A bias-corrected CMIP5 dataset for Africa using the CDF-t method - a contribution to agricultural impact studies

NASA Astrophysics Data System (ADS)

Moise Famien, Adjoua; Janicot, Serge; Delfin Ochou, Abe; Vrac, Mathieu; Defrance, Dimitri; Sultan, Benjamin; Noël, Thomas

2018-03-01

The objective of this paper is to present a new dataset of bias-corrected CMIP5 global climate model (GCM) daily data over Africa. This dataset was obtained using the cumulative distribution function transform (CDF-t) method, a method that has been applied to several regions and contexts but never to Africa. Here CDF-t has been applied over the period 1950-2099 combining Historical runs and climate change scenarios for six variables: precipitation, mean near-surface air temperature, near-surface maximum air temperature, near-surface minimum air temperature, surface downwelling shortwave radiation, and wind speed, which are critical variables for agricultural purposes. WFDEI has been used as the reference dataset to correct the GCMs. Evaluation of the results over West Africa has been carried out on a list of priority user-based metrics that were discussed and selected with stakeholders. It includes simulated yield using a crop model simulating maize growth. These bias-corrected GCM data have been compared with another available dataset of bias-corrected GCMs using WATCH Forcing Data as the reference dataset. The impact of WFD, WFDEI, and also EWEMBI reference datasets has been also examined in detail. It is shown that CDF-t is very effective at removing the biases and reducing the high inter-GCM scattering. Differences with other bias-corrected GCM data are mainly due to the differences among the reference datasets. This is particularly true for surface downwelling shortwave radiation, which has a significant impact in terms of simulated maize yields. Projections of future yields over West Africa are quite different, depending on the bias-correction method used. However all these projections show a similar relative decreasing trend over the 21st century.

Abnormal temperature dependence of conductance of single Cd-doped ZnO nanowires

NASA Astrophysics Data System (ADS)

Li, Q. H.; Wan, Q.; Wang, Y. G.; Wang, T. H.

2005-06-01

Positive temperature coefficient of resistance is observed on single Cd-doped ZnO nanowires. The current along the nanowire increases linearly with the bias and saturates at large biases. The conductance is greatly enhanced either by ultraviolet illumination or infrared illumination. However, the conductance decreases with increasing temperature, in contrast to the reported temperature behavior either for ZnO nanostructures or for CdO nanoneedles. The increase of the conductance under illumination is related to surface effect and the decrease with increasing temperature to bulk effect. These results show that Cd doping does not change surface effect but affects bulk effect. Such a bulk effect could be used to realize on-chip temperature-independent varistors.

North Atlantic climate model bias influence on multiyear predictability

NASA Astrophysics Data System (ADS)

Wu, Y.; Park, T.; Park, W.; Latif, M.

2018-01-01

The influences of North Atlantic biases on multiyear predictability of unforced surface air temperature (SAT) variability are examined in the Kiel Climate Model (KCM). By employing a freshwater flux correction over the North Atlantic to the model, which strongly alleviates both North Atlantic sea surface salinity (SSS) and sea surface temperature (SST) biases, the freshwater flux-corrected integration depicts significantly enhanced multiyear SAT predictability in the North Atlantic sector in comparison to the uncorrected one. The enhanced SAT predictability in the corrected integration is due to a stronger and more variable Atlantic Meridional Overturning Circulation (AMOC) and its enhanced influence on North Atlantic SST. Results obtained from preindustrial control integrations of models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5) support the findings obtained from the KCM: models with large North Atlantic biases tend to have a weak AMOC influence on SAT and exhibit a smaller SAT predictability over the North Atlantic sector.

Confronting the surface temperature cold bias in AGCMs over the Tibetan Plateau and improving climate simulations

NASA Astrophysics Data System (ADS)

Wu, G. X.; Liu, Y.; Bao, Q.; Chen, X.; Li, J.

2017-12-01

One of the mid-term progresses of the NSFC- Key Research Program "Land-air Coupling over the Tibetan Plateau and Its Climate Impact " is presented. The elevated heating in summer and cooling in winter of the Tibetan Plateau significantly regulate the seasonal change of the atmospheric circulation and exert remarkable impacts on world climate. Recent studies have demonstrated that the majority of the Phase-5 Coupled Model Inter-comparison Project (CMIP5) models underestimate annual and seasonal mean surface air temperatures (Ta) over the Tibetan Plateau (TP). In addition, more than half of the models underestimate annual and seasonal mean surface temperatures (Ts) over the TP. These cold biases are larger over the western TP. By decomposing the Ts bias using the surface energy budget equation, it was demonstrated that this TP's cold bias can be attributed to various factors, in which the stronger bias in surface albedo (a-) and the weaker bias in clear-sky downward Longwave radiation (DLR) play the most significant roles. Since a- and DLR are respectively affected by snow coverage fraction at the ground surface and water vapor content in the atmosphere, these results then imply that the cold bias over the TP is caused by too large snow coverage fraction and too less water vapor content over the TP in the models. The FAMIL AGCM model developed at LASG also suffers from the similar cold bias over the TP. By introducing the 3D- Radiative Transfer Parameterization Over Mountains/Snow (Liou, 2013) into the model, the total solar radiation reaching the ground surface is increased during the daytime, resulting in more snowmelt and less snow coverage. Accordingly, surface albedo is decreased on the sunny side of the mountains, and the surface cold bias over mountain areas is decreased. It is shown that the improvement is sensitive to the model resolution: increased the horizontal resolution of Community Land Model version 4.0 (CLM 4.0) from nearly 200km (1.9o×2.5o) to about 25km (0.23o×0.31o) can significantly improve the parameterization effect and accuracy, with more notably improvement appearing in Spring. It is demonstrated that, by stimulating a Rossby wave and strengthen the precipitation in subtropical frontal zone of East Asia, the decrement of clod bias over the TP can greatly improve the climate simulations of the model.

Estimating the urban bias of surface shelter temperatures using upper-air and satellite data. Part 2: Estimation of the urban bias

NASA Technical Reports Server (NTRS)

Epperson, David L.; Davis, Jerry M.; Bloomfield, Peter; Karl, Thomas R.; Mcnab, Alan L.; Gallo, Kevin P.

1995-01-01

A methodology is presented for estimating the urban bias of surface shelter temperatures due to the effect of the urban heat island. Multiple regression techniques were used to predict surface shelter temperatures based on the time period 1986-89 using upper-air data from the European Centre for Medium-Range Weather Forecasts (ECMWF) to represent the background climate, site-specific data to represent the local landscape, and satellite-derived data -- the normalized difference vegetation index (NDVI) and the Defense Meteorological Satellite Program (DMSP) nighttime brightness data -- to represent the urban and rural landscape. Local NDVI and DMSP values were calculated for each station using the mean NDVI and DMSP values from a 3 km x 3 km area centered over the given station. Regional NDVI and DMSP values were calculated to represent a typical rural value for each station using the mean NDVI and DMSP values from a 1 deg x 1 deg latitude-longitude area in which the given station was located. Models for the United States were then developed for monthly maximum, mean, and minimum temperatures using data from over 1000 stations in the U.S. Cooperative (COOP) Network and for monthly mean temperatures with data from over 1150 stations in the Global Historical Climate Network (GHCN). Local biases, or the differences between the model predictions using the observed NDVI and DMSP values, and the predictions using the background regional values were calculated and compared with the results of other research. The local or urban bias of U.S. temperatures, as derived from all U.S. stations (urban and rural) used in the models, averaged near 0.40 C for monthly minimum temperatures, near 0.25 C for monthly mean temperatures, and near 0.10 C for monthly maximum temperatures. The biases of monthly minimum temperatures for individual stations ranged from near -1.1 C for rural stations to 2.4 C for stations from the largest urban areas. The results of this study indicate minimal problems for global application once global NDVI and DMSP data become available.

Eastern equatorial Pacific sea surface temperature annual cycle in the Kiel climate model: simulation benefits from enhancing atmospheric resolution

NASA Astrophysics Data System (ADS)

Wengel, C.; Latif, M.; Park, W.; Harlaß, J.; Bayr, T.

2018-05-01

A long-standing difficulty of climate models is to capture the annual cycle (AC) of eastern equatorial Pacific (EEP) sea surface temperature (SST). In this study, we first examine the EEP SST AC in a set of integrations of the coupled Kiel Climate Model, in which only atmosphere model resolution differs. When employing coarse horizontal and vertical atmospheric resolution, significant biases in the EEP SST AC are observed. These are reflected in an erroneous timing of the cold tongue's onset and termination as well as in an underestimation of the boreal spring warming amplitude. A large portion of these biases are linked to a wrong simulation of zonal surface winds, which can be traced back to precipitation biases on both sides of the equator and an erroneous low-level atmospheric circulation over land. Part of the SST biases also is related to shortwave radiation biases related to cloud cover biases. Both wind and cloud cover biases are inherent to the atmospheric component, as shown by companion uncoupled atmosphere model integrations forced by observed SSTs. Enhancing atmosphere model resolution, horizontal and vertical, markedly reduces zonal wind and cloud cover biases in coupled as well as uncoupled mode and generally improves simulation of the EEP SST AC. Enhanced atmospheric resolution reduces convection biases and improves simulation of surface winds over land. Analysis of a subset of models from the Coupled Model Intercomparison Project phase 5 (CMIP5) reveals that in these models, very similar mechanisms are at work in driving EEP SST AC biases.

The CAUSES Model Intercomparison Project: Using hindcast approach to study the U.S. summertime surface warm temperature bias

NASA Astrophysics Data System (ADS)

Ma, H. Y.; Klein, S. A.; Xie, S.; Zhang, C.; Morcrette, C. J.; Van Weverberg, K.; Petch, J.

2016-12-01

The CAUSES (Clouds Above the United States and Errors at the Surface) is a joint GASS/RGCM/ASR model intercomparison project with an observational focus (data from the U.S. DOE ARM SGP site and other observations). The goal of this project is to evaluate the role of clouds, radiation and precipitation processes in contributing to the surface air temperature bias in the region of the central U.S., which is seen in several weather and climate models. In this project, we use a short-term hindcast approach and examine the error growth due to cloud-associated processes while the large-scale state remains close to observations. The study period is from April 1 to August 31, 2011, which also covers the entire Midlatitude Continental Convective Clouds Experiment (MC3E) campaign that provides very frequent radiosondes (8 per day) and many extensive cloud and precipitation radar observations. Our preliminary analysis indicates that the warm surface air temperature bias in the mean diurnal cycle of the whole study period is very robust across all the participating models over the ARM SGP site. During the spring season (April-May), the daytime warm bias in most models is mostly due to excessive net surface shortwave flux resulting from insufficient deep convective cloud fraction or too optically thin clouds. The nighttime warm bias is likely due to the excessive downwelling longwave flux warming resulting from the persisting deep clouds. During the summer season (June-August), bias contribution from precipitation bias becomes important. The insufficient seasonal accumulated precipitation from the propagating convective systems originated from the Rockies contributes to lower soil moisture. Such condition drives the land surface to a dry state whereby radiative input can only be balanced by sensible heat loss through an increased surface air temperature. More information about the CAUSES project can be found through the following project webpage (http://portal.nersc.gov/project/capt/CAUSES/). (This study is funded by the RGCM and ASR programs of the U.S. Department of Energy as part of the Cloud-Associated Parameterizations Testbed. This work is performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. LLNL-ABS-688818)

Substrate bias effect on the fabrication of thermochromic VO2 films by reactive RF sputtering

NASA Astrophysics Data System (ADS)

Miyazaki, H.; Yasui, I.

2006-05-01

Vanadium oxide VOx films were deposited by reactive RF magnetron sputtering by applying a substrate bias, in which the Ar ions in plasma impacted the growing film surface. The vanadium valence of the VOx film decreased when the substrate negative bias voltage was increased. The VO2 film was successfully deposited at a substrate temperature of 400 °C and with a bias voltage of -50 to -80 V. The transition temperatures of the VO2 films with a substrate bias of -50 and -80 V were about 56 °C and 44 °C, respectively.

Observed Screen (Air) and GCM Surface/Screen Temperatures: Implications for Outgoing Longwave Fluxes at the Surface.

NASA Astrophysics Data System (ADS)

Garratt, J. R.

1995-05-01

There is direct evidence that excess net radiation calculated in general circulation models at continental surfaces [of about 11-17 W m2 (20%-27%) on an annual ~1 is not only due to overestimates in annual incoming shortwave fluxes [of 9-18 W m2 (6%-9%)], but also to underestimates in outgoing longwave fluxes. The bias in the outgoing longwave flux is deduced from a comparison of screen-air temperature observations, available as a global climatology of mean monthly values, and model-calculated surface and screen-air temperatures. An underestimate in the screen temperature computed in general circulation models over continents, of about 3 K on an annual basis, implies an underestimate in the outgoing longwave flux, averaged in six models under study, of 11-15 W m2 (3%-4%). For a set of 22 inland stations studied previously, the residual bias on an annual basis (the residual is the net radiation minus incoming shortwave plus outgoing longwave) varies between 18 and 23 W m2 for the models considered. Additional biases in one or both of the reflected shortwave and incoming longwave components cannot be ruled out.

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.

Implementation of Coupled Skin Temperature Analysis and Bias Correction in a Global Atmospheric Data Assimilation System

NASA Technical Reports Server (NTRS)

Radakovich, Jon; Bosilovich, M.; Chern, Jiun-dar; daSilva, Arlindo

2004-01-01

The NASA/NCAR Finite Volume GCM (fvGCM) with the NCAR CLM (Community Land Model) version 2.0 was integrated into the NASA/GMAO Finite Volume Data Assimilation System (fvDAS). A new method was developed for coupled skin temperature assimilation and bias correction where the analysis increment and bias correction term is passed into the CLM2 and considered a forcing term in the solution to the energy balance. For our purposes, the fvDAS CLM2 was run at 1 deg. x 1.25 deg. horizontal resolution with 55 vertical levels. We assimilate the ISCCP-DX (30 km resolution) surface temperature product. The atmospheric analysis was performed 6-hourly, while the skin temperature analysis was performed 3-hourly. The bias correction term, which was updated at the analysis times, was added to the skin temperature tendency equation at every timestep. In this presentation, we focus on the validation of the surface energy budget at the in situ reference sites for the Coordinated Enhanced Observation Period (CEOP). We will concentrate on sites that include independent skin temperature measurements and complete energy budget observations for the month of July 2001. In addition, MODIS skin temperature will be used for validation. Several assimilations were conducted and preliminary results will be presented.

Comparisons between data assimilated HYCOM output and in situ Argo measurements in the Bay of Bengal

NASA Astrophysics Data System (ADS)

Wilson, E. A.; Riser, S.

2014-12-01

This study evaluates the performance of data assimilated Hybrid Coordinate Ocean Model (HYCOM) output for the Bay of Bengal from September 2008 through July 2013. We find that while HYCOM assimilates Argo data, the model still suffers from significant temperature and salinity biases in this region. These biases are most severe in the northern Bay of Bengal, where the model tends to be too saline near the surface and too fresh at depth. The maximum magnitude of these biases is approximately 0.6 PSS. We also find that the model's salinity biases have a distinct seasonal cycle. The most problematic periods are the months following the summer monsoon (Oct-Jan). HYCOM's near surface temperature estimates compare more favorably with Argo, but significant errors exist at deeper levels. We argue that optimal interpolation will tend to induce positive salinity biases in the northern regions of the Bay. Further, we speculate that these biases are introduced when the model relaxes to climatology and assimilates real-time data.

Collaborative Research: Process-Resolving Decomposition of the Global Temperature Response to Modes of Low Frequency Variability in a Changing Climate

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

Deng, Yi

2014-11-24

DOE-GTRC-05596 11/24/2104 Collaborative Research: Process-Resolving Decomposition of the Global Temperature Response to Modes of Low Frequency Variability in a Changing Climate PI: Dr. Yi Deng (PI) School of Earth and Atmospheric Sciences Georgia Institute of Technology 404-385-1821, yi.deng@eas.gatech.edu El Niño-Southern Oscillation (ENSO) and Annular Modes (AMs) represent respectively the most important modes of low frequency variability in the tropical and extratropical circulations. The projection of future changes in the ENSO and AM variability, however, remains highly uncertain with the state-of-the-science climate models. This project conducted a process-resolving, quantitative evaluations of the ENSO and AM variability in the modern reanalysis observationsmore » and in climate model simulations. The goal is to identify and understand the sources of uncertainty and biases in models’ representation of ENSO and AM variability. Using a feedback analysis method originally formulated by one of the collaborative PIs, we partitioned the 3D atmospheric temperature anomalies and surface temperature anomalies associated with ENSO and AM variability into components linked to 1) radiation-related thermodynamic processes such as cloud and water vapor feedbacks, 2) local dynamical processes including convection and turbulent/diffusive energy transfer and 3) non-local dynamical processes such as the horizontal energy transport in the oceans and atmosphere. In the past 4 years, the research conducted at Georgia Tech under the support of this project has led to 15 peer-reviewed publications and 9 conference/workshop presentations. Two graduate students and one postdoctoral fellow also received research training through participating the project activities. This final technical report summarizes key scientific discoveries we made and provides also a list of all publications and conference presentations resulted from research activities at Georgia Tech. The main findings include: 1) the distinctly different roles played by atmospheric dynamical processes in establishing surface temperature response to ENSO at tropics and extratropics (i.e., atmospheric dynamics disperses energy out of tropics during ENSO warm events and modulate surface temperature at mid-, high-latitudes through controlling downward longwave radiation); 2) the representations of ENSO-related temperature response in climate models fail to converge at the process-level particularly over extratropics (i.e., models produce the right temperature responses to ENSO but with wrong reasons); 3) water vapor feedback contributes substantially to the temperature anomalies found over U.S. during different phases of the Northern Annular Mode (NAM), which adds new insight to the traditional picture that cold/warm advective processes are the main drivers of local temperature responses to the NAM; 4) the overall land surface temperature biases in the latest NCAR model (CESM1) are caused by biases in surface albedo while the surface temperature biases over ocean are related to multiple factors including biases in model albedo, cloud and oceanic dynamics, and the temperature biases over different ocean basins are also induced by different process biases. These results provide a detailed guidance for process-level model turning and improvement, and thus contribute directly to the overall goal of reducing model uncertainty in projecting future changes in the Earth’s climate system, especially in the ENSO and AM variability.« less

Evaluation of energy fluxes in the NCEP climate forecast system version 2.0 (CFSv2)

NASA Astrophysics Data System (ADS)

Rai, Archana; Saha, Subodh Kumar

2018-01-01

The energy fluxes at the surface and top of the atmosphere (TOA) from a long free run by the NCEP climate forecast system version 2.0 (CFSv2) are validated against several observation and reanalysis datasets. This study focuses on the annual mean energy fluxes and tries to link it with the systematic cold biases in the 2 m air temperature, particularly over the land regions. The imbalance in the long term mean global averaged energy fluxes are also evaluated. The global averaged imbalance at the surface and at the TOA is found to be 0.37 and 6.43 Wm-2, respectively. It is shown that CFSv2 overestimates the land surface albedo, particularly over the snow region, which in turn contributes to the cold biases in 2 m air temperature. On the other hand, surface albedo is highly underestimated over the coastal region around Antarctica and that may have contributed to the warm bias over that oceanic region. This study highlights the need for improvements in the parameterization of snow/sea-ice albedo scheme for a realistic simulation of surface temperature and that may have implications on the global energy imbalance in the model.

Comparison between AVHRR surface temperature data and in-situ weather station temperatures over the Greenland Ice Sheet

NASA Astrophysics Data System (ADS)

Rezvanbehbahani, S.; Csatho, B. M.; Comiso, J. C.; Babonis, G. S.

2011-12-01

Advanced Very-High Resolution Radiometer (AVHRR) images have been exhaustively used to measure surface temperature time series of the Greenland Ice sheet. The purpose of this study is to assess the accuracy of monthly average ice sheet surface temperatures, derived from thermal infrared AVHRR satellite imagery on a 6.25 km grid. In-situ temperature data sets are from the Greenland Collection Network (GC-Net). GC-Net stations comprise sensors monitoring air temperature at 1 and 2 meter above the snow surface, gathered at every 60 seconds and monthly averaged to match the AVHRR temporal resolution. Our preliminary results confirm the good agreement between satellite and in-situ temperature measurements reported by previous studies. However, some large discrepancies still exist. While AVHRR provides ice surface temperature, in-situ stations measure air temperatures at different elevations above the snow surface. Since most in-situ data on ice sheets are collected by Automatic Weather Station (AWS) instruments, it is important to characterize the difference between surface and air temperatures. Therefore, we compared and analyzed average monthly AVHRR ice surface temperatures using data collected in 2002. Differences between these temperatures correlate with in-situ temperatures and GC-Net station elevations, with increasing differences at lower elevations and higher temperatures. The Summit Station (3199 m above sea level) and the Swiss Camp (1176 m above sea level) results were compared as high altitude and low altitude stations for 2002, respectively. Our results show that AVHRR derived temperatures were 0.5°K warmer than AWS temperature at the Summit Station, while this difference was 2.8°K in the opposite direction for the Swiss Camp with surface temperatures being lower than air temperatures. The positive bias of 0.5°K at the high altitude Summit Station (surface warmer than air) is within the retrieval error of AVHRR temperatures and might be in part due to atmospheric inversion. The large negative bias of 2.8°K at the low altitude Swiss Camp (surface colder than the air) could be caused by a combination of different factors including local effects such as more windy circumstances above the snow surface and biases introduced by the cloud-masking applied on the AVHRR images. Usually only satellite images acquired in clear-sky conditions are used for deriving monthly AVHRR average temperatures. Since cloud-free days are usually warmer, satellite derived temperatures tend to underestimate the real average temperatures, especially regions with frequent cloud cover, such as Swiss Camp. Therefore, cautions must be exercised while using ice surface temperatures derived from satellite imagery for glaciological applications. Eliminating the cloudy day's' temperature from the in-situ data prior to the comparison with AVHRR derived temperatures will provide a better assessment of AVHRR surface temperature measurement accuracy.

