system is to support numerous research and operational applications in the land modeling and water resources management communities. Since the operational NLDAS version was successfully implemented at NCEP in August 2014, NLDAS products are being used by over 5000 users annually worldwide, including academia, governmental agencies, and private enterprises. Over 71 million files and 144 Tb of data were downloaded in 2015. As we endeavor to increase the quality and breadth of NLDAS products, a joint effort between NASA and NCEP is underway to enable the assimilation of hydrology-relevant remote sensing datasets within NLDAS through the NASA Land Information System (LIS). The use of LIS will also enable easier transition of newly upgraded land surface models into NCEP NLDAS operations. Cold season processes significantly affect water and energy cycles, and their partitioning. As such, in the evaluation of NLDAS systems it is important to assess water and energy exchanges and/or partitioning processes over high-elevations. The Rocky Mountain region of the western U. S. is chosen as such a region to analyze and compare snow water equivalent (SWE), snow cover, snow melt, snow sublimation, total runoff, and sensible heat and latent heat flux. Reference data sets (observation-based and reanalysis) of monthly SWE, streamflow, evapotranspiration, GRACE-based total water storage change, and energy fluxes are used to evaluate model-simulated results. The results show several key factors that affect model simulations: (1) forcing errors such as precipitation partitioning into snowfall and rainfall, (2) snow albedo, (3) refreezing of melted snow, (4) boundary layer stability, and (5) freezing and thawing of soil. Though the anomaly correlations indicate good agreement with the observations or reanalysis products, large quantitative differences are evident in certain cases.

Denitrification in Shallow Groundwater Below Different Arable Land Systems in a High Nitrogen-Loading Region

NASA Astrophysics Data System (ADS)

Zhou, Wei; Ma, Yuchun; Well, Reinhard; Wang, Hua; Yan, Xiaoyuan

2018-03-01

To evaluate the risk of nitrate (NO3--N) in groundwater, it is necessary to know the denitrification capacity. In this study, observations were carried out for 2 years to investigate the groundwater denitrification capacity below three arable land systems in eastern China. Denitrification capacity was assessed by measuring the concentration and distribution patterns of nitrous oxide (N2O) and dinitrogen (N2) in groundwater. The results revealed that groundwater denitrification activity was high and consumed 76%, 83%, and 65% of the NO3--N in the vineyard (VY), vegetable field (VF), and paddy field (PF), respectively. The high denitrification activity might be attributed to the strong reducing conditions, with high dissolved oxygen concentrations in groundwater, which promotes denitrification. During the sampling period, we observed high dinitrogen (excess N2) accumulation in groundwater, which exceeded the total reactive nitrogen (N) in the deep layer. The large amount of excess N2 observed in VY and VF indicated that considerable N was stored as gaseous N2 in groundwater and should not be ignored when balancing N budgets in aquifers where denitrification is high.

The International Geoscience and Remote Sensing Symposium (IGARSS) 84. Remote Sensing: from Research Towards Operational Use, Volume 2

NASA Technical Reports Server (NTRS)

Guyenne, T. D. (Editor); Hunt, James J. (Editor)

1984-01-01

Synthetic aperature radar; systems components; data collection; data evaluation; optical sensor data; air pollution; water pollution; land and sea observation; active sensors (ir and w); and ers-1 are discussed.

A geometric performance assessment of the EO-1 advanced land imager

USGS Publications Warehouse

Storey, James C.; Choate, M.J.; Meyer, D.J.

2004-01-01

The Earth Observing 1 (EO-1) Advanced Land Imager (ALI) demonstrates technology applicable to a successor system to the Landsat Thematic Mapper series. A study of the geometric performance characteristics of the ALI was conducted under the auspices of the EO-1 Science Validation Team. This study evaluated ALI performance with respect to absolute pointing knowledge, focal plane sensor chip assembly alignment, and band-to-band registration for purposes of comparing this new technology to the heritage Landsat systems. On-orbit geometric calibration procedures were developed that allowed the generation of ALI geometrically corrected products that compare favorably with their Landsat 7 counterparts with respect to absolute geodetic accuracy, internal image geometry, and band registration.

Applications of ISES for vegetation and land use

NASA Technical Reports Server (NTRS)

Wilson, R. Gale

1990-01-01

Remote sensing relative to applications involving vegetation cover and land use is reviewed to consider the potential benefits to the Earth Observing System (Eos) of a proposed Information Sciences Experiment System (ISES). The ISES concept has been proposed as an onboard experiment and computational resource to support advanced experiments and demonstrations in the information and earth sciences. Embedded in the concept is potential for relieving the data glut problem, enhancing capabilities to meet real-time needs of data users and in-situ researchers, and introducing emerging technology to Eos as the technology matures. These potential benefits are examined in the context of state-of-the-art research activities in image/data processing and management.

Coherent Lidar Activities at NASA Langley Research Center

NASA Technical Reports Server (NTRS)

Kavaya, Michael J.; Amzajerdian, Farzin; Koch, Grady J.; Singh, Upendra N.; Yu, Jirong

2007-01-01

NASA Langley Research Center has been developing and using coherent lidar systems for many years. The current projects at LaRC are the Global Wind Observing Sounder (GWOS) mission preparation, the Laser Risk Reduction Program (LRRP), the Instrument Incubator Program (IIP) compact, rugged Doppler wind lidar project, the Autonomous precision Landing and Hazard detection and Avoidance Technology (ALHAT) project for lunar landing, and the Skywalker project to find and use thermals to extend UAV flight time. These five projects encompass coherent lidar technology development; characterization, validation, and calibration facilities; compact, rugged packaging; computer simulation; trade studies; data acquisition, processing, and display development; system demonstration; and space mission design. This paper will further discuss these activities at LaRC.

76 FR 37826 - Public Land Order No. 7773; Emergency Withdrawal of Public and National Forest System Lands...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-06-28

...] Public Land Order No. 7773; Emergency Withdrawal of Public and National Forest System Lands, Coconino and... Forest System lands from location and entry under the 1872 Mining Law for a period of 6 months under the... described above aggregate approximately 1,010,776 acres public and National Forest System lands in Coconino...

Land Cover Change Community-based Processing and Analysis System (LC-ComPS): Lessons Learned from Technology Infusion

NASA Astrophysics Data System (ADS)

Masek, J.; Rao, A.; Gao, F.; Davis, P.; Jackson, G.; Huang, C.; Weinstein, B.

2008-12-01

The Land Cover Change Community-based Processing and Analysis System (LC-ComPS) combines grid technology, existing science modules, and dynamic workflows to enable users to complete advanced land data processing on data available from local and distributed archives. Changes in land cover represent a direct link between human activities and the global environment, and in turn affect Earth's climate. Thus characterizing land cover change has become a major goal for Earth observation science. Many science algorithms exist to generate new products (e.g., surface reflectance, change detection) used to study land cover change. The overall objective of the LC-ComPS is to release a set of tools and services to the land science community that can be implemented as a flexible LC-ComPS to produce surface reflectance and land-cover change information with ground resolution on the order of Landsat-class instruments. This package includes software modules for pre-processing Landsat-type satellite imagery (calibration, atmospheric correction, orthorectification, precision registration, BRDF correction) for performing land-cover change analysis and includes pre-built workflow chains to automatically generate surface reflectance and land-cover change products based on user input. In order to meet the project objectives, the team created the infrastructure (i.e., client-server system with graphical and machine interfaces) to expand the use of these existing science algorithm capabilities in a community with distributed, large data archives and processing centers. Because of the distributed nature of the user community, grid technology was chosen to unite the dispersed community resources. At that time, grid computing was not used consistently and operationally within the Earth science research community. Therefore, there was a learning curve to configure and implement the underlying public key infrastructure (PKI) interfaces, required for the user authentication, secure file transfer and remote job execution on the grid network of machines. In addition, science support was needed to vet that the grid technology did not have any adverse affects of the science module outputs. Other open source, unproven technologies, such as a workflow package to manage jobs submitted by the user, were infused into the overall system with successful results. This presentation will discuss the basic capabilities of LC-ComPS, explain how the technology was infused, and provide lessons learned for using and integrating the various technologies while developing and operating the system, and finally outline plans moving forward (maintenance and operations decisions) based on the experience to date.

A Bayesian ensemble data assimilation to constrain model parameters and land-use carbon emissions

NASA Astrophysics Data System (ADS)

Lienert, Sebastian; Joos, Fortunat

2018-05-01

A dynamic global vegetation model (DGVM) is applied in a probabilistic framework and benchmarking system to constrain uncertain model parameters by observations and to quantify carbon emissions from land-use and land-cover change (LULCC). Processes featured in DGVMs include parameters which are prone to substantial uncertainty. To cope with these uncertainties Latin hypercube sampling (LHS) is used to create a 1000-member perturbed parameter ensemble, which is then evaluated with a diverse set of global and spatiotemporally resolved observational constraints. We discuss the performance of the constrained ensemble and use it to formulate a new best-guess version of the model (LPX-Bern v1.4). The observationally constrained ensemble is used to investigate historical emissions due to LULCC (ELUC) and their sensitivity to model parametrization. We find a global ELUC estimate of 158 (108, 211) PgC (median and 90 % confidence interval) between 1800 and 2016. We compare ELUC to other estimates both globally and regionally. Spatial patterns are investigated and estimates of ELUC of the 10 countries with the largest contribution to the flux over the historical period are reported. We consider model versions with and without additional land-use processes (shifting cultivation and wood harvest) and find that the difference in global ELUC is on the same order of magnitude as parameter-induced uncertainty and in some cases could potentially even be offset with appropriate parameter choice.

An improved hindcast approach for evaluation and diagnosis of physical processes in global climate models

DOE PAGES

Ma, H. -Y.; Chuang, C. C.; Klein, S. A.; ...

2015-11-06

Here, we present an improved procedure of generating initial conditions (ICs) for climate model hindcast experiments with specified sea surface temperature and sea ice. The motivation is to minimize errors in the ICs and lead to a better evaluation of atmospheric parameterizations' performance in the hindcast mode. We apply state variables (horizontal velocities, temperature and specific humidity) from the operational analysis/reanalysis for the atmospheric initial states. Without a data assimilation system, we apply a two-step process to obtain other necessary variables to initialize both the atmospheric (e.g., aerosols and clouds) and land models (e.g., soil moisture). First, we nudge onlymore » the model horizontal velocities towards operational analysis/reanalysis values, given a 6-hour relaxation time scale, to obtain all necessary variables. Compared to the original strategy in which horizontal velocities, temperature and specific humidity are nudged, the revised approach produces a better representation of initial aerosols and cloud fields which are more consistent and closer to observations and model's preferred climatology. Second, we obtain land ICs from an offline land model simulation forced with observed precipitation, winds, and surface fluxes. This approach produces more realistic soil moisture in the land ICs. With this refined procedure, the simulated precipitation, clouds, radiation, and surface air temperature over land are improved in the Day 2 mean hindcasts. Following this procedure, we propose a “Core” integration suite which provides an easily repeatable test allowing model developers to rapidly assess the impacts of various parameterization changes on the fidelity of modelled cloud-associated processes relative to observations.« less

An improved hindcast approach for evaluation and diagnosis of physical processes in global climate models

NASA Astrophysics Data System (ADS)

Ma, H.-Y.; Chuang, C. C.; Klein, S. A.; Lo, M.-H.; Zhang, Y.; Xie, S.; Zheng, X.; Ma, P.-L.; Zhang, Y.; Phillips, T. J.

2015-12-01

We present an improved procedure of generating initial conditions (ICs) for climate model hindcast experiments with specified sea surface temperature and sea ice. The motivation is to minimize errors in the ICs and lead to a better evaluation of atmospheric parameterizations' performance in the hindcast mode. We apply state variables (horizontal velocities, temperature, and specific humidity) from the operational analysis/reanalysis for the atmospheric initial states. Without a data assimilation system, we apply a two-step process to obtain other necessary variables to initialize both the atmospheric (e.g., aerosols and clouds) and land models (e.g., soil moisture). First, we nudge only the model horizontal velocities toward operational analysis/reanalysis values, given a 6 h relaxation time scale, to obtain all necessary variables. Compared to the original strategy in which horizontal velocities, temperature, and specific humidity are nudged, the revised approach produces a better representation of initial aerosols and cloud fields which are more consistent and closer to observations and model's preferred climatology. Second, we obtain land ICs from an off-line land model simulation forced with observed precipitation, winds, and surface fluxes. This approach produces more realistic soil moisture in the land ICs. With this refined procedure, the simulated precipitation, clouds, radiation, and surface air temperature over land are improved in the Day 2 mean hindcasts. Following this procedure, we propose a "Core" integration suite which provides an easily repeatable test allowing model developers to rapidly assess the impacts of various parameterization changes on the fidelity of modeled cloud-associated processes relative to observations.

Impact of physical permafrost processes on hydrological change

NASA Astrophysics Data System (ADS)

Hagemann, Stefan; Blome, Tanja; Beer, Christian; Ekici, Altug

2015-04-01

Permafrost or perennially frozen ground is an important part of the terrestrial cryosphere; roughly one quarter of Earth's land surface is underlain by permafrost. As it is a thermal phenomenon, its characteristics are highly dependent on climatic factors. The impact of the currently observed warming, which is projected to persist during the coming decades due to anthropogenic CO2 input, certainly has effects for the vast permafrost areas of the high northern latitudes. The quantification of these effects, however, is scientifically still an open question. This is partly due to the complexity of the system, where several feedbacks are interacting between land and atmosphere, sometimes counterbalancing each other. Moreover, until recently, many global circulation models (GCMs) and Earth system models (ESMs) lacked the sufficient representation of permafrost physics in their land surface schemes. Within the European Union FP7 project PAGE21, the land surface scheme JSBACH of the Max-Planck-Institute for Meteorology ESM (MPI-ESM) has been equipped with the representation of relevant physical processes for permafrost studies. These processes include the effects of freezing and thawing of soil water for both energy and water cycles, thermal properties depending on soil water and ice contents, and soil moisture movement being influenced by the presence of soil ice. In the present study, it will be analysed how these permafrost relevant processes impact projected hydrological changes over northern hemisphere high latitude land areas. For this analysis, the atmosphere-land part of MPI-ESM, ECHAM6-JSBACH, is driven by prescribed SST and sea ice in an AMIP2-type setup with and without the newly implemented permafrost processes. Observed SST and sea ice for 1979-1999 are used to consider induced changes in the simulated hydrological cycle. In addition, simulated SST and sea ice are taken from a MPI-ESM simulation conducted for CMIP5 following the RCP8.5 scenario. The corresponding simulations with ECHAM6-JSBACH are used to assess differences in projected hydrological changes induced by the permafrost relevant processes.

Sinkhole flooding in Murfreesboro, Rutherford County, Tennessee, 2001-02

USGS Publications Warehouse

Bradley, Michael W.; Hileman, Gregg Edward

2006-01-01

The U.S. Geological Survey, in cooperation with the City of Murfreesboro, Tennessee, conducted an investigation from January 2001 through April 2002 to delineate sinkholes and sinkhole watersheds in the Murfreesboro area and to characterize the hydrologic response of sinkholes to major rainfall events. Terrain analysis was used to define sinkholes and delineate the sinkhole drainage areas. Flooding in 78 sinkholes in three focus areas was identified and tracked using aerial photography following three major storms in February 2001, January 2002, and March 2002. The three focus areas are located to the east, north, and northwest of Murfreesboro and are underlain primarily by the Ridley Limestone with some outcrops of the underlying Pierce Limestone. The observed sinkhole flooding is controlled by water inflow, water outflow, and the degree of the hydraulic connection (connectivity) to a ground-water conduit system. The observed sinkholes in the focus areas are grouped into three categories based on the sinkhole morphology and the connectivity to the ground-water system as indicated by their response to flooding. The three types of sinkholes described for these focus areas are pan sinkholes with low connectivity, deep sinkholes with high connectivity, and deep sinkholes with low connectivity to the ground-water conduit system. Shallow, broad pan sinkholes flood as water inflow from a storm inundates the depression at land surface. Water overflow from one pan sinkhole can flow downgradient and become inflow to a sinkhole at a lower altitude. Land-surface modifications that direct more water into a pan sinkhole could increase peak-flood altitudes and extend flood durations. Land-surface modifications that increase the outflow by overland drainage could decrease the flood durations. Road construction or alterations that reduce flow within or between pan sinkholes could result in increased flood durations. Flood levels and durations in the deeper sinkholes observed in the three focus areas are primarily affected by the connectivity with the ground-water conduit system. Deep sinkholes with a relatively high connectivity to the ground-water system fill quickly after a storm, and drain rapidly after the storm ends, and water levels decline as much as 3 to 5 feet per day in the first 2 to 3 days after a major storm. These sinkholes store the initial floodwater and then rapidly transmit water to the ground-water conduit system (high outflow). Land-surface changes that direct more water into the sinkhole may increase the flood peaks, but may not have a substantial effect on the flood durations. Deep sinkholes that have low connectivity to the ground-water conduit system may have a delayed peak water level and may drain slowly, only about 2 to 3 feet in 10 days. Outflow from these sinkholes is limited or restricted by low connectivity to the ground-water conduit system. Land-surface alterations that increase the inflow to the sinkholes can result in high flood levels or increased flood durations.

Uncertainties of wild-land fires emission in AQMEII phase 2 case study

NASA Astrophysics Data System (ADS)

Soares, J.; Sofiev, M.; Hakkarainen, J.