Memory effect versus exchange bias for maghemite nanoparticles

NASA Astrophysics Data System (ADS)

Nadeem, K.; Krenn, H.; Szabó, D. V.

2015-11-01

We studied the temperature dependence of memory and exchange bias effects and their dependence on each other in maghemite (γ-Fe2O3) nanoparticles by using magnetization studies. Memory effect in zero field cooled process in nanoparticles is a fingerprint of spin-glass behavior which can be due to i) surface disordered spins (surface spin-glass) and/or ii) randomly frozen and interacting nanoparticles core spins (super spin-glass). Temperature region (25-70 K) for measurements has been chosen just below the average blocking temperature (TB=75 K) of the nanoparticles. Memory effect (ME) shows a non-monotonous behavior with temperature. It shows a decreasing trend with decreasing temperature and nearly vanishes below 30 K. However it also decreased again near the blocking temperature of the nanoparticles e.g., 70 K. Exchange bias (EB) in these nanoparticles arises due to core/shell interface interactions. The EB increases sharply below 30 K due to increase in core/shell interactions, while ME starts vanishing below 30 K. We conclude that the core/shell interface interactions or EB have not enhanced the ME but may reduce it in these nanoparticles.

Reducing the biases in simulated polar climate by incorporating realistic surface spectral emissivity into the global climate model

NASA Astrophysics Data System (ADS)

Huang, X.; Chen, X.; Flanner, M.; Yang, P.; Feldman, D.; Kuo, C.

2017-12-01

Surface longwave emissivity can be less than unity and vary significantly with frequency. The emissivities of water, ice, and bare land all exhibit different spectral dependence, for both the far-IR and mid-IR bands. However, most climate models still assume blackbody surface in the longwave (LW) radiation scheme of their atmospheric modules. This study incorporates realistic surface spectral emissivity into the RRTMG_LW, the LW radiation scheme in CAM, which is the atmospheric component of the NCAR Community Earth System Model (CESM) version 1.1.1. Then we evaluate its impact on simulated climatology, especially for the polar regions. By ensuring the consistency of the broadband longwave flux across different modules of the CESM, the TOA energy balance in the simulation can be attained without additional tuning of the model. While the impact on global mean surface temperature is small, the surface temperature differences in Polar Regions are statistically significant. The mean surface temperature in Arctic in the modified CESM is 1.5K warmer than that in the standard CESM, reducing the cold bias that the standard CESM has with respect to observations. Accordingly the sea ice fraction in the modified CESM simulation is less than that in the standard CESM simulation by as much as 0.1, which significantly reduces the positive biases in the simulated sea ice coverage by the CESM. The largest sea-ice coverage difference happens in August and September, when new sea ice starts to form. The similar changes can be seen for the simulated Antarctic surface climate as well. In a nutshell, incorporating realistic surface spectral emissivity helps improving the fidelity of simulated surface energy budget in the polar region, which leads to a better simulation of the surface temperature and sea ice coverage.

Clear-sky irradiance simulation using GMAO products and its comparison to ground and CERES satellite observation

NASA Astrophysics Data System (ADS)

Ham, S. H.; Loeb, N. G.; Kato, S.; Rose, F. G.; Bosilovich, M. G.; Rutan, D. A.; Huang, X.; Collow, A.

2017-12-01

Global Modeling Assimilation Office (GMAO) GEOS assimilated datasets are used to describe temperature and humidity profiles in the Clouds and the Earth's Radiant Energy System (CERES) data processing. Given that advance versions of the assimilated data sets known as of Forward Processing (FP), FP Parallel (FPP), and Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2) datasets are available, we examine clear-sky irradiance calculation to see if accuracy is improved with these newer versions of GMAO datasets when their temperature and humidity profiles are used in computing irradiances. Two older versions, GEOS-5.2.0 and GEOS-5.4.1 are used for producing, respectively, Ed3 and Ed4 CERES data products. For the evaluation, CERES-derived TOA irradiances and observed ground-based surface irradiances are compared with the computed irradiances for clear skies identified by Moderate Resolution Imaging Spectroradiometer (MODIS). Surface type dependent spectral emissivity is taken from an observationally-based monthly gridded emissivity dataset. TOA longwave (LW) irradiances computed with GOES-5.2.0 temperature and humidity profiles are biased low, up to -5 Wm-2, compared to CERES-derived TOA longwave irradiance over tropical oceans. In contrast, computed longwave irradiances agree well with CERES observations with the biases less than 2 W m-2 when GOES-5.4.1, FP v5.13, or MERRA-2 temperature and humidity are used. The negative biases of the TOA LW irradiance computed with GOES-5.2.0 appear to be related to a wet bias at 500-850 hPa layer. This indicates that if the input of CERES algorithm switches from GOES-5.2.0 to FP v5.13 or MERRA-2, the bias in clear-sky longwave TOA fluxes over tropical oceans is expected to be smaller. At surface, downward LW irradiances computed with FP v5.13 and MERRA-2 are biased low, up to -10 Wm-2, compared to ground observations over tropical oceans. The magnitude of the bias in the longwave surface irradiances cannot be explained by uncertainties related to aerosol, which is estimated to be less than 2.5 W m-2. Therefore, the negative biases are likely caused by cold or dry biases in FP v5.13 and MERRA-2 datasets. We plan to continue the investigation with more ground sites.

Decadal climate simulations using the Climate Forecast System (CFS) coupled to the SSiB2 land surface model

NASA Astrophysics Data System (ADS)

De Sales, F.; Xue, Y.; Marx, L.; Ek, M. B.

2016-12-01

The Simplified Simple Biophysical version 2 (SSiB2) model was implemented in the NCEP Climate Forecast System (CFS) for two 30-yr simulations. One simulation was initialized from CFS reanalysis data (EXP1), and the other from a 10-yr spin-up run (EXP2), in which the ocean model was allowed to run freely while the atmosphere and land surface were maintained constant to adjust inconsistencies in the initial conditions. EXP2 also includes an update in the SSiB2's average soil water potential calculation. The material presented highlights the model's performance in predicting spatial and temporal variability of monthly precipitation and surface temperature and aims at determining the optimum configuration for longer simulations. In general, the model is able to reproduce the main features of large-scale precipitation, with spatial correlation (scorr) and RMSE of 0.8 and 1.4 mm day-1, respectively. A split ITCZ pattern is observed in the Pacific and Indian oceans, which results in dry biases along the equator and wet-bias bands to its north and south. Positive biases are also observed in the Atlantic ITCZ. The model generates consistent surface temperature climatology (scorr > 0.9, RMSE= 2.3°C). Warm biases are observed especially over southern Asia during summer. Both experiments produce similar precipitation climatology patterns with similar biases. EXP2, however, improves the temperature simulation by reducing the global bias by 48% and 26% during boreal winter and summer, respectively; and improves the temperature decadal variability for many areas. Moreover, EXP2 generates a better continental surface air warming trend. In the attempt to improve the precipitation decadal variability in the simulations, remotely-sensed LAI and vegetation cover fraction have been implemented in the CFS/SSiB2 to substitute the look-up table originally used in EXP1 and 2. The satellite vegetation data has been processed into global monthly maps which are continuous updated throughout the simulation. Results from this experiment will also be presented.

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;

Atlantic Meridional Overturning Circulation Influence on North Atlantic Sector Surface Air Temperature and its Predictability in the Kiel Climate Model

NASA Astrophysics Data System (ADS)

Latif, M.

2017-12-01

We investigate the influence of the Atlantic Meridional Overturning Circulation (AMOC) on the North Atlantic sector surface air temperature (SAT) in two multi-millennial control integrations of the Kiel Climate Model (KCM). One model version employs a freshwater flux correction over the North Atlantic, while the other does not. A clear influence of the AMOC on North Atlantic sector SAT only is simulated in the corrected model that depicts much reduced upper ocean salinity and temperature biases in comparison to the uncorrected model. Further, the model with much reduced biases depicts significantly enhanced multiyear SAT predictability in the North Atlantic sector relative to the uncorrected model. The enhanced SAT predictability in the corrected model is due to a stronger and more variable AMOC and its enhanced influence on North Atlantic sea surface temperature (SST). Results obtained from preindustrial control integrations of models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5) support the findings obtained from the KCM: models with large North Atlantic biases tend to have a weak AMOC influence on SST and exhibit a smaller SAT predictability over the North Atlantic sector.

Estimating Sea Surface Temperature Measurement Methods Using Characteristic Differences in the Diurnal Cycle

NASA Astrophysics Data System (ADS)

Carella, G.; Kennedy, J. J.; Berry, D. I.; Hirahara, S.; Merchant, C. J.; Morak-Bozzo, S.; Kent, E. C.

2018-01-01

Lack of reliable observational metadata represents a key barrier to understanding sea surface temperature (SST) measurement biases, a large contributor to uncertainty in the global surface record. We present a method to identify SST measurement practice by comparing the observed SST diurnal cycle from individual ships with a reference from drifting buoys under similar conditions of wind and solar radiation. Compared to existing estimates, we found a larger number of engine room-intake (ERI) reports post-World War II and in the period 1960-1980. Differences in the inferred mixture of observations lead to a systematic warmer shift of the bias adjusted SST anomalies from 1980 compared to previous estimates, while reducing the ensemble spread. Changes in mean field differences between bucket and ERI SST anomalies in the Northern Hemisphere over the period 1955-1995 could be as large as 0.5°C and are not well reproduced by current bias adjustment models.

Model development for MODIS thermal band electronic cross-talk

NASA Astrophysics Data System (ADS)

Chang, Tiejun; Wu, Aisheng; Geng, Xu; Li, Yonghong; Brinkmann, Jake; Keller, Graziela; Xiong, Xiaoxiong (Jack)

2016-10-01

MODerate-resolution Imaging Spectroradiometer (MODIS) has 36 bands. Among them, 16 thermal emissive bands covering a wavelength range from 3.8 to 14.4 μm. After 16 years on-orbit operation, the electronic crosstalk of a few Terra MODIS thermal emissive bands develop substantial issues which cause biases in the EV brightness temperature measurements and surface feature contamination. The crosstalk effects on band 27 with center wavelength at 6.7 μm and band 29 at 8.5 μm increased significantly in recent years, affecting downstream products such as water vapor and cloud mask. The crosstalk issue can be observed from nearly monthly scheduled lunar measurements, from which the crosstalk coefficients can be derived. Most of MODIS thermal bands are saturated at moon surface temperatures and the development of an alternative approach is very helpful for verification. In this work, a physical model was developed to assess the crosstalk impact on calibration as well as in Earth view brightness temperature retrieval. This model was applied to Terra MODIS band 29 empirically for correction of Earth brightness temperature measurements. In the model development, the detector nonlinear response is considered. The impacts of the electronic crosstalk are assessed in two steps. The first step consists of determining the impact on calibration using the on-board blackbody (BB). Due to the detector nonlinear response and large background signal, both linear and nonlinear coefficients are affected by the crosstalk from sending bands. The crosstalk impact on calibration coefficients was calculated. The second step is to calculate the effects on the Earth view brightness temperature retrieval. The effects include those from affected calibration coefficients and the contamination of Earth view measurements. This model links the measurement bias with crosstalk coefficients, detector nonlinearity, and the ratio of Earth measurements between the sending and receiving bands. The correction of the electronic crosstalk can be implemented empirically from the processed bias at different brightness temperature. The implementation can be done through two approaches. As routine calibration assessment for thermal infrared bands, the trending over select Earth scenes is processed for all the detectors in a band and the band averaged bias is derived for certain time. In this case, the correction of an affected band can be made using the regression of the model with band averaged bias and then corrections of detector differences are applied. The second approach requires the trending for individual detectors and the bias for each detector is used for regression with the model. A test using the first approach was made for Terra MODIS band 29 with the biases derived from long-term trending of sea surface temperature and Dome-C surface temperature.

Time-Dependent Cryospheric Longwave Surface Emissivity Feedback in the Community Earth System Model

NASA Astrophysics Data System (ADS)

Kuo, Chaincy; Feldman, Daniel R.; Huang, Xianglei; Flanner, Mark; Yang, Ping; Chen, Xiuhong

2018-01-01

Frozen and unfrozen surfaces exhibit different longwave surface emissivities with different spectral characteristics, and outgoing longwave radiation and cooling rates are reduced for unfrozen scenes relative to frozen ones. Here physically realistic modeling of spectrally resolved surface emissivity throughout the coupled model components of the Community Earth System Model (CESM) is advanced, and implications for model high-latitude biases and feedbacks are evaluated. It is shown that despite a surface emissivity feedback amplitude that is, at most, a few percent of the surface albedo feedback amplitude, the inclusion of realistic, harmonized longwave, spectrally resolved emissivity information in CESM1.2.2 reduces wintertime Arctic surface temperature biases from -7.2 ± 0.9 K to -1.1 ± 1.2 K, relative to observations. The bias reduction is most pronounced in the Arctic Ocean, a region for which Coupled Model Intercomparison Project version 5 (CMIP5) models exhibit the largest mean wintertime cold bias, suggesting that persistent polar temperature biases can be lessened by including this physically based process across model components. The ice emissivity feedback of CESM1.2.2 is evaluated under a warming scenario with a kernel-based approach, and it is found that emissivity radiative kernels exhibit water vapor and cloud cover dependence, thereby varying spatially and decreasing in magnitude over the course of the scenario from secular changes in atmospheric thermodynamics and cloud patterns. Accounting for the temporally varying radiative responses can yield diagnosed feedbacks that differ in sign from those obtained from conventional climatological feedback analysis methods.

The Effect of Elevation Bias in Interpolated Air Temperature Data Sets on Surface Warming in China During 1951-2015

NASA Astrophysics Data System (ADS)

Wang, Tingting; Sun, Fubao; Ge, Quansheng; Kleidon, Axel; Liu, Wenbin

2018-02-01

Although gridded air temperature data sets share much of the same observations, different rates of warming can be detected due to different approaches employed for considering elevation signatures in the interpolation processes. Here we examine the influence of varying spatiotemporal distribution of sites on surface warming in the long-term trend and over the recent warming hiatus period in China during 1951-2015. A suspicious cooling trend in raw interpolated air temperature time series is found in the 1950s, and 91% of which can be explained by the artificial elevation changes introduced by the interpolation process. We define the regression slope relating temperature difference and elevation difference as the bulk lapse rate of -5.6°C/km, which tends to be higher (-8.7°C/km) in dry regions but lower (-2.4°C/km) in wet regions. Compared to independent experimental observations, we find that the estimated monthly bulk lapse rates work well to capture the elevation bias. Significant improvement can be achieved in adjusting the interpolated original temperature time series using the bulk lapse rate. The results highlight that the developed bulk lapse rate is useful to account for the elevation signature in the interpolation of site-based surface air temperature to gridded data sets and is necessary for avoiding elevation bias in climate change studies.

CAUSES: Diagnosis of the Summertime Warm Bias in CMIP5 Climate Models at the ARM Southern Great Plains Site

NASA Astrophysics Data System (ADS)

Zhang, Chengzhu; Xie, Shaocheng; Klein, Stephen A.; Ma, Hsi-yen; Tang, Shuaiqi; Van Weverberg, Kwinten; Morcrette, Cyril J.; Petch, Jon

2018-03-01

All the weather and climate models participating in the Clouds Above the United States and Errors at the Surface project show a summertime surface air temperature (T2 m) warm bias in the region of the central United States. To understand the warm bias in long-term climate simulations, we assess the Atmospheric Model Intercomparison Project simulations from the Coupled Model Intercomparison Project Phase 5, with long-term observations mainly from the Atmospheric Radiation Measurement program Southern Great Plains site. Quantities related to the surface energy and water budget, and large-scale circulation are analyzed to identify possible factors and plausible links involved in the warm bias. The systematic warm season bias is characterized by an overestimation of T2 m and underestimation of surface humidity, precipitation, and precipitable water. Accompanying the warm bias is an overestimation of absorbed solar radiation at the surface, which is due to a combination of insufficient cloud reflection and clear-sky shortwave absorption by water vapor and an underestimation in surface albedo. The bias in cloud is shown to contribute most to the radiation bias. The surface layer soil moisture impacts T2 m through its control on evaporative fraction. The error in evaporative fraction is another important contributor to T2 m. Similar sources of error are found in hindcast from other Clouds Above the United States and Errors at the Surface studies. In Atmospheric Model Intercomparison Project simulations, biases in meridional wind velocity associated with the low-level jet and the 500 hPa vertical velocity may also relate to T2 m bias through their control on the surface energy and water budget.

Estimating Sampling Biases and Measurement Uncertainties of AIRS-AMSU-A Temperature and Water Vapor Observations Using MERRA Reanalysis

NASA Technical Reports Server (NTRS)

Hearty, Thomas J.; Savtchenko, Andrey K.; Tian, Baijun; Fetzer, Eric; Yung, Yuk L.; Theobald, Michael; Vollmer, Bruce; Fishbein, Evan; Won, Young-In

2014-01-01

We use MERRA (Modern Era Retrospective-Analysis for Research Applications) temperature and water vapor data to estimate the sampling biases of climatologies derived from the AIRS/AMSU-A (Atmospheric Infrared Sounder/Advanced Microwave Sounding Unit-A) suite of instruments. We separate the total sampling bias into temporal and instrumental components. The temporal component is caused by the AIRS/AMSU-A orbit and swath that are not able to sample all of time and space. The instrumental component is caused by scenes that prevent successful retrievals. The temporal sampling biases are generally smaller than the instrumental sampling biases except in regions with large diurnal variations, such as the boundary layer, where the temporal sampling biases of temperature can be +/- 2 K and water vapor can be 10% wet. The instrumental sampling biases are the main contributor to the total sampling biases and are mainly caused by clouds. They are up to 2 K cold and greater than 30% dry over mid-latitude storm tracks and tropical deep convective cloudy regions and up to 20% wet over stratus regions. However, other factors such as surface emissivity and temperature can also influence the instrumental sampling bias over deserts where the biases can be up to 1 K cold and 10% wet. Some instrumental sampling biases can vary seasonally and/or diurnally. We also estimate the combined measurement uncertainties of temperature and water vapor from AIRS/AMSU-A and MERRA by comparing similarly sampled climatologies from both data sets. The measurement differences are often larger than the sampling biases and have longitudinal variations.

Improved atmosphere-ocean coupled modeling in the tropics for climate prediction

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

Zhang, Minghua

2015-01-01

We investigated the initial development of the double ITCZ in the Community Climate System Model (CCSM Version 3) in the central Pacific. Starting from a resting initial condition of the ocean in January, the model developed a warm bias of sea-surface temperature (SST) in the central Pacific from 5oS to 10oS in the first three months. We found this initial bias to be caused by excessive surface shortwave radiation that is also present in the standalone atmospheric model. The initial bias is further amplified by biases in both surface latent heat flux and horizontal heat transport in the upper ocean.more » These biases are caused by the responses of surface winds to SST bias and the thermocline structure to surface wind curls. We also showed that the warming biases in surface solar radiation and latent heat fluxes are seasonally offset by cooling biases from reduced solar radiation after the austral summer due to cloud responses and in the austral fall due to enhanced evaporation when the maximum SST is closest to the equator. The warming biases from the dynamic heat transport by ocean currents however stay throughout all seasons once they are developed, which are eventually balanced by enhanced energy exchange and penetration of solar radiation below the mixed layer. Our results also showed that the equatorial cold tongue develops after the warm biases in the south central Pacific, and the overestimation of surface shortwave radiation recurs in the austral summer in each year.« less

An overview of mainland China temperature change research

NASA Astrophysics Data System (ADS)

Ren, Guoyu; Ding, Yihui; Tang, Guoli

2017-02-01

There has been significant effort devoted to investigating long-term trends in land surface air temperature over mainland China by Chinese scientists over the past 50 years, and much progress has been made in understanding dynamics of the changes. This review highlights research conducted by early Chinese climatologists, and particularly Professor Shaowu Wang from Peking University, with special focus on systematic work that has been conducted since the mid to late 1970s. We also discuss major issues that remain unresolved in past and current studies. The most recent analyses indicate that the country-average annual mean surface air temperature rose by 1.12°C over the past 115 years (1901-2015), with a rate of increase of about 0.10°C decade-1. Temperatures have risen more rapidly since the 1950s, with the rate of increase of more than 0.25°C decade-1. However, the recent increase in temperatures is in large part due to contamination by systematically biased data. These data are influenced by unprecedented urbanization in China, with a contribution of urbanization to the overall increase of annual mean temperatures in mainland China of about one third over the past half a century. If the bias is corrected, the rate of increase for the country-average annual mean surface air temperature is 0.17°C decade-1 over the last 50-60 years, which is approximately the same as global and Northern Hemispheric averages in recent decades. Future efforts should be focused towards the recovery and digitization of early-year observational records, the homogenization of observational data, the evaluation and adjustment of urbanization bias in temperature data series from urban stations, the analysis of extreme temperatures over longer periods including the first half of the 20th century, and the investigation of the observed surface air temperature change mechanisms in mainland China.