2015-08-01

The paper discusses the main uncertainties of wild-land fire emission estimates used in the AQMEII-II case study. The wild-land fire emission of particulate matter for the summer fire season of 2010 in Eurasia was generated by the Integrated System for wild-land Fires (IS4FIRES). The emission calculation procedure included two steps: bottom-up emission compilation from radiative energy of individual fires observed by MODIS instrument on-board of Terra and Aqua satellites; and top-down calibration of emission factors based on the comparison between observations and modelled results. The approach inherits various uncertainties originating from imperfect information on fires, inaccuracies of the inverse problem solution, and simplifications in the fire description. These are analysed in regard to the Eurasian fires in 2010. It is concluded that the total emission is likely to be over-estimated by up to 50% with individual-fire emission accuracy likely to vary in a wide range. The first results of the new IS4FIRESv2 products and fire-resolving modelling are discussed in application to the 2010 events. It is shown that the new emission estimates have similar patterns but are lower than the IS4FIRESv1 values.

Unmanned air vehicle: autonomous takeoff and landing

NASA Astrophysics Data System (ADS)

Lim, K. L.; Gitano-Briggs, Horizon Walker

2010-03-01

UAVs are increasing in popularity and sophistication due to the demonstrated performance which cannot be attained by manned aircraft1. These developments have been made possible by development of sensors, instrumentation, telemetry and controls during the last few decades. UAVs are now common in areas such as aerial observation and as communication relays3. Most UAVs, however, are still flown by a human pilot via remote control from a ground station. Even the existing autonomous UAVs often require a human pilot to handle the most difficult tasks of take off and landing2 (TOL). This is mainly because the navigation of the airplane requires observation, constant situational assessment and hours of experience from the pilot himself4. Therefore, an autonomous takeoff and landing system (TLS) for UAVs using a few practical design rules with various sensors, instrumentation, etc has been developed. This paper details the design and modeling of the UAV TLS. The model indicates that the UAV's TLS shows promising stability.

Unmanned air vehicle: autonomous takeoff and landing

NASA Astrophysics Data System (ADS)

Lim, K. L.; Gitano-Briggs, Horizon Walker

2009-12-01

UAVs are increasing in popularity and sophistication due to the demonstrated performance which cannot be attained by manned aircraft1. These developments have been made possible by development of sensors, instrumentation, telemetry and controls during the last few decades. UAVs are now common in areas such as aerial observation and as communication relays3. Most UAVs, however, are still flown by a human pilot via remote control from a ground station. Even the existing autonomous UAVs often require a human pilot to handle the most difficult tasks of take off and landing2 (TOL). This is mainly because the navigation of the airplane requires observation, constant situational assessment and hours of experience from the pilot himself4. Therefore, an autonomous takeoff and landing system (TLS) for UAVs using a few practical design rules with various sensors, instrumentation, etc has been developed. This paper details the design and modeling of the UAV TLS. The model indicates that the UAV's TLS shows promising stability.

Top–down assessment of the Asian carbon budget since the mid 1990s

PubMed Central

Thompson, R. L.; Patra, P. K.; Chevallier, F.; Maksyutov, S.; Law, R. M.; Ziehn, T.; van der Laan-Luijkx, I. T.; Peters, W.; Ganshin, A.; Zhuravlev, R.; Maki, T.; Nakamura, T.; Shirai, T.; Ishizawa, M.; Saeki, T.; Machida, T.; Poulter, B.; Canadell, J. G.; Ciais, P.

2016-01-01

Increasing atmospheric carbon dioxide (CO2) is the principal driver of anthropogenic climate change. Asia is an important region for the global carbon budget, with 4 of the world's 10 largest national emitters of CO2. Using an ensemble of seven atmospheric inverse systems, we estimated land biosphere fluxes (natural, land-use change and fires) based on atmospheric observations of CO2 concentration. The Asian land biosphere was a net sink of −0.46 (−0.70–0.24) PgC per year (median and range) for 1996–2012 and was mostly located in East Asia, while in South and Southeast Asia the land biosphere was close to carbon neutral. In East Asia, the annual CO2 sink increased between 1996–2001 and 2008–2012 by 0.56 (0.30–0.81) PgC, accounting for ∼35% of the increase in the global land biosphere sink. Uncertainty in the fossil fuel emissions contributes significantly (32%) to the uncertainty in land biosphere sink change. PMID:26911442

The impact of anthropogenic land use and land cover change on regional climate extremes.

PubMed

Findell, Kirsten L; Berg, Alexis; Gentine, Pierre; Krasting, John P; Lintner, Benjamin R; Malyshev, Sergey; Santanello, Joseph A; Shevliakova, Elena

2017-10-20

Land surface processes modulate the severity of heat waves, droughts, and other extreme events. However, models show contrasting effects of land surface changes on extreme temperatures. Here, we use an earth system model from the Geophysical Fluid Dynamics Laboratory to investigate regional impacts of land use and land cover change on combined extremes of temperature and humidity, namely aridity and moist enthalpy, quantities central to human physiological experience of near-surface climate. The model's near-surface temperature response to deforestation is consistent with recent observations, and conversion of mid-latitude natural forests to cropland and pastures is accompanied by an increase in the occurrence of hot-dry summers from once-in-a-decade to every 2-3 years. In the tropics, long time-scale oceanic variability precludes determination of how much of a small, but significant, increase in moist enthalpy throughout the year stems from the model's novel representation of historical patterns of wood harvesting, shifting cultivation, and regrowth of secondary vegetation and how much is forced by internal variability within the tropical oceans.

Protection of surface assets on Mars from wind blown jettisoned spacecraft components

NASA Astrophysics Data System (ADS)

Paton, Mark

2017-07-01

Jettisoned Entry, Descent and Landing System (EDLS) hardware from landing spacecraft have been observed by orbiting spacecraft, strewn over the Martian surface. Future Mars missions that land spacecraft close to prelanded assets will have to use a landing architecture that somehow minimises the possibility of impacts from these jettisoned EDLS components. Computer modelling is used here to investigate the influence of wind speed and direction on the distribution of EDLS components on the surface. Typical wind speeds encountered in the Martian Planetary Boundary Layer (PBL) were found to be of sufficient strength to blow items having a low ballistic coefficient, i.e. Hypersonic Inflatable Aerodynamic Decelerators (HIADs) or parachutes, onto prelanded assets even when the lander itself touches down several kilometres away. Employing meteorological measurements and careful characterisation of the Martian PBL, e.g. appropriate wind speed probability density functions, may then benefit future spacecraft landings, increase safety and possibly help reduce the delta v budget for Mars landers that rely on aerodynamic decelerators.

Evaluation of historical land cover, land use, and land-use change emissions in the GCAM integrated assessment model

NASA Astrophysics Data System (ADS)

Calvin, K. V.; Wise, M.; Kyle, P.; Janetos, A. C.; Zhou, Y.

2012-12-01

Integrated Assessment Models (IAMs) are often used as science-based decision-support tools for evaluating the consequences of climate and energy policies, and their use in this framework is likely to increase in the future. However, quantitative evaluation of these models has been somewhat limited for a variety of reasons, including data availability, data quality, and the inherent challenges in projections of societal values and decision-making. In this analysis, we identify and confront methodological challenges involved in evaluating the agriculture and land use component of the Global Change Assessment Model (GCAM). GCAM is a global integrated assessment model, linking submodules of the regionally disaggregated global economy, energy system, agriculture and land-use, terrestrial carbon cycle, oceans and climate. GCAM simulates supply, demand, and prices for energy and agricultural goods from 2005 to 2100 in 5-year increments. In each time period, the model computes the allocation of land across a variety of land cover types in 151 different regions, assuming that farmers maximize profits and that food demand is relatively inelastic. GCAM then calculates both emissions from land-use practices, and long-term changes in carbon stocks in different land uses, thus providing simulation information that can be compared to observed historical data. In this work, we compare GCAM results, both in recent historic and future time periods, to historical data sets. We focus on land use, land cover, land-use change emissions, and albedo.

Spatial modeling of agricultural land use change at global scale

NASA Astrophysics Data System (ADS)

Meiyappan, P.; Dalton, M.; O'Neill, B. C.; Jain, A. K.

2014-11-01

Long-term modeling of agricultural land use is central in global scale assessments of climate change, food security, biodiversity, and climate adaptation and mitigation policies. We present a global-scale dynamic land use allocation model and show that it can reproduce the broad spatial features of the past 100 years of evolution of cropland and pastureland patterns. The modeling approach integrates economic theory, observed land use history, and data on both socioeconomic and biophysical determinants of land use change, and estimates relationships using long-term historical data, thereby making it suitable for long-term projections. The underlying economic motivation is maximization of expected profits by hypothesized landowners within each grid cell. The model predicts fractional land use for cropland and pastureland within each grid cell based on socioeconomic and biophysical driving factors that change with time. The model explicitly incorporates the following key features: (1) land use competition, (2) spatial heterogeneity in the nature of driving factors across geographic regions, (3) spatial heterogeneity in the relative importance of driving factors and previous land use patterns in determining land use allocation, and (4) spatial and temporal autocorrelation in land use patterns. We show that land use allocation approaches based solely on previous land use history (but disregarding the impact of driving factors), or those accounting for both land use history and driving factors by mechanistically fitting models for the spatial processes of land use change do not reproduce well long-term historical land use patterns. With an example application to the terrestrial carbon cycle, we show that such inaccuracies in land use allocation can translate into significant implications for global environmental assessments. The modeling approach and its evaluation provide an example that can be useful to the land use, Integrated Assessment, and the Earth system modeling communities.

Bottlenecks in Geospatial Data-Driven Decision-Making for Natural Disaster Management: A Case Study of Forest Fire Prevention and Control in Guatemala's Maya Biosphere Reserve

NASA Astrophysics Data System (ADS)

Berenter, J. S.; Mueller, J. M.; Morrison, I.

2016-12-01

Annual forest fires are a source of great economic and environmental cost in the Maya Biosphere Reserve (MBR), a region of high ecological and historical value in Guatemala's department of Petén. Scarce institutional resources, limited local response capacity, and difficult terrain place a premium on the use of Earth observation data for forest fire management in the MBR, but also present significant institutional barriers to optimizing the value of this data. Drawing upon key informant interviews and a contingent valuation survey of national and local actors conducted during a three-year performance evaluation of the USAID/NASA Regional Visualization and Monitoring System (SERVIR), this paper traces the flow of SERVIR data from acquisition to decision in order to assess the institutional and contextual factors affecting the value of Earth observation data for forest fire management in the MBR. Findings indicate that the use of satellite data for forest fire management in the MBR is widespread and multi-dimensional: historical assessments of land use and land cover, fire scarring, and climate data help central-level fire management agencies identify and regulate fire-sensitive areas; regular monitoring and dissemination of climate data enables coordination between agricultural burning activities and fire early warning systems; and daily satellite detection of thermal anomalies in land surface temperature permits first responders to monitor and react to "hotspot" activity. Findings also suggest, however, that while the decentralized operations of Petén's fire management systems foster the use of Earth observation data, systemic bottlenecks, including budgetary constraints, inadequate data infrastructure and interpretation capacity, and obstacles to regulatory enforcement, impede the flow of information and use of technology and thus impact the value of that data, particularly in remote and under-resourced areas of the MBR. A geographic expansion and fortification of support systems for use of Earth observation data is thus required to maximize the value of data-driven forest fire management in the MBR. Findings further validate a need for continued cooperation between scientific and governance institutions to disseminate and integrate geospatial data into environmental decision-making.

Wageningen UR Unmanned Aerial Remote Sensing Facility - Overview of activities

NASA Astrophysics Data System (ADS)

Bartholomeus, Harm; Keesstra, Saskia; Kooistra, Lammert; Suomalainen, Juha; Mucher, Sander; Kramer, Henk; Franke, Jappe

2016-04-01

To support environmental management there is an increasing need for timely, accurate and detailed information on our land. Unmanned Aerial Systems (UAS) are increasingly used to monitor agricultural crop development, habitat quality or urban heat efficiency. An important reason is that UAS technology is maturing quickly while the flexible capabilities of UAS fill a gap between satellite based and ground based geo-sensing systems. In 2012, different groups within Wageningen University and Research Centre have established an Unmanned Airborne Remote Sensing Facility. The objective of this facility is threefold: a) To develop innovation in the field of remote sensing science by providing a platform for dedicated and high-quality experiments; b) To support high quality UAS services by providing calibration facilities and disseminating processing procedures to the UAS user community; and c) To promote and test the use of UAS in a broad range of application fields like habitat monitoring, precision agriculture and land degradation assessment. The facility is hosted by the Laboratory of Geo-Information Science and Remote Sensing (GRS) and the Department of Soil Physics and Land Management (SLM) of Wageningen University together with the team Earth Informatics (EI) of Alterra. The added value of the Unmanned Aerial Remote Sensing Facility is that compared to for example satellite based remote sensing more dedicated science experiments can be prepared. This includes for example higher frequent observations in time (e.g., diurnal observations), observations of an object under different observation angles for characterization of BRDF and flexibility in use of camera's and sensors types. In this way, laboratory type of set ups can be tested in a field situation and effects of up-scaling can be tested. In the last years we developed and implemented different camera systems (e.g. a hyperspectral pushbroom system, and multispectral frame cameras) which we operated in projects all around the world, while new camera systems are being planned such as LiDAR and a full frame hyperspectral camera. In the presentation we will give an overview of our activities, ranging from erosion studies, decision support for precision agriculture, determining leaf biochemistry and canopy structure in tropical forests to the mapping of coastal zones.

Land-surface parameter optimisation using data assimilation techniques: the adJULES system V1.0

DOE PAGES

Raoult, Nina M.; Jupp, Tim E.; Cox, Peter M.; ...

2016-08-25

Land-surface models (LSMs) are crucial components of the Earth system models (ESMs) that are used to make coupled climate–carbon cycle projections for the 21st century. The Joint UK Land Environment Simulator (JULES) is the land-surface model used in the climate and weather forecast models of the UK Met Office. JULES is also extensively used offline as a land-surface impacts tool, forced with climatologies into the future. In this study, JULES is automatically differentiated with respect to JULES parameters using commercial software from FastOpt, resulting in an analytical gradient, or adjoint, of the model. Using this adjoint, the adJULES parameter estimationmore » system has been developed to search for locally optimum parameters by calibrating against observations. This paper describes adJULES in a data assimilation framework and demonstrates its ability to improve the model–data fit using eddy-covariance measurements of gross primary production (GPP) and latent heat (LE) fluxes. adJULES also has the ability to calibrate over multiple sites simultaneously. This feature is used to define new optimised parameter values for the five plant functional types (PFTs) in JULES. The optimised PFT-specific parameters improve the performance of JULES at over 85 % of the sites used in the study, at both the calibration and evaluation stages. Furthermore, the new improved parameters for JULES are presented along with the associated uncertainties for each parameter.« less

Research Advances on Radiation Transfer Modeling and Inversion for Multi-scale Land Surface Remote Sensing

NASA Astrophysics Data System (ADS)

Liu, Q.; Li, J.; Du, Y.; Wen, J.; Zhong, B.; Wang, K.

2011-12-01

As the remote sensing data accumulating, it is a challenge and significant issue how to generate high accurate and consistent land surface parameter product from the multi source remote observation and the radiation transfer modeling and inversion methodology are the theoretical bases. In this paper, recent research advances and unresolved issues are presented. At first, after a general overview, recent research advances on multi-scale remote sensing radiation transfer modeling are presented, including leaf spectrum model, vegetation canopy BRDF models, directional thermal infrared emission models, rugged mountains area radiation models, and kernel driven models etc. Then, new methodologies on land surface parameters inversion based on multi-source remote sensing data are proposed, taking the land surface Albedo, leaf area index, temperature/emissivity, and surface net radiation as examples. A new synthetic land surface parameter quantitative remote sensing product generation system is suggested and the software system prototype will be demonstrated. At last, multi-scale field experiment campaigns, such as the field campaigns in Gansu and Beijing, China are introduced briefly. The ground based, tower based, and airborne multi-angular measurement system have been built to measure the directional reflectance, emission and scattering characteristics from visible, near infrared, thermal infrared and microwave bands for model validation and calibration. The remote sensing pixel scale "true value" measurement strategy have been designed to gain the ground "true value" of LST, ALBEDO, LAI, soil moisture and ET etc. at 1-km2 for remote sensing product validation.

An Analytic Approach to Modeling Land-Atmosphere Interaction: 1. Construct and Equilibrium Behavior

NASA Astrophysics Data System (ADS)

Brubaker, Kaye L.; Entekhabi, Dara

1995-03-01

A four-variable land-atmosphere model is developed to investigate the coupled exchanges of water and energy between the land surface and atmosphere and the role of these exchanges in the statistical behavior of continental climates. The land-atmosphere system is substantially simplified and formulated as a set of ordinary differential equations that, with the addition of random noise, are suitable for analysis in the form of the multivariate Îto equation. The model treats the soil layer and the near-surface atmosphere as reservoirs with storage capacities for heat and water. The transfers between these reservoirs are regulated by four states: soil saturation, soil temperature, air specific humidity, and air potential temperature. The atmospheric reservoir is treated as a turbulently mixed boundary layer of fixed depth. Heat and moisture advection, precipitation, and layer-top air entrainment are parameterized. The system is forced externally by solar radiation and the lateral advection of air and water mass. The remaining energy and water mass exchanges are expressed in terms of the state variables. The model development and equilibrium solutions are presented. Although comparisons between observed data and steady state model results re inexact, the model appears to do a reasonable job of partitioning net radiation into sensible and latent heat flux in appropriate proportions for bare-soil midlatitude summer conditions. Subsequent work will introduce randomness into the forcing terms to investigate the effect of water-energy coupling and land-atmosphere interaction on variability and persistence in the climatic system.

Stormwater dissolved organic matter: influence of land cover and environmental factors.

PubMed

McElmurry, Shawn P; Long, David T; Voice, Thomas C

2014-01-01

Dissolved organic matter (DOM) plays a major role in defining biological systems and it influences the fate and transport of many pollutants. Despite the importance of DOM, understanding of how environmental and anthropogenic factors influence its composition and characteristics is limited. This study focuses on DOM exported as stormwater from suburban and urban sources. Runoff was collected before entering surface waters and DOM was characterized using specific ultraviolet absorbance at 280 nm (a proxy for aromaticity), molecular weight, polydispersity and the fraction of DOM removed from solution via hydrophobic and H-bonding mechanisms. General linear models (GLMs) incorporating land cover, precipitation, solar radiation and selected aqueous chemical measurements explained variations in DOM properties. Results show (1) molecular characteristics of DOM differ as a function of land cover, (2) DOM produced by forested land is significantly different from other landscapes, particularly urban and suburban areas, and (3) DOM from land cover that contains paved surfaces and sewers is more hydrophobic than from other types of land cover. GLMs incorporating environmental factors and land cover accounted for up to 86% of the variability observed in DOM characteristics. Significant variables (p < 0.05) included solar radiation, water temperature and water conductivity.

Verifying Diurnal Variations of Global Precipitation in Three New Global Reanalyses

NASA Astrophysics Data System (ADS)

Wu, S.; Xie, P.; Sun, F.; Joyce, R.

2013-12-01

Diurnal variations of global precipitation and their representation in three sets of new generation global reanalyses are examined using the reprocessed and bias corrected CMORPH satellite precipitation estimates. The CMORPH satellite precipitation estimates are produced on an 8km by 8km grid over the globe (60oS-60oN) and in a 30-min interval covering a 15-year period from 1998 to the present through combining information from IR and PMW observations from all available satellites. Bias correction is performed for the raw CMORPH precipitation estimates through calibration against an gauge-based analysis over land and against the pentad GPCP analysis over ocean. The reanalyses examined here include the NCEP CFS reanalysis (CFSR), NASA/GSFC MERRA, and ECMWF Interim. The bias-corrected CMORPH is integrated from its original resolution to the reanalyses grid systems to facilitate the verification. First, quantitative agreements between the reanalysis precipitation fields and the CMORPH satellite observation are examined over the global domain. Precipitation structures associated with the large-scale topography are well reproduced when compared against the observation. Evolution of precipitation patterns with the development of transient weather systems are captured by the CFSR and two other reanalyses. The reanalyses tend to generate precipitation fields with wider raining areas and reduced intensity for heavy rainfall cases compared the observations over both land and ocean. Seasonal migration of global precipitation depicted in the 15-year CMORPH satellite observations is very well captured by the three sets of new reanalyses, although magnitude of precipitation is larger, especially in the CFSR, compared to that in the observations. In general, the three sets of new reanalyses exhibit substantial improvements in their performance to represent global precipitation distributions and variations. In particular, the new reanalyses produced precipitation variations of fine time/space scales collated in the observations. The diurnal cycle of the precipitation is reasonably well reproduced by the reanalyses over many global oceanic and land areas. Diurnal amplitude of the reanalyses precipitation, defined as the standard deviation of the 24 hourly mean values, is smaller than that in the observations over most of the oceanic regions, attributable largely to the continuous weak precipitation throughout the diurnal cycle in all of the three reanalyses. Over ocean, the pattern of diurnal variations of precipitation in the reanalyses is quite similar to that in the observations, with the timing of maximum precipitation shifted by1-3 hours. Over land especially over Africa, the reanalyses tend to produce maximum precipitation around noon, much earlier than that in the observations. Particularly noticeable is the diurnal cycle of warm season precipitation over CONUS in association with the eastward propagation of meso-scale systems distinct in the observations. None of the three new reanalyses are capable of detecting this pattern of diurnal variations. A comprehensive description and diagnostic discussions will be given at the AGU meeting.

Synergistic estimation of surface parameters from jointly using optical and microwave observations in EOLDAS

NASA Astrophysics Data System (ADS)

Timmermans, Joris; Gomez-Dans, Jose; Lewis, Philip; Loew, Alexander; Schlenz, Florian

2017-04-01

The large amount of remote sensing data nowadays available provides a huge potential for monitoring crop development, drought conditions and water efficiency. This potential however not been realized yet because algorithms for land surface parameter retrieval mostly use data from only a single sensor. Consequently products that combine different low-level observations from different sensors are hard to find. The lack of synergistic retrieval is caused because it is easier to focus on single sensor types/footprints and temporal observation times, than to find a way to compensate for differences. Different sensor types (microwave/optical) require different radiative transfer (RT) models and also require consistency between the models to have any impact on the retrieval of soil moisture by a microwave instrument. Varying spatial footprints require first proper collocation of the data before one can scale between different resolutions. Considering these problems, merging optical and microwave observations have not been performed yet. The goal of this research was to investigate the potential of integrating optical and microwave RT models within the Earth Observation Land Data Assimilation System (EOLDAS) synergistically to derive biophysical parameters. This system uses a Bayesian data assimilation approach together with observation operators such as the PROSAIL model to estimate land surface parameters. For the purpose of enabling the system to integrate passive microwave radiation (from an ELBARRA II passive microwave radiometer), the Community Microwave Emission Model (CMEM) RT-model, was integrated within the EOLDAS system. In order to quantify the potential, a variety of land surface parameters was chosen to be retrieved from the system, in particular variables that a) impact only optical RT (such as leaf water content and leaf dry matter), b) only impact the microwave RT (such as soil moisture and soil temperature), and c) Leaf Area Index (LAI) that impacts both optical and microwave RT. The results show a high potential when both optical and microwave are used independently. Using only RapidEye only with SAIL RT model, LAI was estimated with R=0.68 with p=0.09, although estimating leaf water content and dry matter showed lower correlations |R|<0.4. The results for retrieving soil temperature and leaf area index retrievals using only (passive microwave) Elbarra-II observations were good with respectively R=[0.85, 0.79], P=[0.0, 0.0], when focusing on dry-spells (of at least 9 days) only the results respectively [R=0.73, and P=0.0], and R=0.89 and R=0.77 for respectively the trend and anomalies. Synergistically using optical and microwave shows also a good potential. This scenario shows that absolute errors improved (with RMSE=1.22 and S=0.89), but with degrading correlations (R=0.59 and P=0.04); the sparse optical observations only improved part of the temporal domain. However in general the synergistic retrieval showed good potential; microwave data provides better information concerning the overall trend of the retrieved LAI due to the regular acquisitions, while optical data provides better information concerning the absolute values of the LAI.

Analyses of shuttle orbiter approach and landing conditions

NASA Technical Reports Server (NTRS)

Teper, G. L.; Dimarco, R. J.; Ashkenas, I. L.; Hoh, R. H.

1981-01-01

A study of one shuttle orbiter approach and landing conditions are summarized. Causes of observed PIO like flight deficiencies are identified and potential cures are examined. Closed loop pilot/vehicle analyses are described and path/attitude stability boundaries defined. The latter novel technique proved of great value in delineating and illustrating the basic causes of this multiloop pilot control problem. The analytical results are shown to be consistent with flight test and fixed base simulation. Conclusions are drawn relating to possible improvements of the shuttle orbiter/digital flight control system.

Observations of land-atmosphere interactions using satellite data

NASA Astrophysics Data System (ADS)

Green, Julia; Gentine, Pierre; Konings, Alexandra; Alemohammad, Hamed; Kolassa, Jana

2016-04-01

Observations of land-atmosphere interactions using satellite data Julia Green (1), Pierre Gentine (1), Alexandra Konings (1,2), Seyed Hamed Alemohammad (3), Jana Kolassa (4) (1) Columbia University, Earth and Environmental Engineering, NY, NY, USA, (2) Stanford University, Environmental Earth System Science, Stanford, CA, USA, (3) Massachusetts Institute of Technology, Civil and Environmental Engineering, Cambridge, MA, USA, (4) National Aeronautics and Space Administration/Goddard Space Flight Center, Greenbelt, MD, USA. Previous studies of global land-atmosphere hotspots have often relied solely on data from global models with the consequence that they are sensitive to model error. On the other hand, by only analyzing observations, it can be difficult to distinguish causality from mere correlation. In this study, we present a general framework for investigating land-atmosphere interactions using Granger Causality analysis applied to remote sensing data. Based on the near linear relationship between chlorophyll sun induced fluorescence (SIF) and photosynthesis (and thus its relationship with transpiration), we use the GOME-2 fluorescence direct measurements to quantify the surface fluxes between the land and atmosphere. By using SIF data to represent the flux, we bypass the need to use soil moisture data from FLUXNET (limited spatially and temporally) or remote sensing (limited by spatial resolution, canopy interference, measurement depth, and radio frequency interference) thus eliminating additional uncertainty. The Granger Causality analysis allows for the determination of the strength of the two-way causal relationship between SIF and several climatic variables: precipitation, radiation and temperature. We determine that warm regions transitioning from water to energy limitation exhibit strong feedbacks between the land surface and atmosphere due to their high sensitivity to climate and weather variability. Tropical rainforest regions show low magnitudes of causal feedback likely due to other factors influencing the land surface such as phenological controls (e.g. leaf area index), nutrient limitations or soil texture. These results were then compared to CMIP5 GCM results using GPP in place of SIF. GCM results varied greatly between models as well as with the observational data analysis indicating deficiencies in the representation of certain modeled phenomena such as low level clouds and boundary layer development. This study highlights the need for GCM improvement to more accurately capture the feedbacks between the land and atmosphere. These results have the potential to improve our understanding of the underlying mechanisms between land and atmosphere coupling, which could ultimately be used to improve weather and climate predictions.

75 FR 41886 - Public Land Order No. 7744; Withdrawal of National Forest System Land for Inyan Kara Area; WY

Federal Register 2010, 2011, 2012, 2013, 2014

2010-07-19

... National Forest System land other than the mining laws (30 U.S.C. Ch. 2). 3. This withdrawal will expire 20... Order No. 7744; Withdrawal of National Forest System Land for Inyan Kara Area; WY AGENCY: Bureau of Land... Forest System land from location and entry under the United States mining laws for a period of 20 years...

Analyzing the Impacts of Natural Environments on Launch and Landing Availability for NASA's Eploration Systems Development Programs

NASA Technical Reports Server (NTRS)

Altino, Karen M.; Burns, K. Lee; Barbre, Robert E.; Leahy, Frank B.

2014-01-01

NASA is developing new capabilities for human and scientific exploration beyond Earth orbit. Natural environments information is an important asset for NASA's development of the next generation space transportation system as part of the Exploration Systems Development Program, which includes the Space Launch System (SLS) and MultiPurpose Crew Vehicle (MPCV) Programs. Natural terrestrial environment conditions - such as wind, lightning and sea states - can affect vehicle safety and performance during multiple mission phases ranging from prelaunch ground processing to landing and recovery operations, including all potential abort scenarios. Space vehicles are particularly sensitive to these environments during the launch/ascent and the entry/landing phases of mission operations. The Marshall Space Flight Center (MSFC) Natural Environments Branch provides engineering design support for NASA space vehicle projects and programs by providing design engineers and mission planners with natural environments definitions as well as performing custom analyses to help characterize the impacts the natural environment may have on vehicle performance. One such analysis involves assessing the impact of natural environments to operational availability. Climatological time series of operational surface weather observations are used to calculate probabilities of meeting or exceeding various sets of hypothetical vehicle-specific parametric constraint thresholds.

Erosion Prediction Analysis and Landuse Planning in Gunggung Watershed, Bali, Indonesia

NASA Astrophysics Data System (ADS)

Trigunasih, N. M.; Kusmawati, T.; Yuli Lestari, N. W.

2018-02-01

The purpose of this research is to predict the erosion that occurs in Gunggung watershed and sustainable landuse management plan. This research used the USLE (Universal Soil Loss Equation) methodology. The method used observation / field survey and soil analysis at the Soil Laboratory of Faculty of Agriculture, Udayana University. This research is divided into 5 stages, (1) land unit determination, (2) Field observation and soil sampling, (3) Laboratory analysis and data collection, (4) Prediction of erosion using USLE (Universal Soil Loss Equation) method, (5) The permissible erosion determination (EDP) then (6) determines the level of erosion hazard based on the depth of the soil, as well as the soil conservation plan if the erosion is greater than the allowed erosion, and (7) determining landuse management plan for sustainable agriculture. Erosion which value is smaller than soil loss tolerance can be exploited in a sustainable manner, while erosion exceeds allowable erosion will be conservation measures. Conservation action is the improvement of vegetation and land management. Land management like improvements the terrace, addition of organic matter, increase plant density, planting ground cover and planting layered header system will increase the land capability classes. Land use recommended after management is mixed plantation high density with forest plants, mix plantation high density with patio bench construction, seasonal cultivation and perennial crops, cultivation of perennial crops and cultivation of seasonal crops.

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.

The ERTS-1 investigation (ER-600): A compendium of analysis results of the utility of ERTS-1 data for land resources management

NASA Technical Reports Server (NTRS)

Erb, R. B.

1974-01-01

The results of the ERTS-1 investigations conducted by the Earth Observations Division at the NASA Lyndon B. Johnson Space Center are summarized in this report, which is an overview of documents detailing individual investigations. Conventional image interpretation and computer-aided classification procedures were the two basic techniques used in analyzing the data for detecting, identifying, locating, and measuring surface features related to earth resources. Data from the ERTS-1 multispectral scanner system were useful for all applications studied, which included agriculture, coastal and estuarine analysis, forestry, range, land use and urban land use, and signature extension. Percentage classification accuracies are cited for the conventional and computer-aided techniques.

GOFC-GOLD :: Global Observation of Forest and Land Cover Dynamics

Science.gov Websites

GTOS HOME OVERVIEW CALENDAR ORGANIZATION LAND TEAM FIRE TEAM NETWORKS WORKING GROUPS PARTNERS DATA availability of observations of forests and land cover at regional and global scales and to produce useful

The public lands and their water supply: Section in Sixteenth Annual Report of the United States Geological Survey to the Secretary of the Interior, 1894-1895: Part II - Papers of an economic character

USGS Publications Warehouse

Newell, Frederick Haynes

1896-01-01

Questions as to the best methods of utilization and disposal of the vacant public lands have been of great prominence ever since the birth of the Republic, and the inauguration of a wise and judicious system of land laws that has been deemed one of the noteworthy achievements of the early part of the century. Many questions, however, are still far from being finally settled; for with the rapid changes incident to the growth of the nation, the settlement of the Mississippi Valley, and the construction of many transcontinental lines of communication leading to the highly cultivated and thickly populated lands of the Pacific Coast, new conditions have arisen to which former precedents and customs are no longer applicable.While the well-watered lands stretching from the Ohio to the Missouri were open to settlement, the problems were mainly those of administration; but now that the humid lands are disposed of, and pioneers are pressing forward to every part of the vast interior region where water and not land is the first item of value, it becomes necessary to modify the treatment of the public lands and to introduce better methods. Such necessary improvements, or the introduction of systems leading to greater prosperity, must depend to a large extent upon the possession by the general public of broad yet accurate knowledge of the chief characteristics of the remaining public domain. This knowledge can be obtained only by a thorough scientific examination and an impartial statement of the facts as ascertained by disinterested observers.

Diagnosing the Nature of Land-Atmosphere Coupling: A Case Study of Dry/Wet Extremes

NASA Technical Reports Server (NTRS)

Santanello, Joseph A., Jr.; Peters-Lidard, Christa; Kennedy, Aaron D.

2012-01-01

Land-atmosphere (L-A) interactions play a critical role in determining the diurnal evolution of land surface and planetary boundary layer (PBL) temperature and moisture states and fluxes. In turn, these interactions regulate the strength of the connection between surface moisture and precipitation in a coupled system. To address deficiencies in numerical weather prediction and climate models due to improper treatment of L-A interactions, recent studies have focused on development of diagnostics to quantify the strength and accuracy of the land-PBL coupling at the process-level. In this study, a diagnosis of the nature and impacts oflocalland-atmosphere coupling (LoCo) during dry and wet extreme conditions is presented using a combination of models and observations during the summers of2006-7 in the U.S. Southern Great Plains. Specifically, the Weather Research and Forecasting (WRF) model has been coupled to NASA's Land Information System (LIS), which provides a flexible and high-resolution representation and initialization of land surface physics and states. A range of diagnostics exploring the links and feedbacks between soil moisture and precipitation are examined for the dry/wet regimes of this region, along with the behavior and accuracy of different land-PBL scheme couplings under these conditions. In addition, we examine the impact of improved specification ofland surface states, anomalies, and fluxes that are obtained through the use of a hew optimization and uncertainty module in LIS, on the L-A coupling in WRF forecasts. Results demonstrate how LoCo diagnostics can be applied to coupled model components in the context of their integrated impacts on the process-chain connecting the land surface to the PBL and support of hydrological anomalies.

Shipborne LF-VLF oceanic lightning observations and modeling

NASA Astrophysics Data System (ADS)

Zoghzoghy, F. G.; Cohen, M. B.; Said, R. K.; Lehtinen, N. G.; Inan, U. S.

2015-10-01

Approximately 90% of natural lightning occurs over land, but recent observations, using Global Lightning Detection (GLD360) geolocation peak current estimates and satellite optical data, suggested that cloud-to-ground flashes are on average stronger over the ocean. We present initial statistics from a novel experiment using a Low Frequency (LF) magnetic field receiver system installed aboard the National Oceanic Atmospheric Agency (NOAA) Ronald W. Brown research vessel that allowed the detection of impulsive radio emissions from deep-oceanic discharges at short distances. Thousands of LF waveforms were recorded, facilitating the comparison of oceanic waveforms to their land counterparts. A computationally efficient electromagnetic radiation model that accounts for propagation over lossy and curved ground is constructed and compared with previously published models. We include the effects of Earth curvature on LF ground wave propagation and quantify the effects of channel-base current risetime, channel-base current falltime, and return stroke speed on the radiated LF waveforms observed at a given distance. We compare simulation results to data and conclude that previously reported larger GLD360 peak current estimates over the ocean are unlikely to fully result from differences in channel-base current risetime, falltime, or return stroke speed between ocean and land flashes.