Identifying causes of Western Pacific ITCZ drift in ECMWF System 4 hindcasts

NASA Astrophysics Data System (ADS)

Shonk, Jonathan K. P.; Guilyardi, Eric; Toniazzo, Thomas; Woolnough, Steven J.; Stockdale, Tim

2018-02-01

The development of systematic biases in climate models used in operational seasonal forecasting adversely affects the quality of forecasts they produce. In this study, we examine the initial evolution of systematic biases in the ECMWF System 4 forecast model, and isolate aspects of the model simulations that lead to the development of these biases. We focus on the tendency of the simulated intertropical convergence zone in the western equatorial Pacific to drift northwards by between 0.5° and 3° of latitude depending on season. Comparing observations with both fully coupled atmosphere-ocean hindcasts and atmosphere-only hindcasts (driven by observed sea-surface temperatures), we show that the northward drift is caused by a cooling of the sea-surface temperature on the Equator. The cooling is associated with anomalous easterly wind stress and excessive evaporation during the first twenty days of hindcast, both of which occur whether air-sea interactions are permitted or not. The easterly wind bias develops immediately after initialisation throughout the lower troposphere; a westerly bias develops in the upper troposphere after about 10 days of hindcast. At this point, the baroclinic structure of the wind bias suggests coupling with errors in convective heating, although the initial wind bias is barotropic in structure and appears to have an alternative origin.

A Realization of Bias Correction Method in the GMAO Coupled System

NASA Technical Reports Server (NTRS)

Chang, Yehui; Koster, Randal; Wang, Hailan; Schubert, Siegfried; Suarez, Max

2018-01-01

Over the past several decades, a tremendous effort has been made to improve model performance in the simulation of the climate system. The cold or warm sea surface temperature (SST) bias in the tropics is still a problem common to most coupled ocean atmosphere general circulation models (CGCMs). The precipitation biases in CGCMs are also accompanied by SST and surface wind biases. The deficiencies and biases over the equatorial oceans through their influence on the Walker circulation likely contribute the precipitation biases over land surfaces. In this study, we introduce an approach in the CGCM modeling to correct model biases. This approach utilizes the history of the model's short-term forecasting errors and their seasonal dependence to modify model's tendency term and to minimize its climate drift. The study shows that such an approach removes most of model climate biases. A number of other aspects of the model simulation (e.g. extratropical transient activities) are also improved considerably due to the imposed pre-processed initial 3-hour model drift corrections. Because many regional biases in the GEOS-5 CGCM are common amongst other current models, our approaches and findings are applicable to these other models as well.

Omens of coupled model biases in the CMIP5 AMIP simulations

NASA Astrophysics Data System (ADS)

Găinuşă-Bogdan, Alina; Hourdin, Frédéric; Traore, Abdoul Khadre; Braconnot, Pascale

2018-02-01

Despite decades of efforts and improvements in the representation of processes as well as in model resolution, current global climate models still suffer from a set of important, systematic biases in sea surface temperature (SST), not much different from the previous generation of climate models. Many studies have looked at errors in the wind field, cloud representation or oceanic upwelling in coupled models to explain the SST errors. In this paper we highlight the relationship between latent heat flux (LH) biases in forced atmospheric simulations and the SST biases models develop in coupled mode, at the scale of the entire intertropical domain. By analyzing 22 pairs of forced atmospheric and coupled ocean-atmosphere simulations from the CMIP5 database, we show a systematic, negative correlation between the spatial patterns of these two biases. This link between forced and coupled bias patterns is also confirmed by two sets of dedicated sensitivity experiments with the IPSL-CM5A-LR model. The analysis of the sources of the atmospheric LH bias pattern reveals that the near-surface wind speed bias dominates the zonal structure of the LH bias and that the near-surface relative humidity dominates the east-west contrasts.

Backfitting in Smoothing Spline Anova, with Application to Historical Global Temperature Data

NASA Astrophysics Data System (ADS)

Luo, Zhen

In the attempt to estimate the temperature history of the earth using the surface observations, various biases can exist. An important source of bias is the incompleteness of sampling over both time and space. There have been a few methods proposed to deal with this problem. Although they can correct some biases resulting from incomplete sampling, they have ignored some other significant biases. In this dissertation, a smoothing spline ANOVA approach which is a multivariate function estimation method is proposed to deal simultaneously with various biases resulting from incomplete sampling. Besides that, an advantage of this method is that we can get various components of the estimated temperature history with a limited amount of information stored. This method can also be used for detecting erroneous observations in the data base. The method is illustrated through an example of modeling winter surface air temperature as a function of year and location. Extension to more complicated models are discussed. The linear system associated with the smoothing spline ANOVA estimates is too large to be solved by full matrix decomposition methods. A computational procedure combining the backfitting (Gauss-Seidel) algorithm and the iterative imputation algorithm is proposed. This procedure takes advantage of the tensor product structure in the data to make the computation feasible in an environment of limited memory. Various related issues are discussed, e.g., the computation of confidence intervals and the techniques to speed up the convergence of the backfitting algorithm such as collapsing and successive over-relaxation.

Daily air temperature interpolated at high spatial resolution over a large mountainous region

USGS Publications Warehouse

Dodson, R.; Marks, D.

1997-01-01

Two methods are investigated for interpolating daily minimum and maximum air temperatures (Tmin and Tmax) at a 1 km spatial resolution over a large mountainous region (830 000 km2) in the U.S. Pacific Northwest. The methods were selected because of their ability to (1) account for the effect of elevation on temperature and (2) efficiently handle large volumes of data. The first method, the neutral stability algorithm (NSA), used the hydrostatic and potential temperature equations to convert measured temperatures and elevations to sea-level potential temperatures. The potential temperatures were spatially interpolated using an inverse-squared-distance algorithm and then mapped to the elevation surface of a digital elevation model (DEM). The second method, linear lapse rate adjustment (LLRA), involved the same basic procedure as the NSA, but used a constant linear lapse rate instead of the potential temperature equation. Cross-validation analyses were performed using the NSA and LLRA methods to interpolate Tmin and Tmax each day for the 1990 water year, and the methods were evaluated based on mean annual interpolation error (IE). The NSA method showed considerable bias for sites associated with vertical extrapolation. A correction based on climate station/grid cell elevation differences was developed and found to successfully remove the bias. The LLRA method was tested using 3 lapse rates, none of which produced a serious extrapolation bias. The bias-adjusted NSA and the 3 LLRA methods produced almost identical levels of accuracy (mean absolute errors between 1.2 and 1.3??C), and produced very similar temperature surfaces based on image difference statistics. In terms of accuracy, speed, and ease of implementation, LLRA was chosen as the best of the methods tested.

Diagnostic and model dependent uncertainty of simulated Tibetan permafrost area

NASA Astrophysics Data System (ADS)

Wang, W.; Rinke, A.; Moore, J. C.; Cui, X.; Ji, D.; Li, Q.; Zhang, N.; Wang, C.; Zhang, S.; Lawrence, D. M.; McGuire, A. D.; Zhang, W.; Delire, C.; Koven, C.; Saito, K.; MacDougall, A.; Burke, E.; Decharme, B.

2015-03-01

We perform a land surface model intercomparison to investigate how the simulation of permafrost area on the Tibetan Plateau (TP) varies between 6 modern stand-alone land surface models (CLM4.5, CoLM, ISBA, JULES, LPJ-GUESS, UVic). We also examine the variability in simulated permafrost area and distribution introduced by 5 different methods of diagnosing permafrost (from modeled monthly ground temperature, mean annual ground and air temperatures, air and surface frost indexes). There is good agreement (99-135 x 104 km2) between the two diagnostic methods based on air temperature which are also consistent with the best current observation-based estimate of actual permafrost area (101 x 104 km2). However the uncertainty (1-128 x 104 km2) using the three methods that require simulation of ground temperature is much greater. Moreover simulated permafrost distribution on TP is generally only fair to poor for these three methods (diagnosis of permafrost from monthly, and mean annual ground temperature, and surface frost index), while permafrost distribution using air temperature based methods is generally good. Model evaluation at field sites highlights specific problems in process simulations likely related to soil texture specification and snow cover. Models are particularly poor at simulating permafrost distribution using definition that soil temperature remains at or below 0°C for 24 consecutive months, which requires reliable simulation of both mean annual ground temperatures and seasonal cycle, and hence is relatively demanding. Although models can produce better permafrost maps using mean annual ground temperature and surface frost index, analysis of simulated soil temperature profiles reveals substantial biases. The current generation of land surface models need to reduce biases in simulated soil temperature profiles before reliable contemporary permafrost maps and predictions of changes in permafrost distribution can be made for the Tibetan Plateau.

Improved Modeling of Surface Layer Parameters in a AGCM Using Refined Vertical Resolution in the Surface Layer

NASA Astrophysics Data System (ADS)

Shin, H. H.; Zhao, M.; Ming, Y.; Chen, X.; Lin, S. J.

2017-12-01

Surface layer (SL) parameters in atmospheric models - such as 2-m air temperature (T2), 10-m wind speed (U10), and surface turbulent fluxes - are computed by applying the Monin-Obukhov Similarity Theory (MOST) to the lowest model level height (LMH) in the models. The underlying assumption is that LMH is within surface layer height (SLH), but most AGCMs hardly meet the condition in stable boundary layers (SBLs) over land. To assess the errors in modeled SL parameters caused by this, offline computations of the MOST are performed with different LMHs from 1 to 100 m, for an idealized SBL case with prescribed surface parameters (surface temperature, roughness length and Obukhov length), and vertical profiles of temperature and winds. The results show that when LMH is higher than SLH, T2 and U10 are underestimated by O(1 K) and O(1 m/s), respectively, and the biases increase as LMH increases. Based on this, the refined vertical resolution with an additional layer in the SL is applied to the GFDL AGCM, and it reduces the systematic cold biases in T2 and the systematic underestimation of U10.

Exploring Model Error through Post-processing and an Ensemble Kalman Filter on Fire Weather Days

NASA Astrophysics Data System (ADS)

Erickson, Michael J.

The proliferation of coupling atmospheric ensemble data to models in other related fields requires a priori knowledge of atmospheric ensemble biases specific to the desired application. In that spirit, this dissertation focuses on elucidating atmospheric ensemble model bias and error through a variety of different methods specific to fire weather days (FWDs) over the Northeast United States (NEUS). Other than a handful of studies that use models to predict fire indices for single fire seasons (Molders 2008, Simpson et al. 2014), an extensive exploration of model performance specific to FWDs has not been attempted. Two unique definitions for FWDs are proposed; one that uses pre-existing fire indices (FWD1) and another from a new statistical fire weather index (FWD2) relating fire occurrence and near-surface meteorological observations. Ensemble model verification reveals FWDs to have warmer (> 1 K), moister (~ 0.4 g kg-1) and less windy (~ 1 m s-1) biases than the climatological average for both FWD1 and FWD2. These biases are not restricted to the near surface but exist through the entirety of the planetary boundary layer (PBL). Furthermore, post-processing methods are more effective when previous FWDs are incorporated into the statistical training, suggesting that model bias could be related to the synoptic flow pattern. An Ensemble Kalman Filter (EnKF) is used to explore the effectiveness of data assimilation during a period of extensive FWDs in April 2012. Model biases develop rapidly on FWDs, consistent with the FWD1 and FWD2 verification. However, the EnKF is effective at removing most biases for temperature, wind speed and specific humidity. Potential sources of error in the parameterized physics of the PBL are explored by rerunning the EnKF with simultaneous state and parameter estimation (SSPE) for two relevant parameters within the ACM2 PBL scheme. SSPE helps to reduce the cool temperature bias near the surface on FWDs, with the variability in parameter estimates exhibiting some relationship to model bias for temperature. This suggests the potential for structural model error within the ACM2 PBL scheme and could lead toward the future development of improved PBL parameterizations.

An Indirect Data Assimilation Scheme for Deep Soil Temperature in the Pleim-Xiu Land Surface Model

EPA Science Inventory

The Pleim-Xiu land surface model (PX LSM) has been improved by the addition of a 2nd indirect data assimilation scheme. The first, which was described previously, is a technique where soil moisture in nudged according to the biases in 2-m air temperature and relative humidity be...

Tuning the surface anisotropy in Fe-doped NiO nanoparticles.

PubMed

Moura, K O; Lima, R J S; Coelho, A A; Souza-Junior, E A; Duque, J G S; Meneses, C T

2014-01-07

Ni(1-x)FexO nanoparticles have been obtained by the co-precipitation chemical route. X-ray diffraction analyses using Rietveld refinement have shown a slight decrease in the microstrain and mean particle size as a function of the Fe content. The zero-field-cooling (ZFC) and field-cooling (FC) magnetization curves show superparamagnetic behavior at high temperatures and a low temperature peak (at T = 11 K), which is enhanced with increasing Fe concentration. Unusual behavior of the coercive field in the low temperature region and an exchange bias behavior were also observed. A decrease in the Fe concentration induces an increase in the exchange bias field. We argue that these behaviors can be linked with the strengthening of surface anisotropy caused by the incorporation of Fe ions.

Unabated global surface temperature warming: evaluating the evidence

NASA Astrophysics Data System (ADS)

Karl, T. R.; Arguez, A.

2015-12-01

New insights related to time-dependent bias corrections in global surface temperatures have led to higher rates of warming over the past few decades than previously reported in the IPCC Fifth Assessment Report (2014). Record high global temperatures in the past few years have also contributed to larger trends. The combination of these factors and new analyses of the rate of temperature change show unabated global warming since at least the mid-Twentieth Century. New time-dependent bias corrections account for: (1) differences in temperatures measured from ships and drifting buoys; (2) improved corrections to ship measured temperatures; and (3) the larger rates of warming in polar regions (particularly the Arctic). Since 1951, the period over which IPCC (2014) attributes over half of the observed global warming to human causes, it is shown that there has been a remarkably robust and sustained warming, punctuated with inter-annual and decadal variability. This finding is confirmed through simple trend analysis and Empirical Mode Decomposition (EMD). Trend analysis however, especially for decadal trends, is sensitive to selection bias of beginning and ending dates. EMD has no selection bias. Additionally, it can highlight both short- and long-term processes affecting the global temperature times series since it addresses both non-linear and non-stationary processes. For the new NOAA global temperature data set, our analyses do not support the notion of a hiatus or slowing of long-term global warming. However, sub-decadal periods of little (or no warming) and rapid warming can also be found, clearly showing the impact of inter-annual and decadal variability that previously has been attributed to both natural and human-induced non-greenhouse forcings.

High Lapse Rates in AIRS Retrieved Temperatures in Cold Air Outbreaks

NASA Technical Reports Server (NTRS)

Fetzer, Eric J.; Kahn, Brian; Olsen, Edward T.; Fishbein, Evan

2004-01-01

The Atmospheric Infrared Sounder (AIRS) experiment, on NASA's Aqua spacecraft, uses a combination of infrared and microwave observations to retrieve cloud and surface properties, plus temperature and water vapor profiles comparable to radiosondes throughout the troposphere, for cloud cover up to 70%. The high spectral resolution of AIRS provides sensitivity to important information about the near-surface atmosphere and underlying surface. A preliminary analysis of AIRS temperature retrievals taken during January 2003 reveals extensive areas of superadiabatic lapse rates in the lowest kilometer of the atmosphere. These areas are found predominantly east of North America over the Gulf Stream, and, off East Asia over the Kuroshio Current. Accompanying the high lapse rates are low air temperatures, large sea-air temperature differences, and low relative humidities. Imagery from a Visible / Near Infrared instrument on the AIRS experiment shows accompanying clouds. These lines of evidence all point to shallow convection in the bottom layer of a cold air mass overlying warm water, with overturning driven by heat flow from ocean to atmosphere. An examination of operational radiosondes at six coastal stations in Japan shows AIRS to be oversensitive to lower tropospheric lapse rates due to systematically warm near-surface air temperatures. The bias in near-surface air temperature is seen to be independent of sea surface temperature, however. AIRS is therefore sensitive to air-sea temperature difference, but with a warm atmospheric bias. A regression fit to radiosondes is used to correct AIRS near-surface retrieved temperatures, and thereby obtain an estimate of the true atmosphere-ocean thermal contrast in five subtropical regions across the north Pacific. Moving eastward, we show a systematic shift in this air-sea temperature differences toward more isothermal conditions. These results, while preliminary, have implications for our understanding of heat flow from ocean to atmosphere. We anticipate future improvements in the AIRS retrieval algorithm will lead to improved understanding of the exchange of sensible and latent heat from ocean to atmosphere, and more realistic near-surface lapse rates.

Estimation and correction of different flavors of surface observation biases in ensemble Kalman filter

NASA Astrophysics Data System (ADS)

Lorente-Plazas, Raquel; Hacker, Josua P.; Collins, Nancy; Lee, Jared A.

2017-04-01

The impact of assimilating surface observations has been shown in several publications, for improving weather prediction inside of the boundary layer as well as the flow aloft. However, the assimilation of surface observations is often far from optimal due to the presence of both model and observation biases. The sources of these biases can be diverse: an instrumental offset, errors associated to the comparison of point-based observations and grid-cell average, etc. To overcome this challenge, a method was developed using the ensemble Kalman filter. The approach consists on representing each observation bias as a parameter. These bias parameters are added to the forward operator and they extend the state vector. As opposed to the observation bias estimation approaches most common in operational systems (e.g. for satellite radiances), the state vector and parameters are simultaneously updated by applying the Kalman filter equations to the augmented state. The method to estimate and correct the observation bias is evaluated using observing system simulation experiments (OSSEs) with the Weather Research and Forecasting (WRF) model. OSSEs are constructed for the conventional observation network including radiosondes, aircraft observations, atmospheric motion vectors, and surface observations. Three different kinds of biases are added to 2-meter temperature for synthetic METARs. From the simplest to more sophisticated, imposed biases are: (1) a spatially invariant bias, (2) a spatially varying bias proportional to topographic height differences between the model and the observations, and (3) bias that is proportional to the temperature. The target region characterized by complex terrain is the western U.S. on a domain with 30-km grid spacing. Observations are assimilated every 3 hours using an 80-member ensemble during September 2012. Results demonstrate that the approach is able to estimate and correct the bias when it is spatially invariant (experiment 1). More complex bias structure in experiments (2) and (3) are more difficult to estimate, but still possible. Estimated the parameter in experiments with unbiased observations results in spatial and temporal parameter variability about zero, and establishes a threshold on the accuracy of the parameter in further experiments. When the observations are biased, the mean parameter value is close to the true bias, but temporal and spatial variability in the parameter estimates is similar to the parameters used when estimating a zero bias in the observations. The distributions are related to other errors in the forecasts, indicating that the parameters are absorbing some of the forecast error from other sources. In this presentation we elucidate the reasons for the resulting parameter estimates, and their variability.

Development of a Climate-Data Record (CDR) of the Surface Temperature of the Greenland Ice Sheet

NASA Technical Reports Server (NTRS)

Hall, Dorthy K.; Comiso, Josefino C.; Shuman, Christopher A.; DiGirolamo, Nicolo E.; Stock, Larry V.

2010-01-01

Regional "clear sky" surface temperature increases since the early 1980s in the Arctic, measured using Advanced Very High Resolution Radiometer (AVHRR) infrared data, range from 0.57+/-0.02 deg C to 72+/-0.10 deg C per decade. Arctic warming has important implications for ice-sheet mass balance because much of the periphery of the Greenland Ice Sheet is already near 0 deg C during the melt season, and is thus vulnerable to rapid melting if temperatures continue to increase. An increase in melting of the ice sheet would accelerate sea-level rise, an issue affecting potentially billions of people worldwide. To quantify the ice-surface temperature (IST) of the Greenland Ice Sheet, and to provide an IST dataset of Greenland for modelers that provides uncertainties, we are developing a climate-data record (CDR) of daily "clear-sky" IST of the Greenland Ice Sheet, from 1982 to the present using AVHRR (1982 - present) and Moderate-Resolution Imaging Spectroradiometer (MODIS) data (2000 - present) at a resolution of approximately 5 km. Known issues being addressed in the production of the CDR are: time-series bias caused by cloud cover (surface temperatures can be different under clouds vs. clear areas) and cross-calibration in the overlap period between AVHRR instruments, and between AVHRR and MODIS instruments. Because of uncertainties, mainly due to clouds, time-series of satellite IST do not necessarily correspond with actual surface temperatures. The CDR will be validated by comparing results with automatic-weather station data and with satellite-derived surface-temperature products and biases will be calculated.