Atmosphere Assessment for MARS Science Laboratory Entry, Descent and Landing Operations

NASA Technical Reports Server (NTRS)

Cianciolo, Alicia D.; Cantor, Bruce; Barnes, Jeff; Tyler, Daniel, Jr.; Rafkin, Scot; Chen, Allen; Kass, David; Mischna, Michael; Vasavada, Ashwin R.

2013-01-01

On August 6, 2012, the Mars Science Laboratory rover, Curiosity, successfully landed on the surface of Mars. The Entry, Descent and Landing (EDL) sequence was designed using atmospheric conditions estimated from mesoscale numerical models. The models, developed by two independent organizations (Oregon State University and the Southwest Research Institute), were validated against observations at Mars from three prior years. In the weeks and days before entry, the MSL "Council of Atmospheres" (CoA), a group of atmospheric scientists and modelers, instrument experts and EDL simulation engineers, evaluated the latest Mars data from orbiting assets including the Mars Reconnaissance Orbiter's Mars Color Imager (MARCI) and Mars Climate Sounder (MCS), as well as Mars Odyssey's Thermal Emission Imaging System (THEMIS). The observations were compared to the mesoscale models developed for EDL performance simulation to determine if a spacecraft parameter update was necessary prior to entry. This paper summarizes the daily atmosphere observations and comparison to the performance simulation atmosphere models. Options to modify the atmosphere model in the simulation to compensate for atmosphere effects are also presented. Finally, a summary of the CoA decisions and recommendations to the MSL project in the days leading up to EDL is provided.

Identifying and Evaluating the Relationships that Control a Land Surface Model's Hydrological Behavior

NASA Technical Reports Server (NTRS)

Koster, Randal D.; Mahanama, Sarith P.

2012-01-01

The inherent soil moisture-evaporation relationships used in today 's land surface models (LSMs) arguably reflect a lot of guesswork given the lack of contemporaneous evaporation and soil moisture observations at the spatial scales represented by regional and global models. The inherent soil moisture-runoff relationships used in the LSMs are also of uncertain accuracy. Evaluating these relationships is difficult but crucial given that they have a major impact on how the land component contributes to hydrological and meteorological variability within the climate system. The relationships, it turns out, can be examined efficiently and effectively with a simple water balance model framework. The simple water balance model, driven with multi-decadal observations covering the conterminous United States, shows how different prescribed relationships lead to different manifestations of hydrological variability, some of which can be compared directly to observations. Through the testing of a wide suite of relationships, the simple model provides estimates for the underlying relationships that operate in nature and that should be operating in LSMs. We examine the relationships currently used in a number of different LSMs in the context of the simple water balance model results and make recommendations for potential first-order improvements to these LSMs.

Preliminary study of a possible automatic landing system

NASA Technical Reports Server (NTRS)

Sherman, W. L.; Winfrey, S. W.

1974-01-01

Navigation and control laws for a possible automatic landing system have been investigated. The system makes use of data from an inertial table and either an airborne or ground radar to generate signals that guide the airplane to a landing. All landing maneuvers take place within a zone that extends 6000 m out from the touchdown point, 4000 m on each side of the runway center line, and 540 m high. The results show that the system can adequately control the airplane on steep, curved decelerating approaches to a landing that takes place with small errors from the desired landing point and desired airplane attitude. The system studied would interface well with the scanning beam microwave landing system (MLS). The use of this system with the MLS makes it possible to incorporate an independent landing monitor.

Flight test evaluation of the E-systems Differential GPS category 3 automatic landing system

NASA Technical Reports Server (NTRS)

Kaufmann, David N.; Mcnally, B. David

1995-01-01

Test flights were conducted to evaluate the capability of Differential Global Positioning System (DGPS) to provide the accuracy and integrity required for International Civil Aviation Organization (ICAO) Category (CAT) III precision approach and landings. These test flights were part of a Federal Aviation Administration (FAA) program to evaluate the technical feasibility of using DGPS based technology for CAT III precision approach and landing applications. An IAI Westwind 1124 aircraft (N24RH) was equipped with DGPS receiving equipment and additional computing capability provided by E-Systems. The test flights were conducted at NASA Ames Research Center's Crows Landing Flight Facility, Crows Landing, California. The flight test evaluation was based on completing 100 approaches and landings. The navigation sensor error accuracy requirements were based on ICAO requirements for the Microwave Landing System (MLS). All of the approaches and landings were evaluated against ground truth reference data provided by a laser tracker. Analysis of these approaches and landings shows that the E-Systems DGPS system met the navigation sensor error requirements for a successful approach and landing 98 out of 100 approaches and landings, based on the requirements specified in the FAA CAT III Level 2 Flight Test Plan. In addition, the E-Systems DGPS system met the integrity requirements for a successful approach and landing or stationary trial for all 100 approaches and landings and all ten stationary trials, based on the requirements specified in the FAA CAT III Level 2 Flight Test Plan.

Large differences in land use emission quantifications implied by definition discrepancies

NASA Astrophysics Data System (ADS)

Stocker, B. D.; Joos, F.

2015-03-01

The quantification of CO2 emissions from anthropogenic land use and land use change (eLUC) is essential to understand the drivers of the atmospheric CO2 increase and to inform climate change mitigation policy. Reported values in synthesis reports are commonly derived from different approaches (observation-driven bookkeeping and process-modelling) but recent work has emphasized that inconsistencies between methods may imply substantial differences in eLUC estimates. However, a consistent quantification is lacking and no concise modelling protocol for the separation of primary and secondary components of eLUC has been established. Here, we review the conceptual differences of eLUC quantification methods and apply an Earth System Model to demonstrate that what is claimed to represent total eLUC differs by up to ~20% when quantified from ESM vs. offline vegetation models. Under a future business-as-usual scenario, differences tend to increase further due to slowing land conversion rates and an increasing impact of altered environmental conditions on land-atmosphere fluxes. We establish how coupled Earth System Models may be applied to separate component fluxes of eLUC arising from the replacement of potential C sinks/sources and the land use feedback and show that secondary fluxes derived from offline vegetation models are conceptually and quantitatively not identical to either, nor their sum. Therefore, we argue that synthesis studies and global carbon budget accountings should resort to the "least common denominator" of different methods, following the bookkeeping approach where only primary land use emissions are quantified under the assumption of constant environmental boundary conditions.

Quantifying differences in land use emission estimates implied by definition discrepancies

NASA Astrophysics Data System (ADS)

Stocker, B. D.; Joos, F.

2015-11-01

The quantification of CO2 emissions from anthropogenic land use and land use change (eLUC) is essential to understand the drivers of the atmospheric CO2 increase and to inform climate change mitigation policy. Reported values in synthesis reports are commonly derived from different approaches (observation-driven bookkeeping and process-modelling) but recent work has emphasized that inconsistencies between methods may imply substantial differences in eLUC estimates. However, a consistent quantification is lacking and no concise modelling protocol for the separation of primary and secondary components of eLUC has been established. Here, we review differences of eLUC quantification methods and apply an Earth System Model (ESM) of Intermediate Complexity to quantify them. We find that the magnitude of effects due to merely conceptual differences between ESM and offline vegetation model-based quantifications is ~ 20 % for today. Under a future business-as-usual scenario, differences tend to increase further due to slowing land conversion rates and an increasing impact of altered environmental conditions on land-atmosphere fluxes. We establish how coupled Earth System Models may be applied to separate secondary component fluxes of eLUC arising from the replacement of potential C sinks/sources and the land use feedback and show that secondary fluxes derived from offline vegetation models are conceptually and quantitatively not identical to either, nor their sum. Therefore, we argue that synthesis studies should resort to the "least common denominator" of different methods, following the bookkeeping approach where only primary land use emissions are quantified under the assumption of constant environmental boundary conditions.

Land quality, sustainable development and environmental degradation in agricultural districts: A computational approach based on entropy indexes

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

Zambon, Ilaria, E-mail: ilaria.zambon@unitus.it; Colantoni, Andrea; Carlucci, Margherita

Land Degradation (LD) in socio-environmental systems negatively impacts sustainable development paths. This study proposes a framework to LD evaluation based on indicators of diversification in the spatial distribution of sensitive land. We hypothesize that conditions for spatial heterogeneity in a composite index of land sensitivity are more frequently associated to areas prone to LD than spatial homogeneity. Spatial heterogeneity is supposed to be associated with degraded areas that act as hotspots for future degradation processes. A diachronic analysis (1960–2010) was performed at the Italian agricultural district scale to identify environmental factors associated with spatial heterogeneity in the degree of landmore » sensitivity to degradation based on the Environmentally Sensitive Area Index (ESAI). In 1960, diversification in the level of land sensitivity measured using two common indexes of entropy (Shannon's diversity and Pielou's evenness) increased significantly with the ESAI, indicating a high level of land sensitivity to degradation. In 2010, surface area classified as “critical” to LD was the highest in districts with diversification in the spatial distribution of ESAI values, confirming the hypothesis formulated above. Entropy indexes, based on observed alignment with the concept of LD, constitute a valuable base to inform mitigation strategies against desertification. - Highlights: • Spatial heterogeneity is supposed to be associated with degraded areas. • Entropy indexes can inform mitigation strategies against desertification. • Assessing spatial diversification in the degree of land sensitivity to degradation. • Mediterranean rural areas have an evident diversity in agricultural systems. • A diachronic analysis carried out at the Italian agricultural district scale.« less

MODIS Cloud Products Derived from Terra and Aqua During CRYSTAL-FACE

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, S.; Riedi, J. C.; Ackerman, S. A.; Menzel, W. P.

2003-01-01

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. During the CRYSTAL-FACE experiment, numerous aircraft coordinated both in situ and remote sensing observations with the Terra and Aqua spacecraft. In this paper we will emphasize the optical, microphysical, and physical properties of both liquid water and ice clouds obtained from an analysis of the satellite observations over Florida and the Gulf of Mexico during July 2002. We will present the frequency distribution of liquid water and ice cloud microphysical properties throughout the region, separating the results over land and ocean. Probability distributions of effective radius and cloud optical thickness will also be shown.

Beyond Impervious: Urban Land-Cover Pattern Variation and Implications for Watershed Management

NASA Astrophysics Data System (ADS)

Beck, Scott M.; McHale, Melissa R.; Hess, George R.

2016-07-01

Impervious surfaces degrade urban water quality, but their over-coverage has not explained the persistent water quality variation observed among catchments with similar rates of imperviousness. Land-cover patterns likely explain much of this variation, although little is known about how they vary among watersheds. Our goal was to analyze a series of urban catchments within a range of impervious cover to evaluate how land-cover varies among them. We then highlight examples from the literature to explore the potential effects of land-cover pattern variability for urban watershed management. High-resolution (1 m2) land-cover data were used to quantify 23 land-cover pattern and stormwater infrastructure metrics within 32 catchments across the Triangle Region of North Carolina. These metrics were used to analyze variability in land-cover patterns among the study catchments. We used hierarchical clustering to organize the catchments into four groups, each with a distinct landscape pattern. Among these groups, the connectivity of combined land-cover patches accounted for 40 %, and the size and shape of lawns and buildings accounted for 20 %, of the overall variation in land-cover patterns among catchments. Storm water infrastructure metrics accounted for 8 % of the remaining variation. Our analysis demonstrates that land-cover patterns do vary among urban catchments, and that trees and grass (lawns) are divergent cover types in urban systems. The complex interactions among land-covers have several direct implications for the ongoing management of urban watersheds.

23 CFR 970.214 - Federal lands congestion management system (CMS).

Code of Federal Regulations, 2014 CFR

2014-04-01

... 23 Highways 1 2014-04-01 2014-04-01 false Federal lands congestion management system (CMS). 970... LANDS HIGHWAYS NATIONAL PARK SERVICE MANAGEMENT SYSTEMS National Park Service Management Systems § 970.214 Federal lands congestion management system (CMS). (a) For purposes of this section, congestion...

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.

Understanding the global land-use marketplace

NASA Astrophysics Data System (ADS)

Belward, Alan

2013-04-01

Over 7 billion humans inhabit Earth and our population increases by more than a hundred per minute. Satisfying the resource demands of seven-plus billion people whilst sustaining the Earth System is a delicate balancing act. We need to balance resource use with regenerative capacity and this balance must avoid tipping points beyond which return and recovery are impossible. Tipping points in the physical, biogeochemical and ecological components of the Earth System have all been proposed - adding the global land-use marketplace to such a list may not be obvious but it undeniably deserves attention. The land is where most humans live most of the time. It meets most food, fuel, freshwater and fibre requirements and shapes Earth's climate. As land is essentially a finite resource this leads to intense competition. Monetizing land resources is nothing new. Choice of agricultural practice has long been governed in part by economics. But in recent years monetization has extended to include new dimensions such as carbon trading and biodiversity offsetting. Our land-use marketplace now has to optimise food, fibre and fuel production whilst maintaining and enhancing land's role as a carbon sink, a hydrologic reservoir and a support for biological diversity. International (and national) environmental policies aim to find a balance between such competing uses. These policies call for accurate, accountable and timely evidence concerning how, when and where land resources are changing. In 2013 the European Space Agency will launch the first of the Copernicus programme's Earth Observing Sentinel satellites. These technologically advanced systems are matched to data acquisition and processing strategies that should provide scientific evidence concerning the land on an unprecedented scale. This paper provides one vision of how Earth science will benefit from the Sentinels and their associated services and how this science will subsequently inform and shape policies, especially those linked to Multilateral Environmental Agreements. Examples will show how the science can promote transparency and good governance, help build knowledge-bases, capacity and markets and illustrates how Copernicus services and the Sentinels are an important component of EU international co-operation.

Establishment and analysis of a High-Resolution Assimilation Dataset of the water-energy cycle in China

NASA Astrophysics Data System (ADS)

Wen, Xiaohang; Dong, Wenjie; Yuan, Wenping; Zheng, Zhiyuan

For better prediction and understanding of land-atmospheric interaction, in-situ observed meteorological data acquired from the China Meteorological Administration (CMA) were assimilated in the Weather Research and Forecasting (WRF) model and the monthly Green Vegetation Coverage (GVF) data, which was calculated using the Normalized Difference Vegetation Index (NDVI) of the Earth Observing System Moderate-Resolution Imaging Spectroradiometer (EOS-MODIS) and Digital Elevation Model (DEM) data of the Shuttle Radar Topography Mission (SRTM) system. Furthermore, the WRF model produced a High-Resolution Assimilation Dataset of the water-energy cycle in China (HRADC). This dataset has a horizontal resolution of 25 km for near surface meteorological data, such as air temperature, humidity, wind vectors and pressure (19 levels); soil temperature and moisture (four levels); surface temperature; downward/upward short/long radiation; 3-h latent heat flux; sensible heat flux; and ground heat flux. In this study, we 1) briefly introduce the cycling 3D-Var assimilation method and 2) compare results of meteorological elements, such as 2 m temperature and precipitation generated by the HRADC with the gridded observation data from CMA, and surface temperature and specific humidity with Global Land Data Assimilation System (GLDAS) output data from the National Aeronautics and Space Administration (NASA). We find that the simulated results of monthly 2 m temperature from HRADC is improved compared with the control simulation and has effectively reproduced the observed patterns. The simulated special distribution of ground surface temperature and specific humidity from HRADC are much closer to GLDAS outputs. The spatial distribution of root mean square errors (RMSE) and bias of 2 m temperature between observations and HRADC is reduced compared with the bias between observations and the control run. The monthly spatial distribution of surface temperature and specific humidity from HRADC is consistent with the GLDAS outputs over China. This study could improve the land surface parameters by utilizing remote sensing data and could further improve atmospheric elements with a data assimilation system. This work provides an effective attempt at combining multi-source data with different spatial and temporal scales into numerical simulations, and the simulated results could be used in further research on the long-term climatic effects and characteristics of the water-energy cycle over China.

Land Cover and Hydrologic Variability in Residential Watersheds: Drivers of N Loss in Sacramento CA

NASA Astrophysics Data System (ADS)

McConaghie, J. B.; Zhou, W.; Cadenasso, M. L.

2011-12-01

A key aspect to understanding N loss from urban systems is the link between landscape heterogeneity and variability in non-point source (NPS) nitrogen (N) flux. Because water transports N across the landscape and into receiving streams as runoff, understanding how landscape heterogeneity influences water quantity and movement is also needed. High variability in N loss has been documented from urban systems. However, typical NPS studies characterize landscape heterogeneity by land use and only weakly explain variability in stream N. Focusing on land cover, rather than land use, may better explain observed variability in N loss because land cover elements may better indicate major drivers of N loss. Also, most studies have been conducted in temperate urban systems with stream flow year round. In semi-arid urban systems, storm flow accounts for the majority of stream discharges, and residential irrigation contributes significantly to flows in the dry season. To address how landscape heterogeneity affects variability in water quantity and quality in urban streams, we examined how land cover influences stream flows and N loss in residential streams of metropolitan Sacramento, CA. We analyzed fine-scale variation in land cover and stream N during base flow and storm events in 4 residential watersheds which differ substantially in land cover. We classified land cover using HERCULES (High Ecological Resolution Classification for Urban Landscapes and Environmental Systems) which was developed specifically for urban systems. HERCULES classifies high-resolution aerial photographs into 5 elements: buildings, pavement, herbaceous and woody vegetation, and bare soil. Streams were sampled for discharge, NO3, and Total N using auto samplers during storms in the 2010-2011 rainy season and monthly in the dry season. Partial correlation analysis and multivariate models describe the relationships between land cover elements, water retention, and stream N in these watersheds. We found an early season flush of N from streams during the first storms, and N levels diminished through progressive storms. Also, N concentrations were higher during the rainy season compared to the dry season. High proportion of impervious cover was associated with greater flow rates overall, while high proportion of herbaceous cover was associated with reduced flow rates during storms. The proportion of pavement in the watersheds, a commonly used indicator of urban intensity, did not strongly correlate with increased levels of stream N except during the flush, but did correlate with the magnitude and timing of flows during storms. However, high proportions of building cover, e.g. residential homes, did correlate with higher N fluxes. The use of fertilizers or enhanced N cycling through vegetation management near residential buildings is a possible source of increased N. Management to reduce aquatic enrichment of N from urban ecosystems may be best directed toward identifying N sources and sinks associated with specific land covers. Management must also account for seasonal dynamics, such as annual hydrologic patterns, which drive the loss of N.

Snow Radiance Data Assimilation over High Mountain Asia Using the NASA Land Information System and a Well-Trained Support Vector Machine

NASA Astrophysics Data System (ADS)

Kwon, Y.; Forman, B. A.; Yoon, Y.; Kumar, S.

2017-12-01

High Mountain Asia (HMA) has been progressively losing ice and snow in recent decades, which could negatively impact regional water supply and native ecosystems. One goal of this study is to characterize the spatiotemporal variability of snow (and ice) across the HMA region. In addition, modeled snow water equivalent (SWE) estimates will be enhanced through the assimilation of passive microwave brightness temperatures (TB) collected by the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) as part of a radiance assimilation system. The radiance assimilation framework includes the NASA Land Information System (LIS) in conjunction with a well-trained support vector machine (SVM) that acts as the observation operator. The Noah Land Surface Model with multi-parameterization options (Noah-MP) is used as the prior model for simulating snow dynamics. Noah-MP is forced by meteorological fields from the NASA Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) atmospheric reanalysis for the periods 01 Sep. 2002 to 01 Sep. 2011. The radiance assimilation system requires two separate phases: 1) training and 2) assimilation. During the training phase, a nonlinear SVM is generated for three different AMSR-E frequencies - 10.65, 18.7, and 36.5 GHz - at both vertical and horizontal polarization. The trained SVM is then used to predict TB during the assimilation phase. An ensemble Kalman filter will be used to condition the model on AMSR-E brightness temperatures not used during SVM training. The performance of the Noah-MP (with and without radiance assimilation) will be assessed via comparison to in-situ measurements, remotely-sensing geophysical retrievals, and other reanalysis products.

Ocean observing systems support operational forecasts for the timing of Maine's lobster fishery

NASA Astrophysics Data System (ADS)

Mills, K.; Hernandez, C.; Pershing, A. J.

2016-02-01

American lobster supports one of the most valuable fisheries in the United States, with a landed value in 2013 exceeding $460M. Although US lobstermen are free to fish throughout the year, the New England climate, lobster biology and fleet dynamics lead to a strong annual cycle with catch rates rising rapidly in early summer and landings peaking in late summer. When this annual cycle is disrupted, it can impact the supply and ultimately the price of lobsters. During the record warm conditions in 2012, the rise in catch rates occurred three weeks ahead of normal. Combined with higher than normal landings from the spring Canadian fishery, the early and high volume landings in 2012 led to a collapse in price that severely stressed the U. S. fishery, especially in Maine where over 85% of the landings occur. Based on this experience, we have been developing seasonal forecasts of the phenology of Maine lobster landings. Using temperatures at 50m from four NERACOOS buoys in the Gulf of Maine, we can reliably forecast the date when the Maine lobster fishery will `turn on' for the year, with prediction accuracy peaking in April. The high-landings period normally starts in July, and the 2-3 month lead-time provides some advance warning to dealers and processors of when their capacity needs to be ready and to fishermen of potential supply chain and market impacts such as we observed in 2012. We are currently working towards finer-scale regional forecasts along the Maine coast that may include other features that will provide information to help the lobster industry adapt to the rapid changes that are underway in the Gulf of Maine.

Land-atmosphere coupling and climate prediction over the U.S. Southern Great Plains

NASA Astrophysics Data System (ADS)

Williams, Ian N.; Lu, Yaqiong; Kueppers, Lara M.; Riley, William J.; Biraud, Sebastien C.; Bagley, Justin E.; Torn, Margaret S.

2016-10-01

Biases in land-atmosphere coupling in climate models can contribute to climate prediction biases, but land models are rarely evaluated in the context of this coupling. We tested land-atmosphere coupling and explored effects of land surface parameterizations on climate prediction in a single-column version of the National Center for Atmospheric Research Community Earth System Model (CESM1.2.2) and an off-line Community Land Model (CLM4.5). The correlation between leaf area index (LAI) and surface evaporative fraction (ratio of latent to total turbulent heat flux) was substantially underpredicted compared to observations in the U.S. Southern Great Plains, while the correlation between soil moisture and evaporative fraction was overpredicted by CLM4.5. To estimate the impacts of these errors on climate prediction, we modified CLM4.5 by prescribing observed LAI, increasing soil resistance to evaporation, increasing minimum stomatal conductance, and increasing leaf reflectance. The modifications improved the predicted soil moisture-evaporative fraction (EF) and LAI-EF correlations in off-line CLM4.5 and reduced the root-mean-square error in summer 2 m air temperature and precipitation in the coupled model. The modifications had the largest effect on prediction during a drought in summer 2006, when a warm bias in daytime 2 m air temperature was reduced from +6°C to a smaller cold bias of -1.3°C, and a corresponding dry bias in precipitation was reduced from -111 mm to -23 mm. The role of vegetation in droughts and heat waves is underpredicted in CESM1.2.2, and improvements in land surface models can improve prediction of climate extremes.

Historical record of Landsat global coverage

USGS Publications Warehouse

Goward, Samuel; Arvidson, Terry; Williams, Darrel; Faundeen, John; Irons, James; Franks, Shannon

2006-01-01

The long-term, 34+ year record of global Landsat remote sensing data is a critical resource to study the Earth system and human impacts on this system. The National Satellite Land Remote Sensing Data Archive (NSLRSDA) is charged by public law to: “maintain a permanent, comprehensive Government archive of global Landsat and other land remote sensing data for long-term monitoring and study of the changing global environment” (U.S. Congress, 1992). The advisory committee for NSLRSDA requested a detailed analysis of observation coverage within the U.S. Landsat holdings, as well as that acquired and held by International Cooperator (IC) stations. Our analyses, to date, have found gaps of varying magnitude in U.S. holdings of Landsat global coverage data, which appear to reflect technical or administrative variations in mission operations. In many cases it may be possible to partially fill these gaps in U.S. holdings through observations that were acquired and are now being held at International Cooperator stations.

A Land System representation for global assessments and land-use modeling.

PubMed

van Asselen, Sanneke; Verburg, Peter H

2012-10-01

Current global scale land-change models used for integrated assessments and climate modeling are based on classifications of land cover. However, land-use management intensity and livestock keeping are also important aspects of land use, and are an integrated part of land systems. This article aims to classify, map, and to characterize Land Systems (LS) at a global scale and analyze the spatial determinants of these systems. Besides proposing such a classification, the article tests if global assessments can be based on globally uniform allocation rules. Land cover, livestock, and agricultural intensity data are used to map LS using a hierarchical classification method. Logistic regressions are used to analyze variation in spatial determinants of LS. The analysis of the spatial determinants of LS indicates strong associations between LS and a range of socioeconomic and biophysical indicators of human-environment interactions. The set of identified spatial determinants of a LS differs among regions and scales, especially for (mosaic) cropland systems, grassland systems with livestock, and settlements. (Semi-)Natural LS have more similar spatial determinants across regions and scales. Using LS in global models is expected to result in a more accurate representation of land use capturing important aspects of land systems and land architecture: the variation in land cover and the link between land-use intensity and landscape composition. Because the set of most important spatial determinants of LS varies among regions and scales, land-change models that include the human drivers of land change are best parameterized at sub-global level, where similar biophysical, socioeconomic and cultural conditions prevail in the specific regions. © 2012 Blackwell Publishing Ltd.

LSRA landing with tire test

NASA Technical Reports Server (NTRS)

1994-01-01

A space shuttle landing gear system is visible between the two main landing gear components on this NASA CV-990, modified as a Landing Systems Research Aircraft (LSRA). The space shuttle landing gear test unit, operated by a high-pressure hydraulic system, allowed engineers to assess and document the performance of space shuttle main and nose landing gear systems, tires and wheel assemblies, plus braking and nose wheel steering performance. The series of 155 test missions for the space shuttle program, conducted at NASA's Dryden Flight Research Center, Edwards, California, provided extensive data about the life and endurance of the shuttle tire systems and helped raise the shuttle crosswind landing limits at Kennedy.

Process Architecture for Managing Digital Object Identifiers

NASA Astrophysics Data System (ADS)

Wanchoo, L.; James, N.; Stolte, E.

2014-12-01

In 2010, NASA's Earth Science Data and Information System (ESDIS) Project implemented a process for registering Digital Object Identifiers (DOIs) for data products distributed by Earth Observing System Data and Information System (EOSDIS). For the first 3 years, ESDIS evolved the process involving the data provider community in the development of processes for creating and assigning DOIs, and guidelines for the landing page. To accomplish this, ESDIS established two DOI User Working Groups: one for reviewing the DOI process whose recommendations were submitted to ESDIS in February 2014; and the other recently tasked to review and further develop DOI landing page guidelines for ESDIS approval by end of 2014. ESDIS has recently upgraded the DOI system from a manually-driven system to one that largely automates the DOI process. The new automated feature include: a) reviewing the DOI metadata, b) assigning of opaque DOI name if data provider chooses, and c) reserving, registering, and updating the DOIs. The flexibility of reserving the DOI allows data providers to embed and test the DOI in the data product metadata before formally registering with EZID. The DOI update process allows the changing of any DOI metadata except the DOI name unless the name has not been registered. Currently, ESDIS has processed a total of 557 DOIs of which 379 DOIs are registered with EZID and 178 are reserved with ESDIS. The DOI incorporates several metadata elements that effectively identify the data product and the source of availability. Of these elements, the Uniform Resource Locator (URL) attribute has the very important function of identifying the landing page which describes the data product. ESDIS in consultation with data providers in the Earth Science community is currently developing landing page guidelines that specify the key data product descriptive elements to be included on each data product's landing page. This poster will describe in detail the unique automated process and underlying system implemented by ESDIS for registering DOIs, as well as some of the lessons learned from the development of the process. In addition, this paper will summarize the recommendations made by the DOI Process and DOI Landing Page User Working Groups, and the procedures developed for implementing those recommendations.

Synergy of airborne LiDAR and Worldview-2 satellite imagery for land cover and habitat mapping: A BIO_SOS-EODHaM case study for the Netherlands

NASA Astrophysics Data System (ADS)

Mücher, C. A.; Roupioz, L.; Kramer, H.; Bogers, M. M. B.; Jongman, R. H. G.; Lucas, R. M.; Kosmidou, V. E.; Petrou, Z.; Manakos, I.; Padoa-Schioppa, E.; Adamo, M.; Blonda, P.

2015-05-01

A major challenge is to develop a biodiversity observation system that is cost effective and applicable in any geographic region. Measuring and reliable reporting of trends and changes in biodiversity requires amongst others detailed and accurate land cover and habitat maps in a standard and comparable way. The objective of this paper is to assess the EODHaM (EO Data for Habitat Mapping) classification results for a Dutch case study. The EODHaM system was developed within the BIO_SOS (The BIOdiversity multi-SOurce monitoring System: from Space TO Species) project and contains the decision rules for each land cover and habitat class based on spectral and height information. One of the main findings is that canopy height models, as derived from LiDAR, in combination with very high resolution satellite imagery provides a powerful input for the EODHaM system for the purpose of generic land cover and habitat mapping for any location across the globe. The assessment of the EODHaM classification results based on field data showed an overall accuracy of 74% for the land cover classes as described according to the Food and Agricultural Organization (FAO) Land Cover Classification System (LCCS) taxonomy at level 3, while the overall accuracy was lower (69.0%) for the habitat map based on the General Habitat Category (GHC) system for habitat surveillance and monitoring. A GHC habitat class is determined for each mapping unit on the basis of the composition of the individual life forms and height measurements. The classification showed very good results for forest phanerophytes (FPH) when individual life forms were analyzed in terms of their percentage coverage estimates per mapping unit from the LCCS classification and validated with field surveys. Analysis for shrubby chamaephytes (SCH) showed less accurate results, but might also be due to less accurate field estimates of percentage coverage. Overall, the EODHaM classification results encouraged us to derive the heights of all vegetated objects in the Netherlands from LiDAR data, in preparation for new habitat classifications.

Land-atmosphere interaction and disaster-causing process of drought in northern China: observation and experiment (DroughtPEX_China)

NASA Astrophysics Data System (ADS)

Li, Yaohui

2017-04-01

Drought is one of the most common and frequent nature disasters in the world, particularly in China under the continental monsoonal climate with great variation. About thirty percent of economic loss caused by natural disasters is contributed by droughts in China, which is by far the most damaging weather disasters because of its long duration and extensive hazard areas. Droughts not only have a serious impact on the agriculture, water resources, ecology, natural environment, but also seriously affect the socio-economic such as human health, energy and transportation. Worsely, under the background of climate change, droughts in show increases in frequency, duration and scope in many places around the world, particularly northern China. Nowadays, droughts have aroused extensive concern of the scientists, governments and international community, and became one of the important scientific issues in geoscience research. However, most of researches on droughts in China so far were focused on the causes or regulars of one type of droughts (the atmosphere, agriculture or hydrological) from the perspective of the atmospheric circulation anomalies. Few of them considered a whole cycle of the drought-forming process from atmosphere-land interaction to agricultural/ecological one in terms of the land-atmosphere interaction; meanwhile, the feedback mechanism with the drought and land-atmosphere interaction is still unclear as well. All of them is because of lack of the relevant comprehensive observation experiment. "Land-atmosphere interaction and disaster-causing process of drought in northern China: observation and experiment" (DroughtPEX_China)is just launched in this requirement and background. DroughtPEX_China is supported by Special Scientific Research Fund of Public Welfare Industry (Meteorological) of China (Grant No.GYHY201506001)—"Drought Meteorology Scientific Research Project—the disaster-causing process and mechanism of drought in northern China". This project aims to establish a complete observation &experiment system for droughts particularly over the arid and semi-arid regions in northern China. Relying on the existing meteorological observation network and experimental bases, the DroughtPEX_China implemented interdisciplinary, comprehensive and systemic drought-scientific experiment including the routine observation, intensive and special observation, and the artificially field control test for the drought forming and reducing. Such large observation &experiment will promote a large step or theoretical breakthrough on the knowledge of the complex dynamic process for the formation and development of drought disasters, the mechanism of the water-energy cycle in the atmosphere-soil-vegetation on multi-scales, and the interrelationship in the atmosphere, agriculture and hydrological droughts. The ultimate purpose of DroughtPEX_China is to make great progress on the technology of accurate drought monitoring, risk assessment and early warning. This paper will introduce the Drought PEX_China with the scientific goal, experiment design and layout, preliminary results, information sharing, and its promoting role on international cooperation of drought scientific research. Key words: Disaster-causing process of drought; Observation & experiment; Northern China

Uncertainty in solid precipitation and snow depth prediction for Siberia using the Noah and Noah-MP land surface models

NASA Astrophysics Data System (ADS)

Suzuki, Kazuyoshi; Zupanski, Milija

2018-01-01

In this study, we investigate the uncertainties associated with land surface processes in an ensemble predication context. Specifically, we compare the uncertainties produced by a coupled atmosphere-land modeling system with two different land surface models, the Noah- MP land surface model (LSM) and the Noah LSM, by using the Maximum Likelihood Ensemble Filter (MLEF) data assimilation system as a platform for ensemble prediction. We carried out 24-hour prediction simulations in Siberia with 32 ensemble members beginning at 00:00 UTC on 5 March 2013. We then compared the model prediction uncertainty of snow depth and solid precipitation with observation-based research products and evaluated the standard deviation of the ensemble spread. The prediction skill and ensemble spread exhibited high positive correlation for both LSMs, indicating a realistic uncertainty estimation. The inclusion of a multiple snowlayer model in the Noah-MP LSM was beneficial for reducing the uncertainties of snow depth and snow depth change compared to the Noah LSM, but the uncertainty in daily solid precipitation showed minimal difference between the two LSMs. The impact of LSM choice in reducing temperature uncertainty was limited to surface layers of the atmosphere. In summary, we found that the more sophisticated Noah-MP LSM reduces uncertainties associated with land surface processes compared to the Noah LSM. Thus, using prediction models with improved skill implies improved predictability and greater certainty of prediction.

Built-Up Area and Land Cover Extraction Using High Resolution Pleiades Satellite Imagery for Midrand, in Gauteng Province, South Africa

NASA Astrophysics Data System (ADS)

Fundisi, E.; Musakwa, W.

2017-09-01

Urban areas, particularly in developing countries face immense challenges such as climate change, poverty, lack of resources poor land use management systems, and week environmental management practices. Mitigating against these challenges is often hampered by lack of data on urban expansion, urban footprint and land cover. To support the recently adopted new urban agenda 2030 there is need for the provision of information to support decision making in the urban areas. Earth observation has been identified as a tool to foster sustainable urban planning and smarter cities as recognized by the new urban agenda, because it is a solution to unavailability of data. Accordingly, this study uses high resolution EO data Pleiades satellite imagery to map and document land cover for the rapidly expanding area of Midrand in Johannesburg, South Africa. An unsupervised land cover classification of the Pleiades satellite imagery was carried out using ENVI software, whereas NDVI was derived using ArcGIS software. The land cover had an accuracy of 85% that is highly adequate to document the land cover in Midrand. The results are useful because it provides a highly accurate land cover and NDVI datasets at localised spatial scale that can be used to support land use management strategies within Midrand and the City of Johannesburg South Africa.

Catchment land use-dependent effects of barrage fishponds on the functioning of headwater streams.