Sensitivity of the Antarctic surface mass balance to oceanic perturbations

NASA Astrophysics Data System (ADS)

Kittel, C.; Amory, C.; Agosta, C.; Fettweis, X.

2017-12-01

Regional climate models (RCMs) are suitable numerical tools to study the surface mass balance (SMB) of the wide polar ice sheets due to their high spatial resolution and polar-adapted physics. Nonetheless, RCMs are driven at their boundaries and over the ocean by reanalysis or global climate model (GCM) products and are thus influenced by potential biases in these large-scale fields. These biases can be significant for both the atmosphere and the sea surface conditions (i.e. sea ice concentration and sea surface temperature). With the RCM MAR, a set of sensitivity experiments has been realized to assess the direct response of the SMB of the Antarctic ice sheet to oceanic perturbations. MAR is forced by ERA-Interim and anomalies based on mean GCM biases are introduced in sea surface conditions. Results show significant increases (decreases) of liquid and solid precipitation due to biases related to warm (cold) oceans. As precipitation is mainly caused by low-pressure systems that intrude into the continent and do not penetrate far inland, coastal areas are more sensitive than inland regions. Furthermore, warm ocean representative biases lead to anomalies as large as anomalies simulated by other RCMs or GCMs for the end of the 21st century.

Temperature sensitivity of a numerical pollen forecast model

NASA Astrophysics Data System (ADS)

Scheifinger, Helfried; Meran, Ingrid; Szabo, Barbara; Gallaun, Heinz; Natali, Stefano; Mantovani, Simone

2016-04-01

Allergic rhinitis has become a global health problem especially affecting children and adolescence. Timely and reliable warning before an increase of the atmospheric pollen concentration means a substantial support for physicians and allergy suffers. Recently developed numerical pollen forecast models have become means to support the pollen forecast service, which however still require refinement. One of the problem areas concerns the correct timing of the beginning and end of the flowering period of the species under consideration, which is identical with the period of possible pollen emission. Both are governed essentially by the temperature accumulated before the entry of flowering and during flowering. Phenological models are sensitive to a bias of the temperature. A mean bias of -1°C of the input temperature can shift the entry date of a phenological phase for about a week into the future. A bias of such an order of magnitude is still possible in case of numerical weather forecast models. If the assimilation of additional temperature information (e.g. ground measurements as well as satellite-retrieved air / surface temperature fields) is able to reduce such systematic temperature deviations, the precision of the timing of phenological entry dates might be enhanced. With a number of sensitivity experiments the effect of a possible temperature bias on the modelled phenology and the pollen concentration in the atmosphere is determined. The actual bias of the ECMWF IFS 2 m temperature will also be calculated and its effect on the numerical pollen forecast procedure presented.

Thermal contact conductance as a method of rectification in bulk materials

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

Sayer, Robert A.

2016-08-01

A thermal rectifier that utilizes thermal expansion to directionally control interfacial conductance between two contacting surfaces is presented. The device consists of two thermal reservoirs contacting a beam with one rough and one smooth end. When the temperature of reservoir in contact with the smooth surface is raised, a similar temperature rise will occur in the beam, causing it to expand, thus increasing the contact pressure at the rough interface and reducing the interfacial contact resistance. However, if the temperature of the reservoir in contact with the rough interface is raised, the large contact resistance will prevent a similar temperaturemore » rise in the beam. As a result, the contact pressure will be marginally affected and the contact resistance will not change appreciably. Owing to the decreased contact resistance of the first scenario compared to the second, thermal rectification occurs. A parametric analysis is used to determine optimal device parameters including surface roughness, contact pressure, and device length. Modeling predicts that rectification factors greater than 2 are possible at thermal biases as small as 3 K. Lastly, thin surface coatings are discussed as a method to control the temperature bias at which maximum rectification occurs.« less

Introduction to CAUSES: Description of Weather and Climate Models and Their Near-Surface Temperature Errors in 5 day Hindcasts Near the Southern Great Plains

DOE PAGES

Morcrette, C. J.; Van Weverberg, K.; Ma, H. -Y.; ...

2018-02-16

We introduce the Clouds Above the United States and Errors at the Surface (CAUSES) project with its aim of better understanding the physical processes leading to warm screen temperature biases over the American Midwest in many numerical models. In this first of four companion papers, 11 different models, from nine institutes, perform a series of 5 day hindcasts, each initialized from reanalyses. After describing the common experimental protocol and detailing each model configuration, a gridded temperature data set is derived from observations and used to show that all the models have a warm bias over parts of the Midwest. Additionally,more » a strong diurnal cycle in the screen temperature bias is found in most models. In some models the bias is largest around midday, while in others it is largest during the night. At the Department of Energy Atmospheric Radiation Measurement Southern Great Plains (SGP) site, the model biases are shown to extend several kilometers into the atmosphere. Finally, to provide context for the companion papers, in which observations from the SGP site are used to evaluate the different processes contributing to errors there, it is shown that there are numerous locations across the Midwest where the diurnal cycle of the error is highly correlated with the diurnal cycle of the error at SGP. This suggests that conclusions drawn from detailed evaluation of models using instruments located at SGP will be representative of errors that are prevalent over a larger spatial scale.« less

Introduction to CAUSES: Description of Weather and Climate Models and Their Near-Surface Temperature Errors in 5 day Hindcasts Near the Southern Great Plains

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

Morcrette, C. J.; Van Weverberg, K.; Ma, H. -Y.

We introduce the Clouds Above the United States and Errors at the Surface (CAUSES) project with its aim of better understanding the physical processes leading to warm screen temperature biases over the American Midwest in many numerical models. In this first of four companion papers, 11 different models, from nine institutes, perform a series of 5 day hindcasts, each initialized from reanalyses. After describing the common experimental protocol and detailing each model configuration, a gridded temperature data set is derived from observations and used to show that all the models have a warm bias over parts of the Midwest. Additionally,more » a strong diurnal cycle in the screen temperature bias is found in most models. In some models the bias is largest around midday, while in others it is largest during the night. At the Department of Energy Atmospheric Radiation Measurement Southern Great Plains (SGP) site, the model biases are shown to extend several kilometers into the atmosphere. Finally, to provide context for the companion papers, in which observations from the SGP site are used to evaluate the different processes contributing to errors there, it is shown that there are numerous locations across the Midwest where the diurnal cycle of the error is highly correlated with the diurnal cycle of the error at SGP. This suggests that conclusions drawn from detailed evaluation of models using instruments located at SGP will be representative of errors that are prevalent over a larger spatial scale.« less

Introduction to CAUSES: Description of Weather and Climate Models and Their Near-Surface Temperature Errors in 5 day Hindcasts Near the Southern Great Plains

NASA Astrophysics Data System (ADS)

Morcrette, C. J.; Van Weverberg, K.; Ma, H.-Y.; Ahlgrimm, M.; Bazile, E.; Berg, L. K.; Cheng, A.; Cheruy, F.; Cole, J.; Forbes, R.; Gustafson, W. I.; Huang, M.; Lee, W.-S.; Liu, Y.; Mellul, L.; Merryfield, W. J.; Qian, Y.; Roehrig, R.; Wang, Y.-C.; Xie, S.; Xu, K.-M.; Zhang, C.; Klein, S.; Petch, J.

2018-03-01

We introduce the Clouds Above the United States and Errors at the Surface (CAUSES) project with its aim of better understanding the physical processes leading to warm screen temperature biases over the American Midwest in many numerical models. In this first of four companion papers, 11 different models, from nine institutes, perform a series of 5 day hindcasts, each initialized from reanalyses. After describing the common experimental protocol and detailing each model configuration, a gridded temperature data set is derived from observations and used to show that all the models have a warm bias over parts of the Midwest. Additionally, a strong diurnal cycle in the screen temperature bias is found in most models. In some models the bias is largest around midday, while in others it is largest during the night. At the Department of Energy Atmospheric Radiation Measurement Southern Great Plains (SGP) site, the model biases are shown to extend several kilometers into the atmosphere. Finally, to provide context for the companion papers, in which observations from the SGP site are used to evaluate the different processes contributing to errors there, it is shown that there are numerous locations across the Midwest where the diurnal cycle of the error is highly correlated with the diurnal cycle of the error at SGP. This suggests that conclusions drawn from detailed evaluation of models using instruments located at SGP will be representative of errors that are prevalent over a larger spatial scale.

Causes of the large warm bias in the Angola-Benguela Frontal Zone in the Norwegian Earth System Model

NASA Astrophysics Data System (ADS)

Koseki, Shunya; Keenlyside, Noel; Demissie, Teferi; Toniazzo, Thomas; Counillon, Francois; Bethke, Ingo; Ilicak, Mehmet; Shen, Mao-Lin

2018-06-01

We have investigated the causes of the sea surface temperature (SST) bias in the Angola-Benguela Frontal Zone (ABFZ) of the southeastern Atlantic Ocean simulated by the Norwegian Earth System Model (NorESM). Similar to other coupled-models, NorESM has a warm SST bias in the ABFZ of up to 8 °C in the annual mean. Our analysis of NorESM reveals that a cyclonic surface wind bias over the ABFZ drives a locally excessively strong southward (0.05 m/s (relative to observation)) Angola Current displacing the ABFZ southward. A series of uncoupled stand-alone atmosphere and ocean model simulations are performed to investigate the cause of the coupled model bias. The stand-alone atmosphere model driven with observed SST exhibits a similar cyclonic surface circulation bias; while the stand-alone ocean model forced with the reanalysis data produces a warm SST in the ABFZ with a magnitude approximately half of that in the coupled NorESM simulation. An additional uncoupled sensitivity experiment shows that the atmospheric model's local negative surface wind curl generates anomalously strong Angola Current at the ocean surface. Consequently, this contributes to the warm SST bias in the ABFZ by 2 °C (compared to the reanalysis forced simulation). There is no evidence that local air-sea feedbacks among wind stress curl, SST, and sea level pressure (SLP) affect the ABFZ SST bias. Turbulent surface heat flux differences between coupled and uncoupled experiments explain the remaining 2 °C warm SST bias in NorESM. Ocean circulation, upwelling and turbulent heat flux errors all modulate the intensity and the seasonality of the ABFZ errors.

Impact of new land boundary conditions from Moderate Resolution Imaging Spectroradiometer (MODIS) data on the climatology of land surface variables

NASA Astrophysics Data System (ADS)

Tian, Y.; Dickinson, R. E.; Zhou, L.; Shaikh, M.

2004-10-01

This paper uses the Community Land Model (CLM2) to investigate the improvements of a new land surface data set, created from multiple high-quality collection 4 Moderate Resolution Imaging Spectroradiometer data of leaf area index (LAI), plant functional type, and vegetation continuous fields, for modeled land surface variables. The previous land surface data in CLM2 underestimate LAI and overestimate the percent cover of grass/crop over most of the global area. For snow-covered regions with abundant solar energy the increased LAI and percent cover of tree/shrub in the new data set decreases the percent cover of surface snow and increases net radiation and thus increases ground and surface (2-m) air temperature, which reduces most of the model cold bias. For snow-free regions the increased LAI and changes in the percent cover from grass/crop to tree or shrub decrease ground and surface air temperature by converting most of the increased net radiation to latent heat flux, which decreases the model warm bias. Furthermore, the new data set greatly decreases ground evaporation and increases canopy evapotranspiration over tropical forests, especially during the wet season, owing to the higher LAI and more trees in the new data set. It makes the simulated ground evaporation and canopy evapotranspiration closer to reality and also reduces the warm biases over tropical regions.

Quality and sensitivity of high-resolution numerical simulation of urban heat islands

NASA Astrophysics Data System (ADS)

Li, Dan; Bou-Zeid, Elie

2014-05-01

High-resolution numerical simulations of the urban heat island (UHI) effect with the widely-used Weather Research and Forecasting (WRF) model are assessed. Both the sensitivity of the results to the simulation setup, and the quality of the simulated fields as representations of the real world, are investigated. Results indicate that the WRF-simulated surface temperatures are more sensitive to the planetary boundary layer (PBL) scheme choice during nighttime, and more sensitive to the surface thermal roughness length parameterization during daytime. The urban surface temperatures simulated by WRF are also highly sensitive to the urban canopy model (UCM) used. The implementation in this study of an improved UCM (the Princeton UCM or PUCM) that allows the simulation of heterogeneous urban facets and of key hydrological processes, together with the so-called CZ09 parameterization for the thermal roughness length, significantly reduce the bias (<1.5 °C) in the surface temperature fields as compared to satellite observations during daytime. The boundary layer potential temperature profiles are captured by WRF reasonable well at both urban and rural sites; the biases in these profiles relative to aircraft-mounted senor measurements are on the order of 1.5 °C. Changing UCMs and PBL schemes does not alter the performance of WRF in reproducing bulk boundary layer temperature profiles significantly. The results illustrate the wide range of urban environmental conditions that various configurations of WRF can produce, and the significant biases that should be assessed before inferences are made based on WRF outputs. The optimal set-up of WRF-PUCM developed in this paper also paves the way for a confident exploration of the city-scale impacts of UHI mitigation strategies in the companion paper (Li et al 2014).

Evaluation of four global reanalysis products using in situ observations in the Amundsen Sea Embayment, Antarctica

NASA Astrophysics Data System (ADS)

Jones, R. W.; Renfrew, I. A.; Orr, A.; Webber, B. G. M.; Holland, D. M.; Lazzara, M. A.

2016-06-01

The glaciers within the Amundsen Sea Embayment (ASE), West Antarctica, are amongst the most rapidly retreating in Antarctica. Meteorological reanalysis products are widely used to help understand and simulate the processes causing this retreat. Here we provide an evaluation against observations of four of the latest global reanalysis products within the ASE region—the European Centre for Medium-Range Weather Forecasts Interim Reanalysis (ERA-I), Japanese 55-year Reanalysis (JRA-55), Climate Forecast System Reanalysis (CFSR), and Modern Era Retrospective-Analysis for Research and Applications (MERRA). The observations comprise data from four automatic weather stations (AWSs), three research vessel cruises, and a new set of 38 radiosondes all within the period 2009-2014. All four reanalyses produce 2 m temperature fields that are colder than AWS observations, with the biases varying from approximately -1.8°C (ERA-I) to -6.8°C (MERRA). Over the Amundsen Sea, spatially averaged summertime biases are between -0.4°C (JRA-55) and -2.1°C (MERRA) with notably larger cold biases close to the continent (up to -6°C) in all reanalyses. All four reanalyses underestimate near-surface wind speed at high wind speeds (>15 m s-1) and exhibit dry biases and relatively large root-mean-square errors (RMSE) in specific humidity. A comparison to the radiosonde soundings shows that the cold, dry bias at the surface extends into the lower troposphere; here ERA-I and CFSR reanalyses provide the most accurate profiles. The reanalyses generally contain larger temperature and humidity biases, (and RMSE) when a temperature inversion is observed, and contain larger wind speed biases (~2 to 3 m s-1), when a low-level jet is observed.

Assessing recent warming using instrumentally homogeneous sea surface temperature records.

PubMed

Hausfather, Zeke; Cowtan, Kevin; Clarke, David C; Jacobs, Peter; Richardson, Mark; Rohde, Robert

2017-01-01

Sea surface temperature (SST) records are subject to potential biases due to changing instrumentation and measurement practices. Significant differences exist between commonly used composite SST reconstructions from the National Oceanic and Atmospheric Administration's Extended Reconstruction Sea Surface Temperature (ERSST), the Hadley Centre SST data set (HadSST3), and the Japanese Meteorological Agency's Centennial Observation-Based Estimates of SSTs (COBE-SST) from 2003 to the present. The update from ERSST version 3b to version 4 resulted in an increase in the operational SST trend estimate during the last 19 years from 0.07° to 0.12°C per decade, indicating a higher rate of warming in recent years. We show that ERSST version 4 trends generally agree with largely independent, near-global, and instrumentally homogeneous SST measurements from floating buoys, Argo floats, and radiometer-based satellite measurements that have been developed and deployed during the past two decades. We find a large cooling bias in ERSST version 3b and smaller but significant cooling biases in HadSST3 and COBE-SST from 2003 to the present, with respect to most series examined. These results suggest that reported rates of SST warming in recent years have been underestimated in these three data sets.

Impact of tropical Atlantic sea-surface temperature biases on the simulated atmospheric circulation and precipitation over the Atlantic region: An ECHAM6 model study

NASA Astrophysics Data System (ADS)

Eichhorn, Astrid; Bader, Jürgen

2017-09-01

As many coupled atmosphere-ocean general circulation models, the coupled Earth System Model developed at the Max Planck Institute for Meteorology suffers from severe sea-surface temperature (SST) biases in the tropical Atlantic. We performed a set of SST sensitivity experiments with its atmospheric model component ECHAM6 to understand the impact of tropical Atlantic SST biases on atmospheric circulation and precipitation. The model was forced by a climatology of observed global SSTs to focus on simulated seasonal and annual mean state climate. Through the superposition of varying tropical Atlantic bias patterns extracted from the MPI-ESM on top of the control field, this study investigates the relevance of the seasonal variation and spatial structure of tropical Atlantic biases for the simulated response. Results show that the position and structure of the Intertropical Convergence Zone (ITCZ) across the Atlantic is significantly affected, exhibiting a dynamically forced shift of annual mean precipitation maximum to the east of the Atlantic basin as well as a southward shift of the oceanic rain belt. The SST-induced changes in the ITCZ in turn affect seasonal rainfall over adjacent continents. However not only the ITCZ position but also other effects arising from biases in tropical Atlantic SSTs, e.g. variations in the wind field, change the simulation of precipitation over land. The seasonal variation and spatial pattern of tropical Atlantic SST biases turns out to be crucial for the simulated atmospheric response and is essential for analyzing the contribution of SST biases to coupled model mean state biases. Our experiments show that MPI-ESM mean-state biases in the Atlantic sector are mainly driven by SST biases in the tropical Atlantic while teleconnections from other basins seem to play a minor role.

Evaluation of WRF Simulations With Different Selections of Subgrid Orographic Drag Over the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Zhou, X.; Beljaars, A.; Wang, Y.; Huang, B.; Lin, C.; Chen, Y.; Wu, H.

2017-09-01

Weather Research and Forecasting (WRF) simulations with different selections of subgrid orographic drag over the Tibetan Plateau have been evaluated with observation and ERA-Interim reanalysis. Results show that the subgrid orographic drag schemes, especially the turbulent orographic form drag (TOFD) scheme, efficiently reduce the 10 m wind speed bias and RMS error with respect to station measurements. With the combination of gravity wave, flow blocking and TOFD schemes, wind speed is simulated more realistically than with the individual schemes only. Improvements are also seen in the 2 m air temperature and surface pressure. The gravity wave drag, flow blocking drag, and TOFD schemes combined have the smallest station mean bias (-2.05°C in 2 m air temperature and 1.27 hPa in surface pressure) and RMS error (3.59°C in 2 m air temperature and 2.37 hPa in surface pressure). Meanwhile, the TOFD scheme contributes more to the improvements than the gravity wave drag and flow blocking schemes. The improvements are more pronounced at low levels of the atmosphere than at high levels due to the stronger drag enhancement on the low-level flow. The reduced near-surface cold bias and high-pressure bias over the Tibetan Plateau are the result of changes in the low-level wind components associated with the geostrophic balance. The enhanced drag directly leads to weakened westerlies but also enhances the a-geostrophic flow in this case reducing (enhancing) the northerlies (southerlies), which bring more warm air across the Himalaya Mountain ranges from South Asia (bring less cold air from the north) to the interior Tibetan Plateau.

Climate applications for NOAA 1/4° Daily Optimum Interpolation Sea Surface Temperature

NASA Astrophysics Data System (ADS)

Boyer, T.; Banzon, P. V. F.; Liu, G.; Saha, K.; Wilson, C.; Stachniewicz, J. S.

2015-12-01

Few sea surface temperature (SST) datasets from satellites have the long temporal span needed for climate studies. The NOAA Daily Optimum Interpolation Sea Surface Temperature (DOISST) on a 1/4° grid, produced at National Centers for Environmental Information, is based primarily on SSTs from the Advanced Very High Resolution Radiometer (AVHRR), available from 1981 to the present. AVHRR data can contain biases, particularly when aerosols are present. Over the three decade span, the largest departure of AVHRR SSTs from buoy temperatures occurred during the Mt Pinatubo and El Chichon eruptions. Therefore, in DOISST, AVHRR SSTs are bias-adjusted to match in situ SSTs prior to interpolation. This produces a consistent time series of complete SST fields that is suitable for modelling and investigating local climate phenomena like El Nino or the Pacific warm blob in a long term context. Because many biological processes and animal distributions are temperature dependent, there are also many ecological uses of DOISST (e.g., coral bleaching thermal stress, fish and marine mammal distributions), thereby providing insights into resource management in a changing ocean. The advantages and limitations of using DOISST for different applications will be discussed.