PubMed

Four, Brian; Arce, Evelyne; Danger, Michaël; Gaillard, Juliette; Thomas, Marielle; Banas, Damien

2017-02-01

Extensive fish production systems in continental areas are often created by damming headwater streams. However, these lentic systems favour autochthonous organic matter production. As headwater stream functioning is essentially based on allochthonous organic matter (OM) supply, the presence of barrage fishponds on headwater streams might change the main food source for benthic communities. The goal of this study was thus to identify the effects of barrage fishponds on the functioning of headwater streams. To this end, we compared leaf litter breakdown (a key ecosystem function in headwater streams), their associated invertebrate communities and fungal biomass at sites upstream and downstream of five barrage fishponds in two dominant land use systems (three in forested catchments and two in agricultural catchments). We observed significant structural and functional differences between headwater stream ecosystems in agricultural catchments and those in forested catchments. Leaf litter decay was more rapid in forest streams, with a moderate, but not significant, increase in breakdown rate downstream from the barrage fishponds. In agricultural catchments, the trend was opposite with a 2-fold lower leaf litter breakdown rate at downstream sites compared to upstream sites. Breakdown rates observed at all sites were closely correlated with fungal biomass and shredder biomass. No effect of barrage fishponds were observed in this study concerning invertebrate community structure or functional feeding groups especially in agricultural landscapes. In forest streams, we observed a decrease in organic pollution (OP)-intolerant taxa at downstream sites that was correlated with an increase in OP-tolerant taxa. These results highlighted that the influence of barrage fishponds on headwater stream functioning is complex and land use dependent. It is therefore necessary to clearly understand the various mechanisms (competition for food resources, complementarities between autochthonous and allochthonous OM) that control ecosystem functioning in different contexts in order to optimize barrage fishpond management.

Using Flux Site Observations to Calibrate Root System Architecture Stencils for Water Uptake of Plant Functional Types in Land Surface Models.

NASA Astrophysics Data System (ADS)

Bouda, M.

2017-12-01

Root system architecture (RSA) can significantly affect plant access to water, total transpiration, as well as its partitioning by soil depth, with implications for surface heat, water, and carbon budgets. Despite recent advances in land surface model (LSM) descriptions of plant hydraulics, RSA has not been included because of its three-dimensional complexity, which makes RSA modelling generally too computationally costly. This work builds upon the recently introduced "RSA stencil," a process-based 1D layered model that captures the dynamic shifts in water potential gradients of 3D RSA in response to heterogeneous soil moisture profiles. In validations using root systems calibrated to the rooting profiles of four plant functional types (PFT) of the Community Land Model, the RSA stencil predicts plant water potentials within 2% of the outputs of full 3D models, despite its trivial computational cost. In transient simulations, the RSA stencil yields improved predictions of water uptake and soil moisture profiles compared to a 1D model based on root fraction alone. Here I show how the RSA stencil can be calibrated to time-series observations of soil moisture and transpiration to yield a water uptake PFT definition for use in terrestrial models. This model-data integration exercise aims to improve LSM predictions of soil moisture dynamics and, under water-limiting conditions, surface fluxes. These improvements can be expected to significantly impact predictions of downstream variables, including surface fluxes, climate-vegetation feedbacks and soil nutrient cycling.

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.

Disagreement between Hydrological and Land Surface models on the water budgets in the Arctic: why is this and which of them is right?

NASA Astrophysics Data System (ADS)

Blyth, E.; Martinez-de la Torre, A.; Ellis, R.; Robinson, E.

2017-12-01

The fresh-water budget of the Artic region has a diverse range of impacts: the ecosystems of the region, ocean circulation response to Arctic freshwater, methane emissions through changing wetland extent as well as the available fresh water for human consumption. But there are many processes that control the budget including a seasonal snow packs building and thawing, freezing soils and permafrost, extensive organic soils and large wetland systems. All these processes interact to create a complex hydrological system. In this study we examine a suite of 10 models that bring all those processes together in a 25 year reanalysis of the global water budget. We assess their performance in the Arctic region. There are two approaches to modelling fresh-water flows at large scales, referred to here as `Hydrological' and `Land Surface' models. While both approaches include a physically based model of the water stores and fluxes, the Land Surface models links the water flows to an energy-based model for processes such as snow melt and soil freezing. This study will analyse the impact of that basic difference on the regional patterns of evapotranspiration, runoff generation and terrestrial water storage. For the evapotranspiration, the Hydrological models tend to have a bigger spatial range in the model bias (difference to observations), implying greater errors compared to the Land-Surface models. For instance, some regions such as Eastern Siberia have consistently lower Evaporation in the Hydrological models than the Land Surface models. For the Runoff however, the results are the other way round with a slightly higher spatial range in bias for the Land Surface models implying greater errors than the Hydrological models. A simple analysis would suggest that Hydrological models are designed to get the runoff right, while Land Surface models designed to get the evapotranspiration right. Tracing the source of the difference suggests that the difference comes from the treatment of snow and evapotranspiration. The study reveals that expertise in the role of snow on runoff generation and evapotranspiration in Hydrological and Land Surface could be combined to improve the representation of the fresh water flows in the Arctic in both approaches. Improved observations are essential to make these modelling advances possible.

Soil frost-induced soil moisture precipitation feedback and effects on atmospheric states

NASA Astrophysics Data System (ADS)

Hagemann, Stefan; Blome, Tanja; Ekici, Altug; Beer, Christian

2016-04-01

Permafrost or perennially frozen ground is an important part of the terrestrial cryosphere; roughly one quarter of Earth's land surface is underlain by permafrost. As it is a thermal phenomenon, its characteristics are highly dependent on climatic factors. The impact of the currently observed warming, which is projected to persist during the coming decades due to anthropogenic CO2 input, certainly has effects for the vast permafrost areas of the high northern latitudes. The quantification of these effects, however, is scientifically still an open question. This is partly due to the complexity of the system, where several feedbacks are interacting between land and atmosphere, sometimes counterbalancing each other. Moreover, until recently, many global circulation models (GCMs) and Earth system models (ESMs) lacked the sufficient representation of permafrost physics in their land surface schemes. Within the European Union FP7 project PAGE21, the land surface scheme JSBACH of the Max-Planck-Institute for Meteorology ESM (MPI-ESM) has been equipped with the representation of relevant physical processes for permafrost studies. These processes include the effects of freezing and thawing of soil water for both energy and water cycles, thermal properties depending on soil water and ice contents, and soil moisture movement being influenced by the presence of soil ice. In the present study, it will be analysed how these permafrost relevant processes impact large-scale hydrology and climate over northern hemisphere high latitude land areas. For this analysis, the atmosphere-land part of MPI-ESM, ECHAM6-JSBACH, is driven by prescribed observed SST and sea ice in an AMIP2-type setup with and without the newly implemented permafrost processes. Results show a large improvement in the simulated discharge. On one hand this is related to an improved snowmelt peak of runoff due to frozen soil in spring. On the other hand a subsequent reduction of soil moisture leads to a positive land atmosphere feedback to precipitation over the high latitudes, which reduces the model's wet biases in precipitation and evapotranspiration during the summer. This is noteworthy as soil moisture - atmosphere feedbacks have previously not been in the research focus over the high latitudes. These results point out the importance of high latitude physical processes at the land surface for the regional climate.

KSC-98pc775

NASA Image and Video Library

1998-06-25

KENNEDY SPACE CENTER, FLA. -- NASA's Huey UH-1 helicopter lands at the Shuttle Landing Facility to pick up Kennedy Space Center (KSC) Security personnel who operate the Forward Looking Infrared Radar (FLIR) installed on board. The helicopter has also been outfitted with a portable global positioning satellite (GPS) system to support Florida's Division of Forestry as they fight the brush fires which have been plaguing the state as a result of extremely dry conditions and lightning storms. The FLIR includes a beach ball-sized infrared camera that is mounted on the helicopter's right siderail and a real-time television monitor and recorder installed inside. While the FLIR collects temperature data and images, the GPS system provides the exact coordinates of the fires being observed and transmits the data to the firefighters on the ground. KSC's security team routinely uses the FLIR equipment prior to Shuttle launch and landing activities to ensure that the area surrounding the launch pad and runway are clear of unauthorized personnel. KSC's Base Operations Contractor, EG&G Florida, operates the NASA-owned helicopter

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 physical environment and health-enhancing activity during the school commute: global positioning system, geographical information systems and accelerometry.

PubMed

McMinn, David; Oreskovic, Nicolas M; Aitkenhead, Matt J; Johnston, Derek W; Murtagh, Shemane; Rowe, David A

2014-05-01

Active school travel is in decline. An understanding of the potential determinants of health-enhancing physical activity during the school commute may help to inform interventions aimed at reversing these trends. The purpose of this study was to identify the physical environmental factors associated with health-enhancing physical activity during the school commute. Data were collected in 2009 on 166 children commuting home from school in Scotland. Data on location and physical activity were measured using global positioning systems (GPS) and accelerometers, and mapped using geographical information systems (GIS). Multi-level logistic regression models accounting for repeated observations within participants were used to test for associations between each land-use category (road/track/path, other man-made, greenspace, other natural) and moderate-to-vigorous physical activity (MVPA). Thirty-nine children provided 2,782 matched data points. Over one third (37.1%) of children's school commute time was spent in MVPA. Children commuted approximately equal amounts of time via natural and man-made land-uses (50.2% and 49.8% respectively). Commuting via road/track/path was associated with increased likelihood of MVPA (Exp(B)=1.23, P <0.05), but this association was not seen for commuting via other manmade land-uses. No association was noted between greenspace use and MVPA, but travelling via other natural land-uses was associated with lower odds of MVPA (Exp(B)=0.32, P <0.05). Children spend equal amounts of time commuting to school via man-made and natural land-uses, yet man-made transportation route infrastructure appears to provide greater opportunities for achieving health-enhancing physical activity levels.

Mapping palm oil expansion using SAR to study the impact on the CO2 cycle

NASA Astrophysics Data System (ADS)

Pohl, Christine

2014-06-01

With Malaysia being the second largest palm oil producer in the world and the fact that palm oil ranks first in vegetable oil production on the world market the palm oil industry became an important factor in the country. Along with the expansion of palm oil across the nation causing deforestation of natural rain forest and conversion of peat land into plantation land there are several factors causing a tremendous increase in carbon dioxide (CO2) emissions. Main causes of CO2 emission apart from deforestation and peat-land conversion are the fires to create plantation land plus the fires burning waste products of the plantations itself. This paper describes a project that aims at the development of a remote sensing monitoring system to allow a continuous observation of oil palm plantation activities and expansion in order to be able to quantify CO2 emissions. The research concentrates on developing a spaceborne synthetic aperture radar information extraction system for palm oil plantations in the Tropics. This will lead to objective figures that can be used internationally to create a policy implementation plan to sustainably reduce CO2 emission in the future.

Seasonal-scale Observational Data Analysis and Atmospheric Phenomenology for the Cold Land Processes Experiment

NASA Technical Reports Server (NTRS)

Poulos, Gregory S.; Stamus, Peter A.; Snook, John S.

2005-01-01

The Cold Land Processes Experiment (CLPX) experiment emphasized the development of a strong synergism between process-oriented understanding, land surface models and microwave remote sensing. Our work sought to investigate which topographically- generated atmospheric phenomena are most relevant to the CLPX MSA's for the purpose of evaluating their climatic importance to net local moisture fluxes and snow transport through the use of high-resolution data assimilation/atmospheric numerical modeling techniques. Our task was to create three long-term, scientific quality atmospheric datasets for quantitative analysis (for all CLPX researchers) and provide a summary of the meteorologically-relevant phenomena of the three MSAs (see Figure) over northern Colorado. Our efforts required the ingest of a variety of CLPX datasets and the execution an atmospheric and land surface data assimilation system based on the Navier-Stokes equations (the Local Analysis and Prediction System, LAPS, and an atmospheric numerical weather prediction model, as required) at topographically- relevant grid spacing (approx. 500 m). The resulting dataset will be analyzed by the CLPX community as a part of their larger research goals to determine the relative influence of various atmospheric phenomena on processes relevant to CLPX scientific goals.

Predictability of Malaria Transmission Intensity in the Mpumalanga Province, South Africa, Using Land Surface Climatology and Autoregressive Analysis

NASA Technical Reports Server (NTRS)

Grass, David; Jasinski, Michael F.; Govere, John

2003-01-01

There has been increasing effort in recent years to employ satellite remotely sensed data to identify and map vector habitat and malaria transmission risk in data sparse environments. In the current investigation, available satellite and other land surface climatology data products are employed in short-term forecasting of infection rates in the Mpumalanga Province of South Africa, using a multivariate autoregressive approach. The climatology variables include precipitation, air temperature and other land surface states computed by the Off-line Land-Surface Global Assimilation System (OLGA) including soil moisture and surface evaporation. Satellite data products include the Normalized Difference Vegetation Index (NDVI) and other forcing data used in the Goddard Earth Observing System (GEOS-1) model. Predictions are compared to long- term monthly records of clinical and microscopic diagnoses. The approach addresses the high degree of short-term autocorrelation in the disease and weather time series. The resulting model is able to predict 11 of the 13 months that were classified as high risk during the validation period, indicating the utility of applying antecedent climatic variables to the prediction of malaria incidence for the Mpumalanga Province.

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.

Documentation and Validation of the Goddard Earth Observing System (GEOS) Data Assimilation System, Version 4

NASA Technical Reports Server (NTRS)

Suarez, Max J. (Editor); daSilva, Arlindo; Dee, Dick; Bloom, Stephen; Bosilovich, Michael; Pawson, Steven; Schubert, Siegfried; Wu, Man-Li; Sienkiewicz, Meta; Stajner, Ivanka

2005-01-01

This document describes the structure and validation of a frozen version of the Goddard Earth Observing System Data Assimilation System (GEOS DAS): GEOS-4.0.3. Significant features of GEOS-4 include: version 3 of the Community Climate Model (CCM3) with the addition of a finite volume dynamical core; version two of the Community Land Model (CLM2); the Physical-space Statistical Analysis System (PSAS); and an interactive retrieval system (iRET) for assimilating TOVS radiance data. Upon completion of the GEOS-4 validation in December 2003, GEOS-4 became operational on 15 January 2004. Products from GEOS-4 have been used in supporting field campaigns and for reprocessing several years of data for CERES.

Using NASA Remote Sensing Data to Reduce Uncertainty of Land-use Transitions in Global Carbon-Climate Models

NASA Astrophysics Data System (ADS)

Chini, L. P.; Hurtt, G. C.; Frolking, S. E.; Sahajpal, R.; Potapov, P.; Hansen, M.; Fisk, J.

2016-12-01

For the 5th IPCC Assessment almost all Earth System Models (ESMs) incorporated new gridded products of land-use and land-use change that were harmonized to ensure a continuous transition from historical to future data in a consistent format for all models. However, these Land-Use Harmonization (LUH) data products are estimates, constrained with data where available, and with modeling assumptions, and the remaining challenge is to quantify, and reduce, the uncertainty in these products. At the same time, satellite remote sensing of the terrestrial biosphere has also evolved. Global-scale land cover extent and change monitoring is now possible given systematically acquired earth observation data sets, advanced characterization algorithms and data intensive computing capabilities. Here we consider: how can satellite remote sensing products be used to generate (and reduce uncertainty in) new gridded maps of land-use transitions for use in coupled carbon-climate simulations? As part of the international effort to develop the next generation of land-use datasets (LUH2), new NASA remote-sensing-based maps of global forest extent and change (Hansen et al. 2013) were used as both an added constraint and diagnostic in the LUH process. Harmonizing this remote sensing data with the LUH data was a major computational challenge involving 143 billion 30m Landsat pixels, and the simulation of over 20 billion LUH unknowns. Our approach involved first harmonizing the definitions of forest loss between the observed and simulated data for the years 2000-2012. Next, new spatial patterns of historical wood harvest were calculated to match the observed forest loss transitions while simultaneously meeting all other constraints of the model, and ensuring consistency throughout the historical time-period. After reconciling definitions and developing new wood harvest patterns the LUH2 global forest loss for the period 2000-2012 was reduced from over 8.3 million km2 to 1.78 million km2 (compared with the remote-sensing-based forest loss of 2.03 million km2). Next steps are to evaluate the ability of these land-use transitions to improve the representation of land-use-related climate forcings in ESM experiments, and to then build upon the LUH framework to incorporate additional remote-sensing data constraints.

Evolution of Indian land surface biases in the seasonal hindcasts from the Met Office Global Seasonal Forecasting System GloSea5

NASA Astrophysics Data System (ADS)

Chevuturi, Amulya; Turner, Andrew G.; Woolnoug, Steve J.; Martin, Gill

2017-04-01

In this study we investigate the development of biases over the Indian region in summer hindcasts of the UK Met Office coupled initialised global seasonal forecasting system, GloSea5-GC2. Previous work has demonstrated the rapid evolution of strong monsoon circulation biases over India from seasonal forecasts initialised in early May, together with coupled strong easterly wind biases on the equator. These mean state biases lead to strong precipitation errors during the monsoon over the subcontinent. We analyse a set of three springtime start dates for the 20-year hindcast period (1992-2011) and fifteen total ensemble members for each year. We use comparisons with variety of observations to assess the evolution of the mean state biases over the Indian land surface. All biases within the model develop rapidly, particularly surface heat and radiation flux biases. Strong biases are present within the model climatology from pre-monsoon (May) in the surface heat fluxes over India (higher sensible / lower latent heat fluxes) when compared to observed estimates. The early evolution of such biases prior to onset rains suggests possible problems with the land surface scheme or soil moisture errors. Further analysis of soil moisture over the Indian land surface shows a dry bias present from the beginning of the hindcasts during the pre-monsoon. This lasts until the after the monsoon develops (July) after which there is a wet bias over the region. Soil moisture used for initialization of the model also shows a dry bias when compared against the observed estimates, which may lead to the same in the model. The early dry bias in the model may reduce local moisture availability through surface evaporation and thus may possibly limit precipitation recycling. On this premise, we identify and test the sensitivity of the monsoon in the model against higher soil moisture forcing. We run sensitivity experiments initiated using gridpoint-wise annual soil moisture maxima over the Indian land surface as input for experiments in the atmosphere-only version of the model. We plan to analyse the response of the sensitivity experiments on seasonal forecasting of surface heat fluxes and subsequently monsoon precipitation.