Current rectification for transport of room-temperature ionic liquids through conical nanopores

DOE PAGES

Jiang, Xikai; Liu, Ying; Qiao, Rui

2016-02-09

Here, we studied the transport of room-temperature ionic liquids (RTILs) through charged conical nanopores using a Landau-Ginzburg-type continuum model that takes steric effect and strong ion-ion correlations into account. When the surface charge is uniform on the pore wall, weak current rectification is observed. When the charge density near the pore base is removed, the ionic current is greatly suppressed under negative bias voltage while nearly unchanged under positive bias voltage, thereby leading to enhanced current rectification. These predictions agree qualitatively with prior experimental observations, and we elucidated them by analyzing the different components of the ionic current and themore » structural changes of electrical double layers (EDLs) at the pore tip under different bias voltages and surface charge patterns. These analyses reveal that the different modifications of the EDL structure near the pore tip by the positive and negative bias voltages cause the current rectification and the observed dependence on the distribution of surface charge on the pore wall. The fact that the current rectification phenomena are captured qualitatively by the simple model originally developed for describing EDLs at equilibrium conditions suggests that this model may be promising for understanding the ionic transport under nonequilibrium conditions when the EDL structure is strongly perturbed by external fields.« less

Distinguishing magnetic blocking and surface spin-glass freezing in nickel ferrite nanoparticles

NASA Astrophysics Data System (ADS)

Nadeem, K.; Krenn, H.; Traussing, T.; Letofsky-Papst, I.

2011-01-01

Nickel ferrite nanoparticles dispersed in SiO2 matrix have been synthesized by sol-gel method. Structural analysis has been performed by using x-ray diffraction and transmission electron microscopy. Magnetic properties have been investigated by using superconducting quantum interference device magnetometry. In addition to the average blocking temperature peak at TB=120 K measured by a zero field cooled temperature scan of the dc susceptibility, an additional hump near 15 K is observed. Temperature dependent out-of-phase ac susceptibility shows the same features: one broad peak at high temperature and a second narrow peak at low temperature. The high temperature peak corresponds to magnetic blocking of individual nanoparticles, while the low temperature peak is attributed to surface spin-glass freezing which becomes dominant for decreasing particle diameter. To prove the dynamics of the spin (dis)order in both regimes of freezing and blocking, the frequency dependent ac susceptibility is investigated under a biasing dc field. The frequency shift in the "frozen" low-temperature ac susceptibility peak is fitted to a dynamic scaling law with a critical exponent zv=7.5, which indicates a spin-glass phase. Exchange bias is turned on at low temperature which signifies the existence of a strong core-shell interaction. Aging and memory effects are further unique fingerprints of a spin-glass freezing on the surface of isolated magnetic nanoparticles.

Robust isothermal electric control of exchange bias at room temperature

NASA Astrophysics Data System (ADS)

Binek, Christian

2011-03-01

Voltage-controlled spintronics is of particular importance to continue progress in information technology through reduced power consumption, enhanced processing speed, integration density, and functionality in comparison with present day CMOS electronics. Almost all existing and prototypical solid-state spintronic devices rely on tailored interface magnetism, enabling spin-selective transmission or scattering of electrons. Controlling magnetism at thin-film interfaces, preferably by purely electrical means, is a key challenge to better spintronics. Currently, most attempts to electrically control magnetism focus on potentially large magnetoelectric effects of multiferroics. We report on our interest in magnetoelectric Cr 2 O3 (chromia). Robust isothermal electric control of exchange bias is achieved at room temperature in perpendicular anisotropic Cr 2 O3 (0001)/CoPd exchange bias heterostructures. This discovery promises significant implications for potential spintronics. From the perspective of basic science, our finding serves as macroscopic evidence for roughness-insensitive and electrically controllable equilibrium boundary magnetization in magnetoelectric antiferromagnets. The latter evolves at chromia (0001) surfaces and interfaces when chromia is in one of its two degenerate antiferromagnetic single domain states selected via magnetoelectric annealing. Theoretical insight into the boundary magnetization and its role in electrically controlled exchange bias is gained from first-principles calculations and general symmetry arguments. Measurements of spin-resolved ultraviolet photoemission, magnetometry at Cr 2 O3 (0001) surfaces, and detailed investigations of the unique exchange bias properties of Cr 2 O3 (0001)/CoPd including its electric controllability provide macroscopically averaged information about the boundary magnetization of chromia. Laterally resolved X-ray PEEM and temperature dependent MFM reveal detailed microscopic information of the chromia (0001) surface magnetization and provide a coherent interpretation of our results on robust isothermal electric control of exchange bias. The latter promise a new route towards purely voltage-controlled spintronics and an exciting way to electrically control magnetism. Financial support by NSF through Nebraska MRSEC, SRC/NSF Supplement to Nebraska MRSEC, CAREER DMR-0547887, NRI, and Cottrell Research Corporation.

Using ERA-Interim reanalysis for creating datasets of energy-relevant climate variables

NASA Astrophysics Data System (ADS)

Jones, Philip D.; Harpham, Colin; Troccoli, Alberto; Gschwind, Benoit; Ranchin, Thierry; Wald, Lucien; Goodess, Clare M.; Dorling, Stephen

2017-07-01

The construction of a bias-adjusted dataset of climate variables at the near surface using ERA-Interim reanalysis is presented. A number of different, variable-dependent, bias-adjustment approaches have been proposed. Here we modify the parameters of different distributions (depending on the variable), adjusting ERA-Interim based on gridded station or direct station observations. The variables are air temperature, dewpoint temperature, precipitation (daily only), solar radiation, wind speed, and relative humidity. These are available on either 3 or 6 h timescales over the period 1979-2016. The resulting bias-adjusted dataset is available through the Climate Data Store (CDS) of the Copernicus Climate Change Data Store (C3S) and can be accessed at present from ftp://ecem.climate.copernicus.eu. The benefit of performing bias adjustment is demonstrated by comparing initial and bias-adjusted ERA-Interim data against gridded observational fields.

Improving aerosol vertical retrieval for NWP application: Studying the impact of IR-sensed aerosol on data assimilation systems.

NASA Astrophysics Data System (ADS)

Oyola, Mayra; Marquis, Jared; Ruston, Benjamin; Campbell, James; Baker, Nancy; Westphal, Douglas; Zhang, Jianglong; Hyer, Edward

2017-04-01

Radiometric measurements from passive infrared (IR) sensors are important in numerical weather prediction (NWP) because they are sensitive to surface temperatures and atmospheric temperature profiles. However, these measurements are also sensitive to absorbing and scattering constituents in the atmosphere. Dust aerosols absorb in the IR and are found over many global regions with irregular spatial and temporal frequency. Retrievals of temperature using IR data are thus vulnerable to dust-IR radiance biases, most notably over tropical oceans where accurate surface and atmospheric temperatures are critical to accurate prediction of tropical cyclone development. Previous studies have shown that dust aerosols can bias retrieved brightness temperatures (BT) by up to 10K in some IR channels that are assimilated to constrain atmospheric temperature and water vapor profiles. Other BT-derived parameters such as sea surface temperatures (SSTs) are susceptible to negative biases of at least 1K or higher, which conflicts with the accuracy requirement for most research and operational applications (i.e., +/- 0.3 K). This problem is not limited to just satellite retrievals. BT bias also impacts the incorporation of background fields from NWP analyses in data assimilation (DA) systems. The effect of aerosols on IR fluxes at the ocean surface is a function of both aerosol loading and vertical profile. Therefore, knowledge of the aerosol vertical distribution, and understanding of how well this distribution is captured by NWP models, is necessary to ensuring proper treatment of aerosol-affected radiances in both retrieval and data assimilation. This understanding can be achieved by conducting modeling studies and by the exploitation of a robust observational dataset, such as satellite-based lidar profiling, which can be used to characterize aerosol type and distribution. In this talk, we describe such an application using the Navy Aerosol Analysis Prediction System (NAAPS) and Naval Research Laboratory (NRL) Atmospheric Variational Data Assimilation System (NAVDAS). We describe the impact of aerosol-biased radiances on operational DA, and thus the quantitative impact of dust on model profiles of temperature and water vapor mixing ratio before and after data assimilation, using collocated hyperspectral Cross-track Infrared Sounder (CrIs) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) observations over the Tropical Atlantic. We then describe how the NAVDAS radiance assimilation system responds when coupled with NAAPS dust concentration fields, and thus how the model representation of dust compares with observations.. The result is a conceptual description of how IR-absorbing dust impacts radiance DA for operational weather modeling, and a first-order description of how adept current aerosol transport models are for providing compulsory corrections.

Simulated cold bias being improved by using MODIS time-varying albedo in the Tibetan Plateau in WRF model

NASA Astrophysics Data System (ADS)

Meng, X.; Lyu, S.; Zhang, T.; Zhao, L.; Li, Z.; Han, B.; Li, S.; Ma, D.; Chen, H.; Ao, Y.; Luo, S.; Shen, Y.; Guo, J.; Wen, L.

2018-04-01

Systematic cold biases exist in the simulation for 2 m air temperature in the Tibetan Plateau (TP) when using regional climate models and global atmospheric general circulation models. We updated the albedo in the Weather Research and Forecasting (WRF) Model lower boundary condition using the Global LAnd Surface Satellite Moderate-Resolution Imaging Spectroradiometer albedo products and demonstrated evident improvement for cold temperature biases in the TP. It is the large overestimation of albedo in winter and spring in the WRF model that resulted in the large cold temperature biases. The overestimated albedo was caused by the simulated precipitation biases and over-parameterization of snow albedo. Furthermore, light-absorbing aerosols can result in a large reduction of albedo in snow and ice cover. The results suggest the necessity of developing snow albedo parameterization using observations in the TP, where snow cover and melting are very different from other low-elevation regions, and the influence of aerosols should be considered as well. In addition to defining snow albedo, our results show an urgent call for improving precipitation simulation in the TP.

Comparative study of ITO and TiN fabricated by low-temperature RF biased sputtering

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

Simon, Daniel K., E-mail: daniel.simon@namlab.com; Schenk, Tony; Dirnstorfer, Ingo

2016-03-15

Radio frequency (RF) biasing induced by a second plasma source at the substrate is applied to low-temperature sputtering processes for indium tin oxide (ITO) and titanium nitride (TiN) thin films. Investigations on crystal structure and surface morphology show that RF-biased substrate plasma processes result in a changed growth regime with different grain sizes and orientations than those produced by processes without a substrate bias. The influence of the RF bias is shown comparatively for reactive RF-sputtered ITO and reactive direct-current-sputtered TiN. The ITO layers exhibit an improved electrical resistivity of 0.5 mΩ cm and an optical absorption coefficient of 0.5 × 10{sup 4 }cm{supmore » −1} without substrate heating. Room-temperature sputtered TiN layers are deposited that possess a resistivity (0.1 mΩ cm) of 3 orders of magnitude lower than, and a density (5.4 g/cm{sup 3}) up to 45% greater than, those obtained from layers grown using the standard process without a substrate plasma.« less

Diagnostic and model dependent uncertainty of simulated Tibetan permafrost area

USGS Publications Warehouse

Wang, A.; Moore, J.C.; Cui, Xingquan; Ji, D.; Li, Q.; Zhang, N.; Wang, C.; Zhang, S.; Lawrence, D.M.; McGuire, A.D.; Zhang, W.; Delire, C.; Koven, C.; Saito, K.; MacDougall, A.; Burke, E.; Decharme, B.

2016-01-01

 We perform a land-surface model intercomparison to investigate how the simulation of permafrost area on the Tibetan Plateau (TP) varies among six modern stand-alone land-surface models (CLM4.5, CoLM, ISBA, JULES, LPJ-GUESS, UVic). We also examine the variability in simulated permafrost area and distribution introduced by five different methods of diagnosing permafrost (from modeled monthly ground temperature, mean annual ground and air temperatures, air and surface frost indexes). There is good agreement (99 to 135  ×  104 km2) between the two diagnostic methods based on air temperature which are also consistent with the observation-based estimate of actual permafrost area (101  × 104 km2). However the uncertainty (1 to 128  ×  104 km2) using the three methods that require simulation of ground temperature is much greater. Moreover simulated permafrost distribution on the TP is generally only fair to poor for these three methods (diagnosis of permafrost from monthly, and mean annual ground temperature, and surface frost index), while permafrost distribution using air-temperature-based methods is generally good. Model evaluation at field sites highlights specific problems in process simulations likely related to soil texture specification, vegetation types and snow cover. Models are particularly poor at simulating permafrost distribution using the definition that soil temperature remains at or below 0 °C for 24 consecutive months, which requires reliable simulation of both mean annual ground temperatures and seasonal cycle, and hence is relatively demanding. Although models can produce better permafrost maps using mean annual ground temperature and surface frost index, analysis of simulated soil temperature profiles reveals substantial biases. The current generation of land-surface models need to reduce biases in simulated soil temperature profiles before reliable contemporary permafrost maps and predictions of changes in future permafrost distribution can be made for the Tibetan Plateau.

Diagnostic and model dependent uncertainty of simulated Tibetan permafrost area

NASA Astrophysics Data System (ADS)

Wang, W.; Rinke, A.; Moore, J. C.; Cui, X.; Ji, D.; Li, Q.; Zhang, N.; Wang, C.; Zhang, S.; Lawrence, D. M.; McGuire, A. D.; Zhang, W.; Delire, C.; Koven, C.; Saito, K.; MacDougall, A.; Burke, E.; Decharme, B.

2016-02-01

We perform a land-surface model intercomparison to investigate how the simulation of permafrost area on the Tibetan Plateau (TP) varies among six modern stand-alone land-surface models (CLM4.5, CoLM, ISBA, JULES, LPJ-GUESS, UVic). We also examine the variability in simulated permafrost area and distribution introduced by five different methods of diagnosing permafrost (from modeled monthly ground temperature, mean annual ground and air temperatures, air and surface frost indexes). There is good agreement (99 to 135 × 104 km2) between the two diagnostic methods based on air temperature which are also consistent with the observation-based estimate of actual permafrost area (101 × 104 km2). However the uncertainty (1 to 128 × 104 km2) using the three methods that require simulation of ground temperature is much greater. Moreover simulated permafrost distribution on the TP is generally only fair to poor for these three methods (diagnosis of permafrost from monthly, and mean annual ground temperature, and surface frost index), while permafrost distribution using air-temperature-based methods is generally good. Model evaluation at field sites highlights specific problems in process simulations likely related to soil texture specification, vegetation types and snow cover. Models are particularly poor at simulating permafrost distribution using the definition that soil temperature remains at or below 0 °C for 24 consecutive months, which requires reliable simulation of both mean annual ground temperatures and seasonal cycle, and hence is relatively demanding. Although models can produce better permafrost maps using mean annual ground temperature and surface frost index, analysis of simulated soil temperature profiles reveals substantial biases. The current generation of land-surface models need to reduce biases in simulated soil temperature profiles before reliable contemporary permafrost maps and predictions of changes in future permafrost distribution can be made for the Tibetan Plateau.

A comprehensive approach for the simulation of the Urban Heat Island effect with the WRF/SLUCM modeling system: The case of Athens (Greece)

NASA Astrophysics Data System (ADS)

Giannaros, Christos; Nenes, Athanasios; Giannaros, Theodore M.; Kourtidis, Konstantinos; Melas, Dimitrios

2018-03-01

This study presents a comprehensive modeling approach for simulating the spatiotemporal distribution of urban air temperatures with a modeling system that includes the Weather Research and Forecasting (WRF) model and the Single-Layer Urban Canopy Model (SLUCM) with a modified treatment of the impervious surface temperature. The model was applied to simulate a 3-day summer heat wave event over the city of Athens, Greece. The simulation, using default SLUCM parameters, is capable of capturing the observed diurnal variation of urban temperatures and the Urban Heat Island (UHI) in the greater Athens Area (GAA), albeit with systematic biases that are prominent during nighttime hours. These biases are particularly evident over low-intensity residential areas, and they are associated with the surface and urban canopy properties representing the urban environment. A series of sensitivity simulations unravels the importance of the sub-grid urban fraction parameter, surface albedo, and street canyon geometry in the overall causation and development of the UHI effect. The sensitivities are then used to determine optimal values of the street canyon geometry, which reproduces the observed temperatures throughout the simulation domain. The optimal parameters, apart from considerably improving model performance (reductions in mean temperature bias from 0.30 °C to 1.58 °C), are also consistent with actual city building characteristics - which gives confidence that the model set-up is robust, and can be used to study the UHI in the GAA in the anticipated warmer conditions in the future.

In-flight validation and recovery of water surface temperature with Landsat-5 thermal infrared data using an automated high-altitude lake validation site at Lake Tahoe

USGS Publications Warehouse

Hook, S.J.; Chander, G.; Barsi, J.A.; Alley, R.E.; Abtahi, A.; Palluconi, Frank Don; Markham, B.L.; Richards, R.C.; Schladow, S.G.; Helder, D.L.

2004-01-01

The absolute radiometric accuracy of the thermal infrared band (B6) of the Thematic Mapper (TM) instrument on the Landsat-5 (L5) satellite was assessed over a period of approximately four years using data from the Lake Tahoe automated validation site (California-Nevada). The Lake Tahoe site was established in July 1999, and measurements of the skin and bulk temperature have been made approximately every 2 min from four permanently moored buoys since mid-1999. Assessment involved using a radiative transfer model to propagate surface skin temperature measurements made at the time of the L5 overpass to predict the at-sensor radiance. The predicted radiance was then convolved with the L5B6 system response function to obtain the predicted L5B6 radiance, which was then compared with the radiance measured by L5B6. Twenty-four cloud-free scenes acquired between 1999 and 2003 were used in the analysis with scene temperatures ranging between 4/spl deg/C and 22/spl deg/C. The results indicate L5B6 had a radiance bias of 2.5% (1.6/spl deg/C) in late 1999, which gradually decreased to 0.8% (0.5/spl deg/C) in mid-2002. Since that time, the bias has remained positive (predicted minus measured) and between 0.3% (0.2/spl deg/C) and 1.4% (0.9/spl deg/C). The cause for the cold bias (L5 radiances are lower than expected) is unresolved, but likely related to changes in instrument temperature associated with changes in instrument usage. The in situ data were then used to develop algorithms to recover the skin and bulk temperature of the water by regressing the L5B6 radiance and the National Center for Environmental Prediction (NCEP) total column water data to either the skin or bulk temperature. Use of the NCEP data provides an alternative approach to the split-window approach used with instruments that have two thermal infrared bands. The results indicate the surface skin and bulk temperature can be recovered with a standard error of 0.6/spl deg/C. This error is larger than errors obtained with other instruments due, in part, to the calibration bias. L5 provides the only long-duration high spatial resolution thermal infrared measurements of the land surface. If these data are to be used effectively in studies designed to monitor change, it is essential to continue to monitor instrument performance in-flight and develop quantitative algorithms for recovering surface temperature.

Surface Winds and Dust Biases in Climate Models

NASA Astrophysics Data System (ADS)

Evan, A. T.

2018-01-01

An analysis of North African dust from models participating in the Fifth Climate Models Intercomparison Project (CMIP5) suggested that, when forced by observed sea surface temperatures, these models were unable to reproduce any aspects of the observed year-to-year variability in dust from North Africa. Consequently, there would be little reason to have confidence in the models' projections of changes in dust over the 21st century. However, no subsequent study has elucidated the root causes of the disagreement between CMIP5 and observed dust. Here I develop an idealized model of dust emission and then use this model to show that, over North Africa, such biases in CMIP5 models are due to errors in the surface wind fields and not due to the representation of dust emission processes. These results also suggest that because the surface wind field over North Africa is highly spatially autocorrelated, intermodel differences in the spatial structure of dust emission have little effect on the relative change in year-to-year dust emission over the continent. I use these results to show that similar biases in North African dust from the NASA Modern Era Retrospective analysis for Research and Applications (MERRA) version 2 surface wind field biases but that these wind biases were not present in the first version of MERRA.

On the effect of surface emissivity on temperature retrievals. [for meteorology

NASA Technical Reports Server (NTRS)

Kornfield, J.; Susskind, J.

1977-01-01

The paper is concerned with errors in temperature retrieval caused by incorrectly assuming that surface emissivity is equal to unity. An error equation that applies to present-day atmospheric temperature sounders is derived, and the bias errors resulting from various emissivity discrepancies are calculated. A model of downward flux is presented and used to determine the effective downward flux. In the 3.7-micron region of the spectrum, emissivities of 0.6 to 0.9 have been observed over land. At a surface temperature of 290 K, if the true emissivity is 0.6 and unit emissivity is assumed, the error would be approximately 11 C. In the 11-micron region, the maximum deviation of the surface emissivity from unity was 0.05.

Lessons Learned from Assimilating Altimeter Data into a Coupled General Circulation Model with the GMAO Augmented Ensemble Kalman Filter

NASA Technical Reports Server (NTRS)

Keppenne, Christian; Vernieres, Guillaume; Rienecker, Michele; Jacob, Jossy; Kovach, Robin

2011-01-01

Satellite altimetry measurements have provided global, evenly distributed observations of the ocean surface since 1993. However, the difficulties introduced by the presence of model biases and the requirement that data assimilation systems extrapolate the sea surface height (SSH) information to the subsurface in order to estimate the temperature, salinity and currents make it difficult to optimally exploit these measurements. This talk investigates the potential of the altimetry data assimilation once the biases are accounted for with an ad hoc bias estimation scheme. Either steady-state or state-dependent multivariate background-error covariances from an ensemble of model integrations are used to address the problem of extrapolating the information to the sub-surface. The GMAO ocean data assimilation system applied to an ensemble of coupled model instances using the GEOS-5 AGCM coupled to MOM4 is used in the investigation. To model the background error covariances, the system relies on a hybrid ensemble approach in which a small number of dynamically evolved model trajectories is augmented on the one hand with past instances of the state vector along each trajectory and, on the other, with a steady state ensemble of error estimates from a time series of short-term model forecasts. A state-dependent adaptive error-covariance localization and inflation algorithm controls how the SSH information is extrapolated to the sub-surface. A two-step predictor corrector approach is used to assimilate future information. Independent (not-assimilated) temperature and salinity observations from Argo floats are used to validate the assimilation. A two-step projection method in which the system first calculates a SSH increment and then projects this increment vertically onto the temperature, salt and current fields is found to be most effective in reconstructing the sub-surface information. The performance of the system in reconstructing the sub-surface fields is particularly impressive for temperature, but not as satisfactory for salt.

Synthesis and magnetic properties of bundled and dispersed Co{sub 3}O{sub 4} nanowires

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

Zhang, B.B.; Wang, P.F.; Xu, J.C.

Highlights: • Co{sub 3}O{sub 4} nanowires possessed the same diameter and the different interwires distance. • All samples possessed antiferromagnetism and superparamagnetism at high temperature. • The exchange bias effect was observed at low temperature. • The surface spin coupling restrained the surface effect of magnetic nanostructures. - Abstract: The magnetic Co{sub 3}O{sub 4} nanowires were synthesized using the templates of SBA-15, and then the well-dispersed nanowires (D-wires) were separated from the bundled ordered nanowires (B-wires) with the centrifugal technique. TEM images indicated that D-wires were highly dispersed Co{sub 3}O{sub 4} nanowires and B-wires existed in bundles. All samples possessedmore » the antiferromagnetism and superparamagnetism at high temperature. After revealing the intrinsic magnetic properties of Co{sub 3}O{sub 4} nanowires with D-wires, the magnetic behavior of B-wires was discussed in detail, and then the magnetic interaction between neighboring nanowires could be deduced. The exchange bias effect from the body Co{sub 3}O{sub 4} antiferromagnetism and surface ferromagnetism was observed at low temperature. The magnetization of B-wires was higher than that of D-wires, which was attributed to the constraint of the surface spin coupling between the neighboring nanowires to the surface affect of nanostructures.« less

Improving Representations of Near-Surface Permafrost and Soil Temperature Profiles in the Regional Arctic System Model (RASM)

NASA Astrophysics Data System (ADS)

Gergel, D. R.; Hamman, J.; Nijssen, B.

2017-12-01

Permafrost and seasonally frozen soils are a key characteristic of the terrestrial Arctic, and the fate of near-surface permafrost as a result of climate change is projected to have strong impacts on terrestrial biogeochemistry. The active layer thickness (ALT) is the layer of soil that freezes and thaws annually, and shifts in the depth of the ALT are projected to occur over large areas of the Arctic that are characterized by discontinuous permafrost. Faithful representation of permafrost in land models in climate models is a product of both soil dynamics and the coupling of air and soil temperatures. A common problem is a large bias in simulated ALT due to a model depth that is too shallow. Similarly, soil temperatures often show systematic biases, which lead to biases in air temperature due to poorly modeled air-soil temperature feedbacks in a coupled environment. In this study, we use the Regional Arctic System Model (RASM), a fully-coupled regional earth system model that is run at a 50-km land/atmosphere resolution over a pan-Arctic domain and uses the Variable Infiltration Capacity (VIC) model as its land model. To understand what modeling decisions are necessary to accurately represent near-surface permafrost and soil temperature profiles, we perform a large number of RASM simulations with prescribed atmospheric forcings (e.g. VIC in standalone mode in RASM) while varying the model soil depth, thickness of soil moisture layers, number of soil layers and the distribution of soil nodes. We compare modeled soil temperatures and ALT to observations from the Circumpolar Active Layer Monitoring (CALM) network. CALM observations include annual ALT observations as well as daily soil temperature measurements at three soil depths for three sites in Alaska. In the future, we will use our results to inform our modeling of permafrost dynamics in fully-coupled RASM simulations.

Accuracy of sea ice temperature derived from the advanced very high resolution radiometer

NASA Technical Reports Server (NTRS)

Yu, Y.; Rothrock, D. A.; Lindsay, R. W.

1995-01-01

The accuracy of Arctic sea ice surface temperatures T(sub s) dericed from advanced very high resolution radiometer (AVHRR) thermal channels is evaluated in the cold seasons by comparing them with surface air temperatures T(sub air) from drifting buoys and ice stations. We use three different estimates of satellite surface temperatures, a direct estimate from AVHRR channel 4 with only correction for the snow surface emissivity but not for the atmosphere, a single-channel regression of T(sub s) with T(sub air), and Key and Haefliger's (1992) polar multichannel algorithm. We find no measurable bias in any of these estimates and few differences in their statistics. The similar performance of all three methods indicates that an atmospheric water vapor correction is not important for the dry winter atmosphere in the central Arctic, given the other sources of error that remain in both the satellite and the comparison data. A record of drifting station data shows winter air temperature to be 1.4 C warmer than the snow surface temperature. `Correcting' air temperatures to skin temperature by subtracting this amount implies that satellite T(sub s) estimates are biased warm with respect to skin temperature by about this amount. A case study with low-flying aircraft data suggests that ice crystal precipitation can cause satellite estimates of T(sub s) to be several degrees warmer than radiometric measurements taken close to the surface, presumably below the ice crystal precipitation layer. An analysis in which errors are assumed to exist in all measurements, not just the satellite measurements, gives a standard deviation in the satellite estimates of 0.9 C, about half the standard deviation of 1.7 C estimated by assigning all the variation between T(sub s) and T(sub air) to errors in T(sub s).

Sea surface temperature: Observations from geostationary satellites

NASA Astrophysics Data System (ADS)

Bates, John J.; Smith, William L.

1985-11-01

A procedure is developed for estimating sea surface temperatures (SST) from multispectral image data acquired from the VISSR atmospheric sounder (VAS) on the geostationary GOES satellites. Theoretical regression equations for two and three infrared window channels are empirically tuned by using clear field of view satellite radiances matched with reports of SST from NOAA fixed environmental buoys from 1982. The empirical regression equations are then used to produce daily regional analyses of SST. The daily analyses are used to study the response of SST's to the passage of Hurricane Alicia (1983) and Hurricane Debbie (1982) and are also used as a first guess surface temperature in the retrieval of atmospheric temperature and moisture profiles over the oceanic regions. Monthly mean SST's for the western North Atlantic and the eastern equatorial Pacific during March and July 1982 were produced for use in the NASA/JPL SST intercomparison workshop series. Workshop results showed VAS SST's have a scatter of 0.8°-1.0°C and a slight warm bias with respect to the other measurements of SST. Subsequently, a second set of VAS/ buoy matches collected during 1983 and 1984 was used to produce a set of bias corrected regression relations for VAS.

Reconstruction of Arctic surface temperature in past 100 years using DINEOF

NASA Astrophysics Data System (ADS)

Zhang, Qiyi; Huang, Jianbin; Luo, Yong

2015-04-01

Global annual mean surface temperature has not risen apparently since 1998, which is described as global warming hiatus in recent years. However, measuring of temperature variability in Arctic is difficult because of large gaps in coverage of Arctic region in most observed gridded datasets. Since Arctic has experienced a rapid temperature change in recent years that called polar amplification, and temperature risen in Arctic is faster than global mean, the unobserved temperature in central Arctic will result in cold bias in both global and Arctic temperature measurement compared with model simulations and reanalysis datasets. Moreover, some datasets that have complete coverage in Arctic but short temporal scale cannot show Arctic temperature variability for long time. Data Interpolating Empirical Orthogonal Function (DINEOF) were applied to fill the coverage gap of NASA's Goddard Institute for Space Studies Surface Temperature Analysis (GISTEMP 250km smooth) product in Arctic with IABP dataset which covers entire Arctic region between 1979 and 1998, and to reconstruct Arctic temperature in 1900-2012. This method provided temperature reconstruction in central Arctic and precise estimation of both global and Arctic temperature variability with a long temporal scale. Results have been verified by extra independent station records in Arctic by statistical analysis, such as variance and standard deviation. The result of reconstruction shows significant warming trend in Arctic in recent 30 years, as the temperature trend in Arctic since 1997 is 0.76°C per decade, compared with 0.48°C and 0.67°C per decade from 250km smooth and 1200km smooth of GISTEMP. And global temperature trend is two times greater after using DINEOF. The discrepancies above stress the importance of fully consideration of temperature variance in Arctic because gaps of coverage in Arctic cause apparent cold bias in temperature estimation. The result of global surface temperature also proves that global warming in recent years is not as slow as thought.

Characterizing energy budget variability at a Sahelian site: a test of NWP model behaviour

NASA Astrophysics Data System (ADS)

Mackie, Anna; Palmer, Paul I.; Brindley, Helen

2017-12-01

We use observations of surface and top-of-the-atmosphere (TOA) broadband radiation fluxes determined from the Atmospheric Radiation Measurement programme mobile facility, the Geostationary Earth Radiation Budget (GERB) and Spinning Enhanced Visible and Infrared Imager (SEVIRI) instruments and a range of meteorological variables at a site in the Sahel to test the ability of the ECMWF Integrated Forecasting System cycle 43r1 to describe energy budget variability. The model has daily average biases of -12 and 18 W m-2 for outgoing longwave and reflected shortwave TOA radiation fluxes, respectively. At the surface, the daily average bias is 12(13) W m-2 for the longwave downwelling (upwelling) radiation flux and -21(-13) W m-2 for the shortwave downwelling (upwelling) radiation flux. Using multivariate linear models of observation-model differences, we attribute radiation flux discrepancies to physical processes, and link surface and TOA fluxes. We find that model biases in surface radiation fluxes are mainly due to a low bias in ice water path (IWP), poor description of surface albedo and model-observation differences in surface temperature. We also attribute observed discrepancies in the radiation fluxes, particularly during the dry season, to the misrepresentation of aerosol fields in the model from use of a climatology instead of a dynamic approach. At the TOA, the low IWP impacts the amount of reflected shortwave radiation while biases in outgoing longwave radiation are additionally coupled to discrepancies in the surface upwelling longwave flux and atmospheric humidity.

Assimilation of GOES Land Surface Data into a Mesoscale Models

NASA Technical Reports Server (NTRS)

Lapenta, William M.; Suggs, Ron; McNider, Richard T.; Jedlovec, Gary; Dembek, Scott; Goodman, H. Michael (Technical Monitor)

2001-01-01

A technique has been developed for assimilating Geostationary Operational Environmental Satellite (GOES)-derived skin temperature tendencies and insolation into the surface energy budget equation of a mesoscale model so that the simulated rate of temperature change closely agrees with the satellite observations. A critical assumption of the technique is that the availability of moisture (either from the soil or vegetation) is the least known term in the model's surface energy budget. Therefore, the simulated latent heat flux, which is a function of surface moisture availability, is adjusted based upon differences between the modeled and satellite-observed skin temperature tendencies. An advantage of this technique is that satellite temperature tendencies are assimilated in an energetically consistent manner that avoids energy imbalances and surface stability problems that arise from direct assimilation of surface shelter temperatures. The fact that the rate of change of the satellite skin temperature is used rather than the absolute temperature means that sensor calibration is not as critical. The assimilation technique has been applied to the Oklahoma-Kansas region during the spring-summer 2000 time period when dynamic changes in vegetation cover occur. In April, central Oklahoma is characterized by large NDVI associated with winter wheat while surrounding areas are primarily rangeland with lower NDVI. In July the vegetation pattern reverses as the central wheat area changes to low NDVI due to harvesting and the surrounding rangeland is greener than it was in April. The goal of this study is to determine if assimilating satellite land surface data can improve simulation of the complex spatial distribution of surface energy and water fluxes across this region. The PSU/NCAR NM5 V3 system is used in this study. The grid configuration consists of a 36-km CONUS domain and a 12-km nest over the area of interest. Bulk verification statistics (BIAS and RMSE) of surface air temperature and dewpoint indicates that assimilation of the satellite data results reduces both the bias and RMSE for both state variables. In addition, comparison of model data with ARM/CART EBBR flux observations reveals that the assimilation technique adjusts the bowen ratio in a realistic fashion.

Sensitivity of Last Glacial Maximum climate to uncertainties in tropical and subtropical ocean temperatures

USGS Publications Warehouse

Hostetler, S.; Pisias, N.; Mix, A.

2006-01-01

The faunal and floral gradients that underlie the CLIMAP (1981) sea-surface temperature (SST) reconstructions for the Last Glacial Maximum (LGM) reflect ocean temperature gradients and frontal positions. The transfer functions used to reconstruct SSTs from biologic gradients are biased, however, because at the warmest sites they display inherently low sensitivity in translating fauna to SST and they underestimate SST within the euphotic zones where the pycnocline is strong. Here we assemble available data and apply a statistical approach to adjust for hypothetical biases in the faunal-based SST estimates of LGM temperature. The largest bias adjustments are distributed in the tropics (to address low sensitivity) and subtropics (to address underestimation in the euphotic zones). The resulting SSTs are generally in better agreement than CLIMAP with recent geochemical estimates of glacial-interglacial temperature changes. We conducted a series of model experiments using the GENESIS general atmospheric circulation model to assess the sensitivity of the climate system to our bias-adjusted SSTs. Globally, the new SST field results in a modeled LGM surface-air cooling relative to present of 6.4 ??C (1.9 ??C cooler than that of CLIMAP). Relative to the simulation with CLIMAP SSTs, modeled precipitation over the oceans is reduced by 0.4 mm d-1 (an anomaly -0.4 versus 0.0 mm d-1 for CLIMAP) and increased over land (an anomaly -0.2 versus -0.5 mm d-1 for CLIMAP). Regionally strong responses are induced by changes in SST gradients. Data-model comparisons indicate improvement in agreement relative to CLIMAP, but differences among terrestrial data inferences and simulated moisture and temperature remain. Our SSTs result in positive mass balance over the northern hemisphere ice sheets (primarily through reduced summer ablation), supporting the hypothesis that tropical and subtropical ocean temperatures may have played a role in triggering glacial changes at higher latitudes.

On the impact of the resolution on the surface and subsurface Eastern Tropical Atlantic warm bias

NASA Astrophysics Data System (ADS)

Martín-Rey, Marta; Lazar, Alban

2016-04-01

The tropical variability has a great importance for the climate of adjacent areas. Its sea surface temperature anomalies (SSTA) affect in particular the Brazilian Nordeste and the Sahelian region, as well as the tropical Pacific or the Euro-Atlantic sector. Nevertheless, the state-of the art climate models exhibits very large systematic errors in reproducing the seasonal cycle and inter-annual variability in the equatorial and coastal Africa upwelling zones (up to several °C for SST). Theses biases exist already, in smaller proportions though, in forced ocean models (several 1/10th of °C), and affect not only the mixed layer but also the whole thermocline. Here, we present an analysis of the impact of horizontal and vertical resolution changes on these biases. Three different DRAKKAR NEMO OGCM simulations have been analysed, associated to the same forcing set (DFS4.4) with different grid resolutions: "REF" for reference (1/4°, 46 vertical levels), "HH" with a finer horizontal grid (1/12°, 46 v.l.) and "HV" with a finer vertical grid (1/4°, 75 v.l.). At the surface, a more realistic seasonal SST cycle is produced in HH in the three upwellings, where the warm bias decreases (by 10% - 20%) during boreal spring and summer. A notable result is that increasing vertical resolution in HV causes a shift (in advance) of the upwelling SST seasonal cycles. In order to better understand these results, we estimate the three upwelling subsurface temperature errors, using various in-situ datasets, and provide thus a three-dimensional view of the biases.

Influence of Sub-grid-Scale Isentropic Transports on McRAS Evaluations using ARM-CART SCM Datasets

NASA Technical Reports Server (NTRS)

Sud, Y. C.; Walker, G. K.; Tao, W. K.

2004-01-01

In GCM-physics evaluations with the currently available ARM-CART SCM datasets, McRAS produced very similar character of near surface errors of simulated temperature and humidity containing typically warm and moist biases near the surface and cold and dry biases aloft. We argued it must have a common cause presumably rooted in the model physics. Lack of vertical adjustment of horizontal transport was thought to be a plausible source. Clearly, debarring such a freedom would force the incoming air to diffuse into the grid-cell which would naturally bias the surface air to become warm and moist while the upper air becomes cold and dry, a characteristic feature of McRAS biases. Since, the errors were significantly larger in the two winter cases that contain potentially more intense episodes of cold and warm advective transports, it further reaffirmed our argument and provided additional motivation to introduce the corrections. When the horizontal advective transports were suitably modified to allow rising and/or sinking following isentropic pathways of subgrid scale motions, the outcome was to cool and dry (or warm and moisten) the lower (or upper) levels. Ever, crude approximations invoking such a correction reduced the temperature and humidity biases considerably. The tests were performed on all the available ARM-CART SCM cases with consistent outcome. With the isentropic corrections implemented through two different numerical approximations, virtually similar benefits were derived further confirming the robustness of our inferences. These results suggest the need for insentropic advective transport adjustment in a GCM due to subgrid scale motions.

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.

Salinity bias on the foraminifera Mg/Ca thermometry: Correction procedure and implications for past ocean hydrographic reconstructions

NASA Astrophysics Data System (ADS)

Mathien-Blard, Elise; Bassinot, Franck

2009-12-01

Mg/Ca in foraminiferal calcite has recently been extensively used to estimate past oceanic temperatures. Here we show, however, that the Mg/Ca temperature relationship of the planktonic species Globigerinoides ruber is significantly affected by seawater salinity, with a +1 psu change in salinity resulting in a +1.6°C bias in Mg/Ca temperature calculations. If not accounted for, such a bias could lead, for instance, to systematic overestimations of Mg/Ca temperatures during glacial periods, when global ocean salinity had significantly increased compared to today. We present here a correction procedure to derive unbiased sea surface temperatures (SST) and δ18Osw from G. ruber TMg/Ca and δ18Of measurements. This correction procedure was applied to a sedimentary record to reconstruct hydrographic changes since the Last Glacial Maximum (LGM) in the Western Pacific Warm Pool. While uncorrected TMg/Ca data indicate a 3°C warming of the Western Pacific Warm Pool since the LGM, the salinity-corrected SST result in a stronger warming of 4°C.

Summer U.S. Surface Air Temperature Variability: Controlling Factors and AMIP Simulation Biases

NASA Astrophysics Data System (ADS)

Merrifield, A.; Xie, S. P.

2016-02-01

This study documents and investigates biases in simulating summer surface air temperature (SAT) variability over the continental U.S. in the Coupled Model Intercomparison Project (CMIP5) Atmospheric Model Intercomparison Project (AMIP). Empirical orthogonal function (EOF) and multivariate regression analyses are used to assess the relative importance of circulation and the land surface feedback at setting summer SAT over a 30-year period (1979-2008). In observations, regions of high SAT variability are closely associated with midtropospheric highs and subsidence, consistent with adiabatic theory (Meehl and Tebaldi 2004, Lau and Nath 2012). Preliminary analysis shows the majority of the AMIP models feature high SAT variability over the central U.S., displaced south and/or west of observed centers of action (COAs). SAT COAs in models tend to be concomitant with regions of high sensible heat flux variability, suggesting an excessive land surface feedback in these models modulate U.S. summer SAT. Additionally, tropical sea surface temperatures (SSTs) play a role in forcing the leading EOF mode for summer SAT, in concert with internal atmospheric variability. There is evidence that models respond to different SST patterns than observed. Addressing issues with the bulk land surface feedback and the SST-forced component of atmospheric variability may be key to improving model skill in simulating summer SAT variability over the U.S.

Connections Between the Spring Breakup of the Southern Hemisphere Polar Vortex, Stationary Waves, and Air-sea Roughness

NASA Technical Reports Server (NTRS)

Garfinkel, Chaim I.; Oman, Luke David; Barnes, Elizabeth A.; Waugh, Darryn W.; Hurwitz, Margaret H.; Molod, Andrea M.

2013-01-01

A robust connection between the drag on surface-layer winds and the stratospheric circulation is demonstrated in NASA's Goddard Earth Observing System Chemistry-Climate Model (GEOSCCM). Specifically, an updated parameterization of roughness at the air-sea interface, in which surface roughness is increased for moderate wind speeds (4ms to 20ms), leads to a decrease in model biases in Southern Hemispheric ozone, polar cap temperature, stationary wave heat flux, and springtime vortex breakup. A dynamical mechanism is proposed whereby increased surface roughness leads to improved stationary waves. Increased surface roughness leads to anomalous eddy momentum flux convergence primarily in the Indian Ocean sector (where eddies are strongest climatologically) in September and October. The localization of the eddy momentum flux convergence anomaly in the Indian Ocean sector leads to a zonally asymmetric reduction in zonal wind and, by geostrophy, to a wavenumber-1 stationary wave pattern. This tropospheric stationary wave pattern leads to enhanced upwards wave activity entering the stratosphere. The net effect is an improved Southern Hemisphere vortex: the vortex breaks up earlier in spring (i.e., the spring late-breakup bias is partially ameliorated) yet is no weaker in mid-winter. More than half of the stratospheric biases appear to be related to the surface wind speed biases. As many other chemistry climate models use a similar scheme for their surface layer momentum exchange and have similar biases in the stratosphere, we expect that results from GEOSCCM may be relevant for other climate models.