Surface models of Mars, 1975

NASA Technical Reports Server (NTRS)

1975-01-01

Data derived from Mariners 6, 7, and 9, Russian Mars probes, and photographic and radar observations conducted from earth are used to develop engineering models of Martian surface properties. These models are used in mission planning and in the design of landing and exploration vehicles. Optical models needed in the design of camera systems, dielectric properties needed in the design of radar systems, and thermal properties needed in the design of the spacecraft thermal control system are included.

A small-scale land-sparing approach to conserving biological diversity in tropical agricultural landscapes.

PubMed

Chandler, Richard B; King, David I; Raudales, Raul; Trubey, Richard; Chandler, Carlin; Chávez, Víctor Julio Arce

2013-08-01

Two contrasting strategies have been proposed for conserving biological diversity while meeting the increasing demand for agricultural products: land sparing and land sharing production systems. Land sparing involves increasing yield to reduce the amount of land needed for agriculture, whereas land-sharing agricultural practices incorporate elements of native ecosystems into the production system itself. Although the conservation value of these systems has been extensively debated, empirical studies are lacking. We compared bird communities in shade coffee, a widely practiced land-sharing system in which shade trees are maintained within the coffee plantation, with bird communities in a novel, small-scale, land-sparing coffee-production system (integrated open canopy or IOC coffee) in which farmers obtain higher yields under little or no shade while conserving an area of forest equal to the area under cultivation. Species richness and diversity of forest-dependent birds were higher in the IOC coffee farms than in the shade coffee farms, and community composition was more similar between IOC coffee and primary forest than between shade coffee and primary forest. Our study represents the first empirical comparison of well-defined land sparing and land sharing production systems. Because IOC coffee farms can be established by allowing forest to regenerate on degraded land, widespread adoption of this system could lead to substantial increases in forest cover and carbon sequestration without compromising agricultural yield or threatening the livelihoods of traditional small farmers. However, we studied small farms (<5 ha); thus, our results may not generalize to large-scale land-sharing systems. Furthermore, rather than concluding that land sparing is generally superior to land sharing, we suggest that the optimal approach depends on the crop, local climate, and existing land-use patterns. © 2013 Society for Conservation Biology.

Land-Breeze Forecasting

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; Wheeler, Mark M.; Merceret, Francis J. (Technical Monitor)

2002-01-01

The nocturnal land breeze at the Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) is both operationally significant and challenging to forecast. The occurrence and timing of land breezes impact low-level winds, atmospheric stability, low temperatures, and fog development. Accurate predictions of the land breeze are critical for toxic material dispersion forecasts associated with space launch missions, since wind direction and low-level stability can change noticeably with the onset of a land breeze. This report presents a seven-year observational study of land breezes over east-central Florida from 1995 to 2001. This comprehensive analysis was enabled by the high-resolution tower observations over KSC/CCAFS. Five-minute observations of winds, temperature, and moisture along with 9 15-MHz Doppler Radar Wind Profiler data were used to analyze specific land-breeze cases, while the tower data were used to construct a composite climatology. Utilities derived from this climatology were developed to assist forecasters in determining the land-breeze occurrence, timing, and movement based on predicted meteorological conditions.

Distinct Soil Bacterial Communities Revealed under a Diversely Managed Agroecosystem

PubMed Central

Shange, Raymon S.; Ankumah, Ramble O.; Ibekwe, Abasiofiok M.; Zabawa, Robert; Dowd, Scot E.

2012-01-01

Land-use change and management practices are normally enacted to manipulate environments to improve conditions that relate to production, remediation, and accommodation. However, their effect on the soil microbial community and their subsequent influence on soil function is still difficult to quantify. Recent applications of molecular techniques to soil biology, especially the use of 16S rRNA, are helping to bridge this gap. In this study, the influence of three land-use systems within a demonstration farm were evaluated with a view to further understand how these practices may impact observed soil bacterial communities. Replicate soil samples collected from the three land-use systems (grazed pine forest, cultivated crop, and grazed pasture) on a single soil type. High throughput 16S rRNA gene pyrosequencing was used to generate sequence datasets. The different land use systems showed distinction in the structure of their bacterial communities with respect to the differences detected in cluster analysis as well as diversity indices. Specific taxa, particularly Actinobacteria, Acidobacteria, and classes of Proteobacteria, showed significant shifts across the land-use strata. Families belonging to these taxa broke with notions of copio- and oligotrphy at the class level, as many of the less abundant groups of families of Actinobacteria showed a propensity for soil environments with reduced carbon/nutrient availability. Orders Actinomycetales and Solirubrobacterales showed their highest abundance in the heavily disturbed cultivated system despite the lowest soil organic carbon (SOC) values across the site. Selected soil properties ([SOC], total nitrogen [TN], soil texture, phosphodiesterase [PD], alkaline phosphatase [APA], acid phosphatase [ACP] activity, and pH) also differed significantly across land-use regimes, with SOM, PD, and pH showing variation consistent with shifts in community structure and composition. These results suggest that use of pyrosequencing along with traditional analysis of soil physiochemical properties may provide insight into the ecology of descending taxonomic groups in bacterial communities. PMID:22844402

Distinct soil bacterial communities revealed under a diversely managed agroecosystem.

PubMed

Shange, Raymon S; Ankumah, Ramble O; Ibekwe, Abasiofiok M; Zabawa, Robert; Dowd, Scot E

2012-01-01

Land-use change and management practices are normally enacted to manipulate environments to improve conditions that relate to production, remediation, and accommodation. However, their effect on the soil microbial community and their subsequent influence on soil function is still difficult to quantify. Recent applications of molecular techniques to soil biology, especially the use of 16S rRNA, are helping to bridge this gap. In this study, the influence of three land-use systems within a demonstration farm were evaluated with a view to further understand how these practices may impact observed soil bacterial communities. Replicate soil samples collected from the three land-use systems (grazed pine forest, cultivated crop, and grazed pasture) on a single soil type. High throughput 16S rRNA gene pyrosequencing was used to generate sequence datasets. The different land use systems showed distinction in the structure of their bacterial communities with respect to the differences detected in cluster analysis as well as diversity indices. Specific taxa, particularly Actinobacteria, Acidobacteria, and classes of Proteobacteria, showed significant shifts across the land-use strata. Families belonging to these taxa broke with notions of copio- and oligotrphy at the class level, as many of the less abundant groups of families of Actinobacteria showed a propensity for soil environments with reduced carbon/nutrient availability. Orders Actinomycetales and Solirubrobacterales showed their highest abundance in the heavily disturbed cultivated system despite the lowest soil organic carbon (SOC) values across the site. Selected soil properties ([SOC], total nitrogen [TN], soil texture, phosphodiesterase [PD], alkaline phosphatase [APA], acid phosphatase [ACP] activity, and pH) also differed significantly across land-use regimes, with SOM, PD, and pH showing variation consistent with shifts in community structure and composition. These results suggest that use of pyrosequencing along with traditional analysis of soil physiochemical properties may provide insight into the ecology of descending taxonomic groups in bacterial communities.

Land, Cryosphere, and Nighttime Environmental Products from Suomi NPP VIIRS: Overview and Status

NASA Technical Reports Server (NTRS)

Roman, Miguel O.; Justice, Chris; Csiszar, Ivan

2014-01-01

The Visible Infrared Imaging Radiometer Suite (VIIRS) instrument was launched in October 2011 as part of the Suomi National Polar-orbiting Partnership (S-NPP: http://npp.gsfc.nasa.gov/). VIIRS was designed to improve upon the capabilities of the operational Advanced Very High Resolution Radiometer (AVHRR) and provide observation continuity with NASA's Earth Observing System's (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS). Since the VIIRS first-light images were received in November 2011, NASA and NOAA funded scientists have been working to evaluate the instrument performance and derived products to meet the needs of the NOAA operational users and the NASA science community. NOAA's focus has been on refining a suite of operational products known as Environmental Data Records (EDRs), which were developed according to project specifications under the former National Polar-orbiting Environmental Satellite System (NPOESS). The NASA S-NPP Science Team has focused on evaluating the EDRs for science use, developing and testing additional products to meet science data needs and providing MODIS data product continuity. This paper will present to-date findings of the NASA Science Team's evaluation of the VIIRS Land and Cryosphere EDRs, specifically Surface Reflectance, Land Surface Temperature, Surface Albedo, Vegetation Indices, Surface Type, Active Fires, Snow Cover, Ice Surface Temperature, and Sea Ice Characterization (http://viirsland.gsfc.nasa.gov/index.html). The paper will also discuss new capabilities being developed at NASA's Land Product Evaluation and Test Element (http://landweb.nascom.nasa.gov/NPP_QA/); including downstream data and products derived from the VIIRS Day/Night Band (DNB).

Linking land use changes to surface water quality variability in Lake Victoria: some insights from remote sensing

NASA Astrophysics Data System (ADS)

Mugo, R. M.; Limaye, A. S.; Nyaga, J. W.; Farah, H.; Wahome, A.; Flores, A.

2016-12-01

The water quality of inland lakes is largely influenced by land use and land cover changes within the lake's catchment. In Africa, some of the major land use changes are driven by a number of factors, which include urbanization, intensification of agricultural practices, unsustainable farm management practices, deforestation, land fragmentation and degradation. Often, the impacts of these factors are observable on changes in the land cover, and eventually in the hydrological systems. When the natural vegetation cover is reduced or changed, the surface water flow patterns, water and nutrient retention capacities are also changed. This can lead to high nutrient inputs into lakes, leading to eutrophication, siltation and infestation of floating aquatic vegetation. To assess the relationship between land use and land cover changes in part of the Lake Victoria Basin, a series of land cover maps were derived from Landsat imagery. Changes in land cover were identified through change maps and statistics. Further, the surface water chlorophyll-a concentration and turbidity were derived from MODIS-Aqua data for Lake Victoria. Chlrophyll-a and turbidity are good proxy indicators of nutrient inputs and siltation respectively. The trends in chlorophyll-a and turbidity concentrations were analyzed and compared to the land cover changes over time. Certain land cover changes related to agriculture and urban development were clearly identifiable. While these changes might not be solely responsible for variability in chlrophyll-a and turbidity concentrations in the lake, they are potentially contributing factors to this problem. This work illustrates the importance of addressing watershed degradation while seeking to solve water quality related problems.

Land-use planning of Volyn region (Ukraine) using Geographic Information Systems (GIS) technologies

NASA Astrophysics Data System (ADS)

Strielko, Irina; Pereira, Paulo

2014-05-01

Land-use development planning is carried out in order to create a favourable environment for human life, sustainable socioeconomic and spatial development. Landscape planning is an important part of land-use development that aims to meet the fundamental principles of sustainable development. Geographic Information Systems (GIS) is a fundamental tool to make a better landscape planning at different territorial levels, providing data and maps to support decision making. The objective of this work is to create spatio-temporal, territorial and ecological model of development of Volyn region (Ukraine). It is based on existing spatial raster and vector data and includes the analysis of territory dynamics as the aspects responsible for it. A spatial analyst tool was used to zone the areas according to their environmental components and economic activity. This analysis is fundamental to define the basic parameters of sustainability of Volyn region. To carry out this analysis, we determined the demographic capacity of districts and the analysis of spatial parameters of land use. On the basis of the existing natural resources, we observed that there is a need of landscape protection and integration of more are natural areas in the Pan-European Ecological Network. Using GIS technologies to landscape planning in Volyn region, allowed us to identify, natural areas of interest, contribute to a better resource management and conflict resolution. Geographic Information Systems will help to formulate and implement landscape policies, reform the existing administrative system of Volyn region and contribute to a better sustainable development.

Side-to-side differences in lower extremity biomechanics during multi-directional jump landing in volleyball athletes.

PubMed

Sinsurin, Komsak; Srisangboriboon, Sarun; Vachalathiti, Roongtiwa

2017-07-01

Side-to-side differences of lower extremities may influence the likelihood of injury. Moreover, adding the complexity of jump-landing direction would help to explain lower extremity control during sport activities. The aim was to determine the effects of limb dominance and jump-landing direction on lower extremity biomechanics. Nineteen female volleyball athletes participated. Both dominant limbs (DLs) and non-dominant limbs (NLs) were examined in single-leg jump-landing tests in four directions, including forward (0°), diagonal (30° and 60°), and lateral (90°) directions. Kinematic marker trajectories and ground reaction forces were collected using a 10 camera Vicon system and an AMTI force plate. Repeated measures ANOVA (2 × 4, limb × direction) was used to analyse. The finding showed that, at peak vertical GRF, a significant interaction of limb dominance and direction effects was found in the hip flexion angle and lower extremity joint kinetics (p < .05). NLs and DLs exhibited significantly different strategies while landing in various directions. Significantly higher increase of ankle dorsiflexion angle was observed in lateral direction compared to other directions for both DLs and NLs (p < .05). Increasingly using ankle dorsiflexion was observed from the forward to the lateral direction for both DLs and NLs. However, NLs and DLs preferentially used different strategies of joint moment organization to respond to similar VGRFs in various directions. The response pattern of DLs might not be effective and may expose DLs to a higher injury risk, especially with regard to landing with awkward posture compared with NLs.

The Potential of Time Series Based Earth Observation for the Monitoring of Large River Deltas

NASA Astrophysics Data System (ADS)

Kuenzer, C.; Leinenkugel, P.; Huth, J.; Ottinger, M.; Renaud, F.; Foufoula-Georgiou, E.; Vo Khac, T.; Trinh Thi, L.; Dech, S.; Koch, P.; Le Tissier, M.

2015-12-01

Although river deltas only contribute 5% to the overall land surface, nearly six hundred million people live in these complex social-ecological environments, which combine a variety of appealing locational advantages. In many countries deltas provide the major national contribution to agricultural and industrial production. At the same time these already very dynamic environments are exposed to a variety of threats, including the disturbance and replacement of valuable ecosystems, increasing water, soil, and air pollution, human induced land subsidence, sea level rise, as well upstream developments impacting water and sediment supplies. A constant monitoring of delta systems is thus of utmost relevance for understanding past and current land surface change and anticipating possible future developments. We present the potential of Earth Observation based analyses and derived novel information products that can play a key role in this context. Along with the current trend of opening up numerous satellite data archives go increasing capabilities to explore big data. Whereas in past decades remote sensing data were analysed based on the spectral-reflectance-defined 'finger print' of individual surfaces, we mainly exploit the 'temporal fingerprints' of our land surface in novel pathways of data analyses at differing spatial-, and temporally-dense scales. Following our results on an Earth Observation based characterization of large deltas globally, we present in depth results from the Mekong Delta in Vietnam, the Yellow River Delta in China, the Niger Delta in Nigeria, as well as additional deltas, focussing on the assessment of river delta flood and inundation dynamics, river delta coastline dynamics, delta morphology dynamics including the quantification of erosion and accretion processes, river delta land use change and trends, as well as the monitoring of compliance to environmental regulations.

Global Gross Primary Productivity for 2015 Inferred from OCO-2 SIF and a Carbon-Cycle Data Assimilation System

NASA Astrophysics Data System (ADS)

Norton, A.; Rayner, P. J.; Scholze, M.; Koffi, E. N. D.

2016-12-01

The intercomparison study CMIP5 among other studies (e.g. Bodman et al., 2013) has shown that the land carbon flux contributes significantly to the uncertainty in projections of future CO2 concentration and climate (Friedlingstein et al., 2014)). The main challenge lies in disaggregating the relatively well-known net land carbon flux into its component fluxes, gross primary production (GPP) and respiration. Model simulations of these processes disagree considerably, and accurate observations of photosynthetic activity have proved a hindrance. Here we build upon the Carbon Cycle Data Assimilation System (CCDAS) (Rayner et al., 2005) to constrain estimates of one of these uncertain fluxes, GPP, using satellite observations of Solar Induced Fluorescence (SIF). SIF has considerable benefits over other proxy observations as it tracks not just the presence of vegetation but actual photosynthetic activity (Walther et al., 2016; Yang et al., 2015). To combine these observations with process-based simulations of GPP we have coupled the model SCOPE with the CCDAS model BETHY. This provides a mechanistic relationship between SIF and GPP, and the means to constrain the processes relevant to SIF and GPP via model parameters in a data assimilation system. We ingest SIF observations from NASA's Orbiting Carbon Observatory 2 (OCO-2) for 2015 into the data assimilation system to constrain estimates of GPP in space and time, while allowing for explicit consideration of uncertainties in parameters and observations. Here we present first results of the assimilation with SIF. Preliminary results indicate a constraint on global annual GPP of at least 75% when using SIF observations, reducing the uncertainty to < 3 PgC yr-1. A large portion of the constraint is propagated via parameters that describe leaf phenology. These results help to bring together state-of-the-art observations and model to improve understanding and predictive capability of GPP.

Coral Reef Surveillance: Infrared-Sensitive Video Surveillance Technology as a New Tool for Diurnal and Nocturnal Long-Term Field Observations.

PubMed

Dirnwoeber, Markus; Machan, Rudolf; Herler, Juergen

2012-10-31

Direct field observations of fine-scaled biological processes and interactions of the benthic community of corals and associated reef organisms (e.g., feeding, reproduction, mutualistic or agonistic behavior, behavioral responses to changing abiotic factors) usually involve a disturbing intervention. Modern digital camcorders (without inflexible land-or ship-based cable connection) such as the GoPro camera enable undisturbed and unmanned, stationary close-up observations. Such observations, however, are also very time-limited (~3 h) and full 24 h-recordings throughout day and night, including nocturnal observations without artificial daylight illumination, are not possible. Herein we introduce the application of modern standard video surveillance technology with the main objective of providing a tool for monitoring coral reef or other sessile and mobile organisms for periods of 24 h and longer. This system includes nocturnal close-up observations with miniature infrared (IR)-sensitive cameras and separate high-power IR-LEDs. Integrating this easy-to-set up and portable remote-sensing equipment into coral reef research is expected to significantly advance our understanding of fine-scaled biotic processes on coral reefs. Rare events and long-lasting processes can easily be recorded, in situ -experiments can be monitored live on land, and nocturnal IR-observations reveal undisturbed behavior. The options and equipment choices in IR-sensitive surveillance technology are numerous and subject to a steadily increasing technical supply and quality at decreasing prices. Accompanied by short video examples, this report introduces a radio-transmission system for simultaneous recordings and real-time monitoring of multiple cameras with synchronized timestamps, and a surface-independent underwater-recording system.

Coral Reef Surveillance: Infrared-Sensitive Video Surveillance Technology as a New Tool for Diurnal and Nocturnal Long-Term Field Observations

PubMed Central

Dirnwoeber, Markus; Machan, Rudolf; Herler, Juergen

2014-01-01

Direct field observations of fine-scaled biological processes and interactions of the benthic community of corals and associated reef organisms (e.g., feeding, reproduction, mutualistic or agonistic behavior, behavioral responses to changing abiotic factors) usually involve a disturbing intervention. Modern digital camcorders (without inflexible land-or ship-based cable connection) such as the GoPro camera enable undisturbed and unmanned, stationary close-up observations. Such observations, however, are also very time-limited (~3 h) and full 24 h-recordings throughout day and night, including nocturnal observations without artificial daylight illumination, are not possible. Herein we introduce the application of modern standard video surveillance technology with the main objective of providing a tool for monitoring coral reef or other sessile and mobile organisms for periods of 24 h and longer. This system includes nocturnal close-up observations with miniature infrared (IR)-sensitive cameras and separate high-power IR-LEDs. Integrating this easy-to-set up and portable remote-sensing equipment into coral reef research is expected to significantly advance our understanding of fine-scaled biotic processes on coral reefs. Rare events and long-lasting processes can easily be recorded, in situ-experiments can be monitored live on land, and nocturnal IR-observations reveal undisturbed behavior. The options and equipment choices in IR-sensitive surveillance technology are numerous and subject to a steadily increasing technical supply and quality at decreasing prices. Accompanied by short video examples, this report introduces a radio-transmission system for simultaneous recordings and real-time monitoring of multiple cameras with synchronized timestamps, and a surface-independent underwater-recording system. PMID:24829763

1993 Earth Observing System reference handbook

NASA Technical Reports Server (NTRS)

Asrar, Ghassem (Editor); Dokken, David Jon (Editor)

1993-01-01

Mission to Planet Earth (MTPE) is a NASA-sponsored concept that uses space- and ground-based measurement systems to provide the scientific basis for understanding global change. The space-based components of MTPE will provide a constellation of satellites to monitor the Earth from space. Sustained observations will allow researchers to monitor climate variables overtime to determine trends; however, space-based monitoring alone is not sufficient. A comprehensive data and information system, a community of scientists performing research with the data acquired, and extensive ground campaigns are all important components. Brief descriptions of the various elements that comprise the overall mission are provided. The Earth Observing System (EOS) - a series of polar-orbiting and low-inclination satellites for long-term global observations of the land surface, biosphere, solid Earth, atmosphere, and oceans - is the centerpiece of MTPE. The elements comprising the EOS mission are described in detail.

The SMAP Level 4 Surface and Root-zone Soil Moisture (L4_SM) Product

NASA Technical Reports Server (NTRS)

Reichle, Rolf; Crow, Wade; Koster, Randal; Kimball, John

2010-01-01

The Soil Moisture Active and Passive (SMAP) mission is being developed by NASA for launch in 2013 as one of four first-tier missions recommended by the U.S. National Research Council Committee on Earth Science and Applications from Space in 2007. The primary science objectives of SMAP are to enhance understanding of land surface controls on the water, energy and carbon cycles, and to determine their linkages. Moreover, the high resolution soil moisture mapping provided by SMAP has practical applications in weather and seasonal climate prediction, agriculture, human health, drought and flood decision support. In this paper we describe the assimilation of SMAP observations for the generation of the planned SMAP Level 4 Surface and Root-zone Soil Moisture (L4_SM) product. The SMAP mission makes simultaneous active (radar) and passive (radiometer) measurements in the 1.26-1.43 GHz range (L-band) from a sun-synchronous low-earth orbit. Measurements will be obtained across a 1000 km wide swath using conical scanning at a constant incidence angle (40 deg). The radar resolution varies from 1-3 km over the outer 70% of the swath to about 30 km near the center of the swath. The radiometer resolution is 40 km across the entire swath. The radiometer measurements will allow high-accuracy but coarse resolution (40 km) measurements. The radar measurements will add significantly higher resolution information. The radar is however very sensitive to surface roughness and vegetation structure. The combination of the two measurements allows optimal blending of the advantages of each instrument. SMAP directly observes only surface soil moisture (in the top 5 cm of the soil column). Several of the key applications targeted by SMAP, however, require knowledge of root zone soil moisture (approximately top 1 m of the soil column), which is not directly measured by SMAP. The foremost objective of the SMAP L4_SM product is to fill this gap and provide estimates of root zone soil moisture that are informed by and consistent with SMAP observations. Such estimates are obtained by merging SMAP observations with estimates from a land surface model in a soil moisture data assimilation system. The land surface model component of the assimilation system is driven with observations-based surface meteorological forcing data, including precipitation, which is the most important driver for soil moisture. The model also encapsulates knowledge of key land surface processes, including the vertical transfer of soil moisture between the surface and root zone reservoirs. Finally, the model interpolates and extrapolates SMAP observations in time and in space. The L4_SM product thus provides a comprehensive and consistent picture of land surface hydrological conditions based on SMAP observations and complementary information from a variety of sources. The assimilation algorithm considers the respective uncertainties of each component and yields a product that is superior to satellite or model data alone. Error estimates for the L4_SM product are generated as a by-product of the data assimilation system.

Basin-Scale Assessment of the Land Surface Water Budget in the National Centers for Environmental Prediction Operational and Research NLDAS-2 Systems

NASA Technical Reports Server (NTRS)

Xia, Youlong; Cosgrove, Brian A.; Mitchell, Kenneth E.; Peters-Lidard, Christa D.; Ek, Michael B.; Brewer, Michael; Mocko, David; Kumar, Sujay V.; Wei, Helin; Meng, Jesse;

A review on remotely sensed land surface temperature anomaly as an earthquake precursor

NASA Astrophysics Data System (ADS)

Bhardwaj, Anshuman; Singh, Shaktiman; Sam, Lydia; Joshi, P. K.; Bhardwaj, Akanksha; Martín-Torres, F. Javier; Kumar, Rajesh

2017-12-01

The low predictability of earthquakes and the high uncertainty associated with their forecasts make earthquakes one of the worst natural calamities, capable of causing instant loss of life and property. Here, we discuss the studies reporting the observed anomalies in the satellite-derived Land Surface Temperature (LST) before an earthquake. We compile the conclusions of these studies and evaluate the use of remotely sensed LST anomalies as precursors of earthquakes. The arrival times and the amplitudes of the anomalies vary widely, thus making it difficult to consider them as universal markers to issue earthquake warnings. Based on the randomness in the observations of these precursors, we support employing a global-scale monitoring system to detect statistically robust anomalous geophysical signals prior to earthquakes before considering them as definite precursors.

Precise Orbit Determination for ALOS

NASA Technical Reports Server (NTRS)

Nakamura, Ryo; Nakamura, Shinichi; Kudo, Nobuo; Katagiri, Seiji

2007-01-01

The Advanced Land Observing Satellite (ALOS) has been developed to contribute to the fields of mapping, precise regional land coverage observation, disaster monitoring, and resource surveying. Because the mounted sensors need high geometrical accuracy, precise orbit determination for ALOS is essential for satisfying the mission objectives. So ALOS mounts a GPS receiver and a Laser Reflector (LR) for Satellite Laser Ranging (SLR). This paper deals with the precise orbit determination experiments for ALOS using Global and High Accuracy Trajectory determination System (GUTS) and the evaluation of the orbit determination accuracy by SLR data. The results show that, even though the GPS receiver loses lock of GPS signals more frequently than expected, GPS-based orbit is consistent with SLR-based orbit. And considering the 1 sigma error, orbit determination accuracy of a few decimeters (peak-to-peak) was achieved.

Towards a satellite driven land surface model using SURFEX modelling platform Offline Data Assimilation: an assessment of the method over Europe and the Mediterranean basin

NASA Astrophysics Data System (ADS)

Albergel, Clément; Munier, Simon; Leroux, Delphine; Fairbairn, David; Dorigo, Wouter; Decharme, Bertrand; Calvet, Jean-Christophe

2017-04-01

Modelling platforms including Land Surface Models (LSMs), forced by gridded atmospheric variables and coupled to river routing models are necessary to increase our understanding of the terrestrial water cycle. These LSMs need to simulate biogeophysical variables like Surface and Root Zone Soil Moisture (SSM, RZSM), Leaf Area Index (LAI) in a way that is fully consistent with the representation of surface/energy fluxes and river discharge simulations. Global SSM and LAI products are now operationally available from spaceborne instruments and they can be used to constrain LSMs through Data Assimilation (DA) techniques. In this study, an offline data assimilation system implemented in Météo-France's modelling platform (SURFEX) is tested over Europe and the Mediterranean basin to increase prediction accuracy for land surface variables. The resulting Land Data Assimilation System (LDAS) makes use of a simplified Extended Kalman Filter (SEKF). It is able to ingests information from satellite derived (i) SSM from the latest version of the ESA Climate Change Initiative as well as (ii) LAI from the Copernicus GLS project to constrain the multilayer, CO2-responsive version of the Interactions Between Soil, Biosphere, and Atmosphere model (ISBA) coupled with Météo-France's version of the Total Runoff Integrating Pathways continental hydrological system (ISBA-CTRIP). ERA-Interim observations based atmospheric forcing with precipitations corrected from Global Precipitation Climatology Centre observations (GPCC) is used to force ISBA-CTRIP at a resolution of 0.5 degree over 2000-2015. The model sensitivity to the assimilated observations is presented and a set of statistical diagnostics used to evaluate the impact of assimilating SSM and LAI on different model biogeophysical variables are provided. It is demonstrated that the assimilation scheme works effectively. The SEKF is able to extract useful information from the data signal at the grid scale and distribute the RZSM and LAI increments throughout the model impacting soil moisture, terrestrial vegetation and water cycle, surface carbon and energy fluxes.

The impact of Surface Wind Velocity Data Assimilation on the Predictability of Plume Advection in the Lower Troposphere

NASA Astrophysics Data System (ADS)

Sekiyama, Thomas; Kajino, Mizuo; Kunii, Masaru

2017-04-01

The authors investigated the impact of surface wind velocity data assimilation on the predictability of plume advection in the lower troposphere exploiting the radioactive cesium emitted by the Fukushima nuclear accident in March 2011 as an atmospheric tracer. It was because the radioactive cesium plume was dispersed from the sole point source exactly placed at the Fukushima Daiichi Nuclear Power Plant and its surface concentration was measured at many locations with a high frequency and high accuracy. We used a non-hydrostatic regional weather prediction model with a horizontal resolution of 3 km, which was coupled with an ensemble Kalman filter data assimilation system in this study, to simulate the wind velocity and plume advection. The main module of this weather prediction model has been developed and used operationally by the Japan Meteorological Agency (JMA) since before March 2011. The weather observation data assimilated into the model simulation were provided from two data resources; [#1] the JMA observation archives collected for numerical weather predictions (NWPs) and [#2] the land-surface wind velocity data archived by the JMA surface weather observation network. The former dataset [#1] does not contain land-surface wind velocity observations because their spatial representativeness is relatively small and therefore the land-surface wind velocity data assimilation normally deteriorates the more than one day NWP performance. The latter dataset [#2] is usually used for real-time weather monitoring and never used for the data assimilation of more than one day NWPs. We conducted two experiments (STD and TEST) to reproduce the radioactive cesium plume behavior for 48 hours from 12UTC 14 March to 12UTC 16 March 2011 over the land area of western Japan. The STD experiment was performed to replicate the operational NWP using only the #1 dataset, not assimilating land-surface wind observations. In contrast, the TEST experiment was performed assimilating both the #1 dataset and the #2 dataset including land-surface wind observations measured at more than 200 stations in the model domain. The meteorological boundary conditions for both the experiments were imported from the JMA operational global NWP model results. The modeled radioactive cesium concentrations were examined for plume arrival timing at each observatory comparing with the hourly-measured "suspended particulate matter" filter tape's cesium concentrations retrieved by Tsuruta et al. at more than 40 observatories. The averaged difference of the plume arrival times at 40 observatories between the observational reality and the STD experiment was 82.0 minutes; at this time, the forecast period was 13 hours on average. Meanwhile, The averaged difference of the TEST experiment was 72.8 minutes, which was smaller than that of the STD experiment with a statistical significance of 99.2 %. In summary, the land-surface wind velocity data assimilation improves the predictability of plume advection in the lower troposphere at least in the case of wintertime air pollution over complex terrain. We need more investigation into the data assimilation impact of land-surface weather observations on the predictability of pollutant dispersion especially in the planetary boundary layer.

Compressive Strength of Cometary Surfaces Derived from Radar Observations

NASA Astrophysics Data System (ADS)

ElShafie, A.; Heggy, E.

2014-12-01

Landing on a comet nucleus and probing it, mechanically using harpoons, penetrometers and drills, and electromagnetically using low frequency radar waves is a complex task that will be tackled by the Rosetta mission for Comet 67P/Churyumov-Gerasimenko. The mechanical properties (i.e. density, porosity and compressive strength) and the electrical properties (i.e. the real and imaginary parts of the dielectric constant) of the comet nucleus, constrain both the mechanical and electromagnetic probing capabilities of Rosetta, as well as the choice of landing site, the safety of the landing, and subsurface data interpretation. During landing, the sounding radar data that will be collected by Rosetta's CONSERT experiment can be used to probe the comet's upper regolith layer by assessing its dielectric properties, which are then inverted to retrieve the surface mechanical properties. These observations can help characterize the mechanical properties of the landing site, which will optimize the operation of the anchor system. In this effort, we correlate the mechanical and electrical properties of cometary analogs to each other, and derive an empirical model that can be used to retrieve density, porosity and compressive strength from the dielectric properties of the upper regolith inverted from CONSERT observations during the landing phase. In our approach we consider snow as a viable cometary material analog due to its low density and its porous nature. Therefore, we used the compressive strength and dielectric constant measurements conducted on snow at a temperature of 250 K and a density range of 0.4-0.9 g/cm3 in order to investigate the relation between compressive strength and dielectric constant under cometary-relevant density range. Our results suggest that compressive strength increases linearly as function of the dielectric constant over the observed density range mentioned above. The minimum and maximum compressive strength of 0.5 and 4.5 MPa corresponded to a dielectric constant of 2.2 and 3.4 over the density range of 0.4-0.9 g/cm3. This preliminary correlation will be applied to the case of porous and dust contaminated snow under different temperatures to assess the surface mechanical properties for Comet 67P.

GEONEX: Land Monitoring From a New Generation of Geostationary Satellite Sensors

NASA Technical Reports Server (NTRS)

Nemani, Ramakrishna; Lyapustin, Alexei; Wang, Weile; Wang, Yujie; Hashimoto, Hirofumi; Li, Shuang; Ganguly, Sangram; Michaelis, Andrew; Higuchi, Atsushi; Takaneka, Hideaki;

GEONEX: Land monitoring from a new generation of geostationary satellite sensors

NASA Astrophysics Data System (ADS)

Nemani, R. R.; Lyapustin, A.; Wang, W.; Ganguly, S.; Wang, Y.; Michaelis, A.; Hashimoto, H.; Li, S.; Higuchi, A.; Huete, A. R.; Yeom, J. M.; camacho De Coca, F.; Lee, T. J.; Takenaka, H.

2017-12-01

The latest generation of geostationary satellites carry sensors such as ABI (Advanced Baseline Imager on GOES-16) and the AHI (Advanced Himawari Imager on Himawari) that closely mimic the spatial and spectral characteristics of Earth Observing System flagship MODIS for monitoring land surface conditions. More importantly they provide observations at 5-15 minute intervals. Such high frequency data offer exciting possibilities for producing robust estimates of land surface conditions by overcoming cloud cover, enabling studies of diurnally varying local-to-regional biosphere-atmosphere interactions, and operational decision-making in agriculture, forestry and disaster management. But the data come with challenges that need special attention. For instance, geostationary data feature changing sun angle at constant view for each pixel, which is reciprocal to sun-synchronous observations, and thus require careful adaptation of EOS algorithms. Our goal is to produce a set of land surface products from geostationary sensors by leveraging NASA's investments in EOS algorithms and in the data/compute facility NEX. The land surface variables of interest include atmospherically corrected surface reflectances, snow cover, vegetation indices and leaf area index (LAI)/fraction of photosynthetically absorbed radiation (FPAR), as well as land surface temperature and fires. In order to get ready to produce operational products over the US from GOES-16 starting 2018, we have utilized 18 months of data from Himawari AHI over Australia to test the production pipeline and the performance of various algorithms for our initial tests. The end-to-end processing pipeline consists of a suite of modules to (a) perform calibration and automatic georeference correction of the AHI L1b data, (b) adopt the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm to produce surface spectral reflectances along with compositing schemes and QA, and (c) modify relevant EOS retrieval algorithms (e.g., LAI and FPAR, GPP, etc.) for subsequent science product generation. Initial evaluation of Himawari AHI products against standard MODIS products indicate general agreement, suggesting that data from geostationary sensors can augment low earth orbit (LEO) satellite observations.