Met Éireann high resolution reanalysis for Ireland

NASA Astrophysics Data System (ADS)

Gleeson, Emily; Whelan, Eoin; Hanley, John

2017-03-01

The Irish Meteorological Service, Met Éireann, has carried out a 35-year very high resolution (2.5 km horizontal grid) regional climate reanalysis for Ireland using the ALADIN-HIRLAM numerical weather prediction system. This article provides an overview of the reanalysis, called MÉRA, as well as a preliminary analysis of surface parameters including screen level temperature, 10 m wind speeds, mean sea-level pressure (MSLP), soil temperatures, soil moisture and 24 h rainfall accumulations. The quality of the 3-D variational data assimilation used in the reanalysis is also assessed. Preliminary analysis shows that it takes almost 12 months to spin up the deep soil in terms of moisture, justifying the choice of running year-long spin up periods. Overall, the model performed consistently over the time period. Small biases were found in screen-level temperatures (less than -0.5 °C), MSLP (within 0.5 hPa) and 10 m wind speed (up to 0.5 m s-1) Soil temperatures are well represented by the model. 24 h accumulations of precipitation generally exhibit a small positive bias of ˜ 1 mm per day and negative biases over mountains due to a mismatch between the model orography and the geography of the region. MÉRA outperforms the ERA-Interim reanalysis, particularly in terms of standard deviations in screen-level temperatures and surface winds. This dataset is the first of its kind for Ireland that will be made publically available during spring 2017.

Diagnosing causes of cloud parameterization deficiencies using ARM measurements over SGP site

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

Wu, W.; Liu, Y.; Betts, A. K.

2010-03-15

Decade-long continuous surface-based measurements at Great Southern Plains (SGP) collected by the US Department of Energy’s Atmospheric Radiation Measurement (ARM) Climate Research Facility are first used to evaluate the three major reanalyses (i.e., ERA-Interim, NCEP/NCAR Reanalysis I and NCEP/DOE Reanalysis II) to identify model biases in simulating surface shortwave cloud forcing and total cloud fraction. The results show large systematic lower biases in the modeled surface shortwave cloud forcing and cloud fraction from all the three reanalysis datasets. Then we focus on diagnosing the causes of these model biases using the Active Remote Sensing of Clouds (ARSCL) products (e.g., verticalmore » distribution of cloud fraction, cloud-base and cloud-top heights, and cloud optical depth) and meteorological measurements (temperature, humidity and stability). Efforts are made to couple cloud properties with boundary processes in the diagnosis.« less

Application and Evaluation of MODIS LAI, FPAR, and Albedo ...

EPA Pesticide Factsheets

MODIS vegetation and albedo products provide a more realistic representation of surface conditions for input to the WRF/CMAQ modeling system. However, the initial evaluation of ingesting MODIS data into the system showed mixed results, with increased bias and error for 2-m temperature and reduced bias and error for 2-m mixing ratio. Recently, the WRF/CMAQ land surface and boundary laywer processes have been updated. In this study, MODIS vegetation and albedo data are input to the updated WRF/CMAQ meteorology and air quality simulations for 2006 over a North American (NA) 12-km domain. The evaluation of the simulation results shows that the updated WRF/CMAQ system improves 2-m temperature estimates over the pre-update base modeling system estimates. The MODIS vegetation input produces a realistic spring green-up that progresses through time from the south to north. Overall, MODIS input reduces 2-m mixing ration bias during the growing season. The NA west shows larger positive O3 bias during the growing season because of reduced gas phase deposition resulting from lower O3 deposition velocities driven by reduced vegetation cover. The O3 bias increase associated with the realistic vegetation representation indicates that further improvement may be needed in the WRF/CMAQ system. The National Exposure Research Laboratory’s Atmospheric Modeling Division (AMAD) conducts research in support of EPA’s mission to protect human health and the environment. AMAD’s rese

Altimetric lagrangian advection to reconstruct Pacific Ocean fine scale surface tracer fields

NASA Astrophysics Data System (ADS)

Rogé, Marine; Morrow, Rosemary; Dencausse, Guillaume

2015-04-01

In past studies, lagrangian stirring of surface tracer fields by altimetric surface geostrophic currents has been performed in different mid to high-latitude regions, showing good results in reconstructing finer-scale tracer patterns. Here we apply the technique to three different regions in the eastern and western tropical Pacific, and in the subtropical southwest Pacific. Initial conditions are derived from weekly gridded temperature and salinity fields, based on hydrographic data and Argo. Validation of the improved fine-scale surface tracer fields is performed using satellite AMSRE SST data, and high-resolution ship thermosalinograph data. We test two kinds of lagrangian advection. The standard one-way advection is shown to introduce an increased tracer bias as the advection time increases. Indeed, since we only use passive stirring, a bias is introduced from the missing physics, such as air-sea fluxes or mixing. A second "backward-forward" advection technique is shown to reduce the seasonal bias, but more data is lost around coasts and islands, a strong handicap in the tropical Pacific with many small islands. In the subtropical Pacific Ocean, the mesoscale temperature and salinity fronts are well represented by the one-way advection over a 10-day advection time, including westward propagating features not apparent in the initial fields. In the tropics, the results are less clear. The validation is hampered by the complex vertical stratification, and the technique is limited by the lack of accurate surface currents for the stirring - the gridded altimetric fields poorly represent the meridional currents, and are not detecting the fast tropical instability waves, nor the wind-driven circulation. We suggest that the passive lateral stirring technique is efficient in regions with moderate the high mesoscale energy and correlated mesoscale surface temperature and surface height. In other regions, more complex dynamical processes may need to be included.

Impact of Vegetation Cover Fraction Parameterization schemes on Land Surface Temperature Simulation in the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Lv, M.; Li, C.; Lu, H.; Yang, K.; Chen, Y.

2017-12-01

The parameterization of vegetation cover fraction (VCF) is an important component of land surface models. This paper investigates the impacts of three VCF parameterization schemes on land surface temperature (LST) simulation by the Common Land Model (CoLM) in the Tibetan Plateau (TP). The first scheme is a simple land cover (LC) based method; the second one is based on remote sensing observation (hereafter named as RNVCF) , in which multi-year climatology VCFs is derived from Moderate-resolution Imaging Spectroradiometer (MODIS) NDVI (Normalized Difference Vegetation Index); the third VCF parameterization scheme derives VCF from the LAI simulated by LSM and clump index at every model time step (hereafter named as SMVCF). Simulated land surface temperature(LST) and soil temperature by CoLM with three VCF parameterization schemes were evaluated by using satellite LST observation and in situ soil temperature observation, respectively, during the period of 2010 to 2013. The comparison against MODIS Aqua LST indicates that (1) CTL produces large biases for both four seasons in early afternoon (about 13:30, local solar time), while the mean bias in spring reach to 12.14K; (2) RNVCF and SMVCF reduce the mean bias significantly, especially in spring as such reduce is about 6.5K. Surface soil temperature observed at 5 cm depth from three soil moisture and temperature monitoring networks is also employed to assess the skill of three VCF schemes. The three networks, crossing TP from West to East, have different climate and vegetation conditions. In the Ngari network, located in the Western TP with an arid climate, there are not obvious differences among three schemes. In Naqu network, located in central TP with a semi-arid climate condition, CTL shows a severe overestimates (12.1 K), but such overestimations can be reduced by 79% by RNVCF and 87% by SMVCF. In the third humid network (Maqu in eastern TP), CoLM performs similar to Naqu. However, at both Naqu and Maqu networks, RNVCF shows significant overestimation in summer, perhaps due to RNVCF ignores the growing characteristics of vegetation (mainly grass) in these two regions. Our results demonstrate that VCF schemes have significant influence on LSM performance, and indicate that it is important to consider vegetation growing characteristics in VCF schemes for different LCs.

Estimating optically-thin cirrus cloud induced cold bias on infrared radiometric satellite sea surface temperature retrieval in the tropics

NASA Astrophysics Data System (ADS)

Marquis, Jared Wayne

Passive longwave infrared radiometric satellite-based retrievals of sea surface temperature (SST) at instrument nadir are investigated for cold bias caused by unscreened optically-thin cirrus (OTC) clouds (cloud optical depth ≤ 0.3; COD). Level 2 split-window SST retrievals over tropical oceans (30° S - 30° N) from Moderate Resolution Imaging Spectroradiometer (MODIS) radiances collected aboard the NASA Aqua satellite (Aqua-MODIS) are collocated with cloud profiles from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument, mounted on the independent NASA CALIPSO satellite. OTC are present in approximately 25% of tropical quality-assured (QA) Aqua-MODIS Level-2 data, representing over 99% of all contaminating cirrus found. This results in cold-biased SST retrievals using either split- (MODIS, AVHRR and VIIRS) or triple-window (AVHRR and VIIRS only) retrieval methods. SST retrievals are modeled based on operational algorithms using radiative transfer model simulations conducted with a hypothetical 1.5 km thick OTC cloud placed incrementally from 10.0 - 18.0 km above mean sea level for cloud optical depths (COD) between 0.0 - 0.3. Corresponding cold bias estimates for each sensor are estimated using relative Aqua-MODIS cloud contamination frequencies as a function of cloud top height and COD (assuming them consistent across each platform) integrated within each corresponding modeled cold bias matrix. Split-window relative OTC cold biases, for any single observation, range from 0.40° - 0.49° C for the three sensors, with an absolute (bulk mean) bias between 0.10° - 0.13° C. Triple-window retrievals are more resilient, ranging from 0.03° - 0.04° C relative and 0.11° - 0.16° C absolute. Cold biases are constant across the Pacific and Indian Ocean domains. Absolute bias is smaller over the Atlantic, but relative bias is larger due to different cloud properties indicating that this issue persists globally.

Temperature characteristics of silicon space solar cells and underlying parameters

NASA Technical Reports Server (NTRS)

Anspaugh, B. E.; Kachare, Ram; Garlick, G. F. J.

1987-01-01

Silicon space cells, 2 cm x 2 cm, with 10 ohm-cm p-base resistivity, 8-mil base thickness, and no back-surface fields have been investigated over the temperature range from 301 to 223 K by measurements of dark forward and reverse current-voltage characteristics and current-voltage relations under illumination. From dark forward bias data, the first and second diode saturation currents, I01 and I02, are determined and hence the base diffusion length and lifetime of minority carriers as functions of temperature. Lifetime increases exponentially with temperature and is explained by a Shockley-Read-Hall model with deep recombination levels 0.245 eV above the valence band. The I02 variation with temperature follows the Sah-Noyce-Shockley-Choo model except at low temperature where extra transitions raise the value above the predicted level. Reverse bias current at low voltage is a thermally assisted tunneling process via deep levels which are observed in base recombination at higher temperatures. The tunneling effects tend to become independent of temperature in the low-temperature region. These results demonstrate the ability to deduce basic parameters such as lifetime from simple measurements and show that back-surface fields offer no advantage at temperatures below 230 K. The analysis also explains the fall in lifetimes observed as the base conductivity increases, attributing it to native defects (perhaps carbon-oxygen-vacancy complexes) rather than the concentration of base dopant.

NCAR CCM2 simulation of the modern Antarctic climate

NASA Technical Reports Server (NTRS)

Tzeng, Ren-Yow; Bromwich, David H.; Parish, Thomas R.; Chen, Biao

1994-01-01

The National Center for Atmospheric Research (NCAR) community climate model version 2 (CCM2) simulation of the circumpolar trough, surface air temperature, the polar vortex, cloudiness, winds, and atmospheric moisture and energy budgets are examined to validate the model's representation of the present-day Antarctic climate. The results show that the CCM2 can well simulate many important climate features over Antarctica, such as the location and intensity of the circumpolar trough, the coreless winter over the plateau, the intensity and horizontal distribution of the surface inversion, the speed and streamline pattern of the katabatic winds, the double jet stream feature over the southern Indian and Pacific oceans, and the arid climate over the continent. However, there are also some serious errors in the model. Some are due to old problems but some are caused by the new parameterizations in the model. The model errors over high southern latitudes can be summarized as follows: The circumpolar trough, the polar vertex, and the westerlies in midlatitudes are too strong; the semiannual cycle of the circumpolar trough is distorted compared to the observations; the low centers of the circumpolar trough and the troughs in the middle and upper troposphere are shifted eastward by 15 deg - 40 deg longitude; the surface temperatures are too cold over the plateau in summer and over the coastline in winter; the polar tropopause continues to have a cold bias; and the cloudiness is too high over the continent. These biases are induced by two major factors: (1) the cloud optical properties in tropical and middle latitudes, which cause the eastward shift of troughs and surface low centers and the error in the semiannual cycle, and (2) the cold bias of the surface air temperature, which is attributed to the oversimulation of cloudiness over the continent, especially during summer, and the uniform 2-m-thick sea ice. The constant thickness of sea ice suppresses the energy flux from the ocean to the atmosphere and hence reduces the air temperature near the coast during winter. Finally, although the simulated Antarctic climate still suffers these biases, the overall performance of the CCM2 is much better than that of the CCM1-T42. Therefore the CCM2 is good enough to be used for climate change studies, especially over Antarctica.

Increasing occurrence of cold and warm extremes during the recent global warming slowdown.

PubMed

Johnson, Nathaniel C; Xie, Shang-Ping; Kosaka, Yu; Li, Xichen

2018-04-30

The recent levelling of global mean temperatures after the late 1990s, the so-called global warming hiatus or slowdown, ignited a surge of scientific interest into natural global mean surface temperature variability, observed temperature biases, and climate communication, but many questions remain about how these findings relate to variations in more societally relevant temperature extremes. Here we show that both summertime warm and wintertime cold extreme occurrences increased over land during the so-called hiatus period, and that these increases occurred for distinct reasons. The increase in cold extremes is associated with an atmospheric circulation pattern resembling the warm Arctic-cold continents pattern, whereas the increase in warm extremes is tied to a pattern of sea surface temperatures resembling the Atlantic Multidecadal Oscillation. These findings indicate that large-scale factors responsible for the most societally relevant temperature variations over continents are distinct from those of global mean surface temperature.

Why is SMOS Drier than the South Fork In-situ Soil Moisture Network?

NASA Astrophysics Data System (ADS)

Walker, V. A.; Hornbuckle, B. K.; Cosh, M. H.

2014-12-01

Global maps of near-surface soil moisture are currently being produced by the European Space Agency's Soil Moisture and Ocean Salinity (SMOS) satellite mission at 40 km. Within the next few months NASA's Soil Moisture Active Passive (SMAP) satellite mission will begin producing observations of near-surface soil moisture at 10 km. Near-surface soil moisture is the water content of the first 3 to 5 cm of the soil. Observations of near-surface soil moisture are expected to improve weather and climate forecasts. These satellite observations must be validated. We define validation as determining the space/time statistical characteristics of the uncertainty. A standard that has been used for satellite validation is in-situ measurements of near-surface soil moisture made with a network of sensors spanning the extent of a satellite footprint. Such a network of sensors has been established in the South Fork of the Iowa River in Central Iowa by the USDA ARS. Our analysis of data in 2013 indicates that SMOS has a dry bias: SMOS near-surface soil moisture is between 0.05 to 0.10 m^3m^{-3} lower than what is observed by the South Fork network. A dry bias in SMOS observations has also been observed in other regions of North America. There are many possible explanations for this difference: underestimation of vegetation, or soil surface roughness; undetected radio frequency interference (RFI); a retrieval model that is not appropriate for agricultural areas; or the use of an incorrect surface temperature in the retrieval process. We will begin our investigation by testing this last possibility: that SMOS is using a surface temperature that is too low which results in a drier soil moisture that compensates for this error. We will present a comparison of surface temperatures from the European Center for Medium-range Weather Forecasting (ECMWF) used to retrieve near-surface soil moisture from SMOS measurements of brightness temperature, and surface temperatures in the South Fork obtained from both tower and in-situ sensors. We will also use a long-term data set of tower and in-situ sensors collected in agricultural fields to develop a relationship between air temperature and the surface temperature relevant to the terrestrial microwave emission that is detected by SMOS.

Coupling of Community Land Model with RegCM4 for Indian Summer Monsoon Simulation

NASA Astrophysics Data System (ADS)

Maurya, R. K. S.; Sinha, P.; Mohanty, M. R.; Mohanty, U. C.

2017-11-01

Three land surface schemes available in the regional climate model RegCM4 have been examined to understand the coupling between land and atmosphere for simulation of the Indian summer monsoon rainfall. The RegCM4 is coupled with biosphere-atmosphere transfer scheme (BATS) and the National Center for Atmospheric Research (NCAR) Community Land Model versions 3.5, and 4.5 (CLM3.5 and CLM4.5, respectively) and model performance is evaluated for recent drought (2009) and normal (2011) monsoon years. The CLM4.5 has a more distinct category of surface and it is capable of representing better the land surface characteristics. National Centers for Environmental Prediction (NCEP) and Department of Energy (DOE) reanalysis version 2 (NNRP2) datasets are considered as driving force to conduct the experiments for the Indian monsoon region (30°E-120°E; 30°S-50°N). The NNRP2 and India Meteorological Department (IMD) gridded precipitation data are used for verification analysis. The results indicate that RegCM4 simulations with CLM4.5 (RegCM4-CLM4.5) and CLM3.5 (RegCM4-CLM3.5) surface temperature (at 2 ms) have very low warm biases ( 1 °C), while with BATS (RegCM4-BATS) has a cold bias of about 1-3 °C in peninsular India and some parts of central India. Warm bias in the RegCM4-BATS is observed over the Indo-Gangetic plain and northwest India and the bias is more for the deficit year as compared to the normal year. However, the warm (cold) bias is less in RegCM4-CLM4.5 than other schemes for both the deficit and normal years. The model-simulated maximum (minimum) surface temperature and sensible heat flux at the surface are positively (negatively) biased in all the schemes; however, the bias is higher in RegCM4-BATS and lower in RegCM4-CLM4.5 over India. All the land surface schemes overestimated the precipitation in peninsular India and underestimated in central parts of India for both the years; however, the biases are less in RegCM4-CLM4.5 and more in RegCM4-CLM3.5 and RegCM4-BATS. During both the years, BATS scheme in RegCM4 failed to represent low precipitation over the leeward than windward side of the Western Ghats, while CLM schemes (both versions) in the RegCM4 are able to depict this feature. In the topographic regions, such as the Western Ghats, northeast India and state of Jammu and Kashmir, RegCM4-BATS overestimates the rainfall amount with higher bias. Statistical analysis using anomaly correlation coefficient, root mean square error, equitable threat score, and critical success index confirms that RegCM4-CLM performs better than RegCM4-BATS in the simulation of the Indian summer monsoon.

Mean Bias in Seasonal Forecast Model and ENSO Prediction Error.

PubMed

Kim, Seon Tae; Jeong, Hye-In; Jin, Fei-Fei

2017-07-20

This study uses retrospective forecasts made using an APEC Climate Center seasonal forecast model to investigate the cause of errors in predicting the amplitude of El Niño Southern Oscillation (ENSO)-driven sea surface temperature variability. When utilizing Bjerknes coupled stability (BJ) index analysis, enhanced errors in ENSO amplitude with forecast lead times are found to be well represented by those in the growth rate estimated by the BJ index. ENSO amplitude forecast errors are most strongly associated with the errors in both the thermocline slope response and surface wind response to forcing over the tropical Pacific, leading to errors in thermocline feedback. This study concludes that upper ocean temperature bias in the equatorial Pacific, which becomes more intense with increasing lead times, is a possible cause of forecast errors in the thermocline feedback and thus in ENSO amplitude.

Effects of diurnal adjustment on biases and trends derived from inter-sensor calibrated AMSU-A data

NASA Astrophysics Data System (ADS)

Chen, H.; Zou, X.; Qin, Z.

2018-03-01

Measurements of brightness temperatures from Advanced Microwave Sounding Unit-A (AMSU-A) temperature sounding instruments onboard NOAA Polarorbiting Operational Environmental Satellites (POES) have been extensively used for studying atmospheric temperature trends over the past several decades. Intersensor biases, orbital drifts and diurnal variations of atmospheric and surface temperatures must be considered before using a merged long-term time series of AMSU-A measurements from NOAA-15, -18, -19 and MetOp-A.We study the impacts of the orbital drift and orbital differences of local equator crossing times (LECTs) on temperature trends derivable from AMSU-A using near-nadir observations from NOAA-15, NOAA-18, NOAA-19, and MetOp-A during 1998-2014 over the Amazon rainforest. The double difference method is firstly applied to estimation of inter-sensor biases between any two satellites during their overlapping time period. The inter-calibrated observations are then used to generate a monthly mean diurnal cycle of brightness temperature for each AMSU-A channel. A diurnal correction is finally applied each channel to obtain AMSU-A data valid at the same local time. Impacts of the inter-sensor bias correction and diurnal correction on the AMSU-A derived long-term atmospheric temperature trends are separately quantified and compared with those derived from original data. It is shown that the orbital drift and differences of LECTamong different POESs induce a large uncertainty in AMSU-A derived long-term warming/cooling trends. After applying an inter-sensor bias correction and a diurnal correction, the warming trends at different local times, which are approximately the same, are smaller by half than the trends derived without applying these corrections.

A review of surface heat-flow data of the northern Middle Atlas (Morocco)

NASA Astrophysics Data System (ADS)

Chiozzi, Paolo; Barkaoui, Alae-Eddine; Rimi, Abdelkrim; Verdoya, Massimo; Zarhloule, Yassine

2017-12-01

We revised thermal data available from water and oil wells in the northern sector of the Middle Atlas region. To avoid biased estimation of surface heat flow caused by advection likely occurring in shallow aquifers, temperature measurements in water boreholes were carefully inspected and selected. The heat flow in the oil wells was inferred by taking into account the porosity variation with depth, the temperature effect on thermal conductivity of the matrix and the pore fluid, together with the contribution of the radiogenic heat production. Moreover, the possible bias in heat flow caused by convection occurring in confined carbonate aquifers was evaluated. The results of heat flow slightly modify the picture reported in previous investigations. The heat flow value over the investigated region is rather uniform (about 80 mW m-2) and is similar in oil wells and in water boreholes. Geothermal calculations indicate that such a surface heat flow is compatible with a ∼70 km thick thermal lithosphere and normal thermal conditions in the asthenospheric mantle.

Downscaling with a nested regional climate model in near-surface fields over the contiguous United States

NASA Astrophysics Data System (ADS)

Wang, Jiali; Kotamarthi, Veerabhadra R.

2014-07-01

The Weather Research and Forecasting (WRF) model is used for dynamic downscaling of 2.5-degree National Centers for Environmental Prediction-U.S. Department of Energy Reanalysis II (NCEP-R2) data for 1980-2010 at 12 km resolution over most of North America. The model's performance for surface air temperature and precipitation is evaluated by comparison with high-resolution observational data sets. The model's ability to add value is investigated by comparison with NCEP-R2 data and a 50 km regional climate simulation. The causes for major model bias are studied through additional sensitivity experiments with various model setup/integration approaches and physics representations. The WRF captures the main features of the spatial patterns and annual cycles of air temperature and precipitation over most of the contiguous United States. However, simulated air temperatures over the south central region and precipitation over the Great Plains and the Southwest have significant biases. Allowing longer spin-up time, reducing the nudging strength, or replacing the WRF Single-Moment six-class microphysics with Morrison microphysics reduces the bias over some subregions. However, replacing the Grell-Devenyi cumulus parameterization with Kain-Fritsch shows no improvement. The 12 km simulation does add value above the NCEP-R2 data and the 50 km simulation over mountainous and coastal zones.

A warm-season comparison of WRF coupled to the CLM4.0, Noah-MP, and Bucket hydrology land surface schemes over the central USA

NASA Astrophysics Data System (ADS)

Van Den Broeke, Matthew S.; Kalin, Andrew; Alavez, Jose Abraham Torres; Oglesby, Robert; Hu, Qi

2017-11-01

In climate modeling studies, there is a need to choose a suitable land surface model (LSM) while adhering to available resources. In this study, the viability of three LSM options (Community Land Model version 4.0 [CLM4.0], Noah-MP, and the five-layer thermal diffusion [Bucket] scheme) in the Weather Research and Forecasting model version 3.6 (WRF3.6) was examined for the warm season in a domain centered on the central USA. Model output was compared to Parameter-elevation Relationships on Independent Slopes Model (PRISM) data, a gridded observational dataset including mean monthly temperature and total monthly precipitation. Model output temperature, precipitation, latent heat (LH) flux, sensible heat (SH) flux, and soil water content (SWC) were compared to observations from sites in the Central and Southern Great Plains region. An overall warm bias was found in CLM4.0 and Noah-MP, with a cool bias of larger magnitude in the Bucket model. These three LSMs produced similar patterns of wet and dry biases. Model output of SWC and LH/SH fluxes were compared to observations, and did not show a consistent bias. Both sophisticated LSMs appear to be viable options for simulating the effects of land use change in the central USA.

Narrowing the surface temperature range in CMIP5 simulations over the Arctic

NASA Astrophysics Data System (ADS)

Hao, Mingju; Huang, Jianbin; Luo, Yong; Chen, Xin; Lin, Yanluan; Zhao, Zongci; Xu, Ying

2018-05-01

Much uncertainty exists in reproducing Arctic temperature using different general circulation models (GCMs). Therefore, evaluating the performance of GCMs in reproducing Arctic temperature is critically important. In our study, 32 GCMs in the fifth phase of the Coupled Model Intercomparison Project (CMIP5) during the period 1900-2005 are used, and several metrics, i.e., bias, correlation coefficient ( R), and root mean square error (RMSE), are applied. The Cowtan data set is adopted as the reference data. The results suggest that the GCMs used can reasonably reproduce the Arctic warming trend during the period 1900-2005, as observed in the observational data, whereas a large variation of inter-model differences exists in modeling the Arctic warming magnitude. With respect to the reference data, most GCMs have large cold biases, whereas others have weak warm biases. Additionally, based on statistical thresholds, the models MIROC-ESM, CSIRO-Mk3-6-0, HadGEM2-AO, and MIROC-ESM-CHEM (bias ≤ ±0.10 °C, R ≥ 0.50, and RMSE ≤ 0.60 °C) are identified as well-performing GCMs. The ensemble of the four best-performing GCMs (ES4), with bias, R, and RMSE values of -0.03 °C, 0.72, and 0.39 °C, respectively, performs better than the ensemble with all 32 members, with bias, R, and RMSE values of -0.04 °C, 0.64, and 0.43 °C, respectively. Finally, ES4 is used to produce projections for the next century under the scenarios of RCP2.6, RCP4.5, and RCP8.0. The uncertainty in the projected temperature is greater in the higher emissions scenarios. Additionally, the projected temperature in the cold half year has larger variations than that in the warm half year.

Benchmarking CCMI models' top-of-atmosphere flux in the 9.6-µm ozone band using AURA TES Instantaneous Radiative Kernel

NASA Astrophysics Data System (ADS)

Kuai, L.; Bowman, K. W.; Worden, H. M.; Paulot, F.; Paynter, D.; Oman, L.; Strode, S. A.; Rozanov, E.; Stenke, A.; Revell, L. E.; Plummer, D. A.

2017-12-01

The estimated ozone radiative forcing (RF) from chemical-climate models range widely from +0.2 to +0.6 Wm-2. The reason has never been well understood. Since the ozone absorption in the 9.6 μm band contributes 97% of the O3 longwave RF, the variation of outgoing longwave radiation (OLR) due to ozone is dominant by this band. The observed TOA flux over 9.6 µm ozone band by Thermal Emission Spectrometer (TES) shows the global distribution has unique spatial patterns. In addition, the simulated TOA fluxes over 9.6 µm ozone band by different models have never been evaluated against observations. The bias of TOA flux from model could be primarily contributed by the bias of temperature, water vapor and ozone. Furthermore, the sensitivity of TOA flux to tropospheric ozone (instantaneous radiative kernel, IRK) may also affected by these biases (Kuai et al., 2017). The bias in TOA flux would eventually propagate into model calculations of ozone RF and cause divergence of the predictions of future climate by models. In this study, we applied the observation-based IRK product by AURA TES to attribute the CCMI model bias in TOA flux over 9.6 µm ozone band to ozone, water vapor, air temperature, and surface temperature. The comparisons of the three CCMI models (AM3, SOCOL3 and GEOCCM) to TES observations suggest that 1) all models underestimate the TOA flux at tropics and subtropics. 2) The TOA flux bias is comparable similar by AM3 and GEOSCC (-0.2 to -0.3 W/m2) however is larger for the relative young model, SOCOL3 (-0.4 to -0.6 W/m2). 3) The contributions by surface temperature are similarly moderate (-0.2 W/m2). 4) The contribution of ozone is largest by SOCOL3 (-0.3 W/m2), smallest by GEOSCCM (less than 0.1 W/m2) and moderate by AM3 (-0.2 W/m2). 5) Overall, the contributions by atmospheric temperature are all small (less than 0.1 W/m2). 6) The contribution of water vapor is negative and small by both SOCOL3 and GEOSCCM (0.1 W/m2) however large and positive by AM3 (0.2 W/m2). This postive bias compensate the negative bias from other terms in AM3 and make a tropical minimum in TOA flux bias. It means it is `right for the wrong reasons' at tropics in AM3. The same analysis will be extended to three more CCMI models (CMAM, EMAC, and MRI) and eventually to all CCMI models.

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.

Systematic Biases of Present-day's Land Surface Air Temperature and Precipitation and Associated Tendency of Future Projection in the Asia Monsoon of the CMIP5 models

NASA Astrophysics Data System (ADS)

Ose, T.

2016-12-01

Seasonally varying land surface air temperature (SAT) is basically responsible for the occurrence of the Asia Monsoon precipitation whereas the precipitation may play more important roles in the appearance and variability of the Asia Monsoon circulations. A simple and basic analysis on model biases of land SAT simulations over the Eurasian Continent is done to find necessary improvements of land surface treatment in the models, their relationship with model precipitation and their influences to future projections. Specifically, the Empirical Orthogonal Function (EOF) analysis is applied to land SATs of the CMIP5 present-day's simulation (the June-July-August average during 1975-1999) ensemble. Associated biases of precipitation and other Asia Monsoon elements are obtained by the regression method onto the obtained EOF coefficients. The first EOF is the SAT bias over the dry region of the Eurasia. Positive deviations of the 1st EOF coefficient indicate northwestward shift of the Asia Monsoon System; northwestward (or inner-continent-ward) shifts of precipitation, the Tibetan High, the low-level jet, the Pacific High and so on. The second EOF is the SAT bias over the northeast Eurasia. It is interesting that warmer land SAT bias over the northeast Asia is related to more wet condition over East Asia like in early summer; southward shift of westerly jet and precipitation band in East Asia. The third one indicates the SAT bias over the Eurasian region between the 1st and 2nd EOF SAT regions. However, this EOF may be characterized by the accompanied model precipitation bias over the subtropical Northwest Pacific like in late summer; northeastward shift of upper westerly jet in the eastern Asia and the weak Pacific High in the subtropical Northwest Pacific. The most intrigued feature is a connection of the 3rd EOF with the future change of SAT in the extra-tropical Northern Hemisphere in the CMIP5 projections. This fact may indicate that precipitation climatology in the Asia Monsoon is an important factor in the heat budget of the northern summer in the future change as well as the present-day simulation.

STM/STS Study of LixCoO2 Single Crystals

NASA Astrophysics Data System (ADS)

Iwaya, Katsuya; Minato, Taketoshi; Miyoshi, Kiyotaka; Takeuchi, Jun; Kim, Yousoo; Hitosugi, Taro

2012-02-01

We have performed low temperature scanning tunneling microscopy/spectroscopy (STM/STS) measurements on LixCoO2 (x=0.66) single crystal surfaces. A (1x1) hexagonal lattice was clearly observed and found to be moved by changing bias-voltage polarity, indicating that this could be associated with Li ions on the surface. Under the (1x1) hexagonal lattice, we imaged almost randomly distributed bright dots that were strongly dependent on bias-voltage, with insulating spectroscopic features. Different area on the surface showed a (2x2) hexagonal lattice that could be related to an ordering of Co^3+ and Co^4+ ions. These results suggest the electronic structure of LixCoO2 surface is inhomogeneous possibly due to segregation of Li ions.

Surface Spin Glass Ordering and Exchange Bias in Nanometric Sm0.09Ca0.91MnO3 Manganites

NASA Astrophysics Data System (ADS)

Giri, S. K.; Nath, T. K.

2011-07-01

We have thoroughly investigated the entire magnetic state of under doped ferromagnetic insulating manganite Sm0.09Ca0.91MnO3 through temperature dependent linear and non-linear ac magnetic susceptibility and magnetization measurements. This ferromagnetic insulating manganite is found to have frequency dependent ferromagnetic to paramagnetic transition temperature at around 108 K. Exchange- bias effect are observed in field -cooled magnetic hysteresis loops for this nanoparticle. We have attributed our observation to the formation of ferromagnetic cluster which are formed as a consequence of intrinsic phase separation below certain temperature in this under doped manganites. We have carried out electronic- and magneto-transport measurements to support these observed results.

Evaluation of a novel noninvasive continuous core temperature measurement system with a zero heat flux sensor using a manikin of the human body.

PubMed

Brandes, Ivo F; Perl, Thorsten; Bauer, Martin; Bräuer, Anselm

2015-02-01

Reliable continuous perioperative core temperature measurement is of major importance. The pulmonary artery catheter is currently the gold standard for measuring core temperature but is invasive and expensive. Using a manikin, we evaluated the new, noninvasive SpotOn™ temperature monitoring system (SOT). With a sensor placed on the lateral forehead, SOT uses zero heat flux technology to noninvasively measure core temperature; and because the forehead is devoid of thermoregulatory arteriovenous shunts, a piece of bone cement served as a model of the frontal bone in this study. Bias, limits of agreements, long-term measurement stability, and the lowest measurable temperature of the device were investigated. Bias and limits of agreement of the temperature data of two SOTs and of the thermistor placed on the manikin's surface were calculated. Measurements obtained from SOTs were similar to thermistor values. The bias and limits of agreement lay within a predefined clinically acceptable range. Repeat measurements differed only slightly, and stayed stable for hours. Because of its temperature range, the SOT cannot be used to monitor temperatures below 28°C. In conclusion, the new SOT could provide a reliable, less invasive and cheaper alternative for measuring perioperative core temperature in routine clinical practice. Further clinical trials are needed to evaluate these results.

Evaluation of hydrologic components of community land model 4 and bias identification

DOE PAGES

Du, Enhao; Vittorio, Alan Di; Collins, William D.

2015-04-01

Runoff and soil moisture are two key components of the global hydrologic cycle that should be validated at local to global scales in Earth System Models (ESMs) used for climate projection. Here, we have evaluated the runoff and surface soil moisture output by the Community Climate System Model (CCSM) along with 8 other models from the Coupled Model Intercomparison Project (CMIP5) repository using satellite soil moisture observations and stream gauge corrected runoff products. A series of Community Land Model (CLM) runs forced by reanalysis and coupled model outputs was also performed to identify atmospheric drivers of biases and uncertainties inmore » the CCSM. Results indicate that surface soil moisture simulations tend to be positively biased in high latitude areas by most selected CMIP5 models except CCSM, FGOALS, and BCC, which share similar land surface model code. With the exception of GISS, runoff simulations by all selected CMIP5 models were overestimated in mountain ranges and in most of the Arctic region. In general, positive biases in CCSM soil moisture and runoff due to precipitation input error were offset by negative biases induced by temperature input error. Excluding the impact from atmosphere modeling, the global mean of seasonal surface moisture oscillation was out of phase compared to observations in many years during 1985–2004. The CLM also underestimated runoff in the Amazon, central Africa, and south Asia, where soils all have high clay content. We hypothesize that lack of a macropore flow mechanism is partially responsible for this underestimation. However, runoff was overestimated in the areas covered by volcanic ash soils (i.e., Andisols), which might be associated with poor soil porosity representation in CLM. Finally, our results indicate that CCSM predictability of hydrology could be improved by addressing the compensating errors associated with precipitation and temperature and updating the CLM soil representation.« less

Impact of chlorophyll bias on the tropical Pacific mean climate in an earth system model

NASA Astrophysics Data System (ADS)

Lim, Hyung-Gyu; Park, Jong-Yeon; Kug, Jong-Seong

2017-12-01

Climate modeling groups nowadays develop earth system models (ESMs) by incorporating biogeochemical processes in their climate models. The ESMs, however, often show substantial bias in simulated marine biogeochemistry which can potentially introduce an undesirable bias in physical ocean fields through biogeophysical interactions. This study examines how and how much the chlorophyll bias in a state-of-the-art ESM affects the mean and seasonal cycle of tropical Pacific sea-surface temperature (SST). The ESM used in the present study shows a sizeable positive bias in the simulated tropical chlorophyll. We found that the correction of the chlorophyll bias can reduce the ESM's intrinsic cold SST mean bias in the equatorial Pacific. The biologically-induced cold SST bias is strongly affected by seasonally-dependent air-sea coupling strength. In addition, the correction of chlorophyll bias can improve the annual cycle of SST by up to 25%. This result suggests a possible modeling approach in understanding the two-way interactions between physical and chlorophyll biases by biogeophysical effects.

Arctic (and Antarctic) Observing Experiment - an Assessment of Methods to Measure Temperature over Polar Environments

NASA Astrophysics Data System (ADS)

Rigor, I. G.; Clemente-Colon, P.; Nghiem, S. V.; Hall, D. K.; Woods, J. E.; Henderson, G. R.; Zook, J.; Marshall, C.; Gallage, C.

2014-12-01

The Arctic environment has been undergoing profound changes; the most visible is the dramatic decrease in Arctic sea ice extent (SIE). These changes pose a challenge to our ability to measure surface temperature across the Polar Regions. Traditionally, the International Arctic Buoy Programme (IABP) and International Programme for Antarctic Buoys (IPAB) have measured surface air temperature (SAT) at 2-m height, which minimizes the ambiguity of measurements near of the surface. Specifically, is the temperature sensor measuring open water, snow, sea ice, or air? But now, with the dramatic decrease in Arctic SIE, increase in open water during summer, and the frailty of the younger sea ice pack, the IABP has had to deploy and develop new instruments to measure temperature. These instruments include Surface Velocity Program (SVP) buoys, which are commonly deployed on the world's ice-free oceans and typically measure sea surface temperature (SST), and the new robust Airborne eXpendable Ice Beacons (AXIB), which measure both SST and SAT. "Best Practice" requires that these instruments are inter-compared, and early results showing differences in collocated temperature measurements of over 2°C prompted the establishment of the IABP Arctic Observing Experiment (AOX) buoy test site at the US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) site in Barrow, Alaska. Preliminary results showed that the color of the hull of SVP buoys introduces a bias due to solar heating of the buoy. Since then, we have recommended that buoys should be painted white to reduce biases in temperature measurements due to different colors of the buoys deployed in different regions of the Arctic or the Antarctic. Measurements of SAT are more robust, but some of the temperature shields are susceptible to frosting. During our presentation we will provide an intercomparison of the temperature measurements at the AOX test site (i.e. high quality DOE/ARM observations compared with unattended buoy measurements, and satellite retrievals). We will also show how these data may be used to improve our record of temperature over polar environments.

CLIMATE CHANGE. Possible artifacts of data biases in the recent global surface warming hiatus.

PubMed

Karl, Thomas R; Arguez, Anthony; Huang, Boyin; Lawrimore, Jay H; McMahon, James R; Menne, Matthew J; Peterson, Thomas C; Vose, Russell S; Zhang, Huai-Min

2015-06-26

Much study has been devoted to the possible causes of an apparent decrease in the upward trend of global surface temperatures since 1998, a phenomenon that has been dubbed the global warming "hiatus." Here, we present an updated global surface temperature analysis that reveals that global trends are higher than those reported by the Intergovernmental Panel on Climate Change, especially in recent decades, and that the central estimate for the rate of warming during the first 15 years of the 21st century is at least as great as the last half of the 20th century. These results do not support the notion of a "slowdown" in the increase of global surface temperature. Copyright © 2015, American Association for the Advancement of Science.

Australian snowpack in the NARCliM ensemble: evaluation, bias correction and future projections

NASA Astrophysics Data System (ADS)

Luca, Alejandro Di; Evans, Jason P.; Ji, Fei

2017-10-01

In this study we evaluate the ability of an ensemble of high-resolution Regional Climate Model simulations to represent snow cover characteristics over the Australian Alps and go on to asses future projections of snowpack characteristics. Our results show that the ensemble presents a cold temperature bias and overestimates total precipitation leading to a general overestimation of the snow cover as compared with MODIS satellite data. We then produce a new set of snowpack characteristics by running a temperature based snow melt/accumulation model forced by bias corrected temperature and precipitation fields. While some positive snow cover biases remain, the bias corrected (BC) dataset show large improvements regarding the simulation of total amounts, seasonality and spatial distribution of the snow cover compared with MODIS products. Both the raw and BC datasets are then used to assess future changes in the snowpack characteristics. Both datasets show robust increases in near-surface temperatures and decreases in snowfall that lead to a substantial reduction of the snowpack over the Australian Alps. The snowpack decreases by about 15 and 60% by 2030 and 2070 respectively. While the BC data introduce large differences in the simulation of the present climate snowpack, in relative terms future changes appear to be similar to those obtained using the raw data. Future temperature projections show a clear dependence with elevation through the snow-albedo feedback effect that affects snowpack projections. Uncertainties in future projections of the snowpack are large in both datasets and are mainly dominated by the choice of the lateral boundary conditions.

Kinetics of Ta ions penetration into porous low-k dielectrics under bias-temperature stress

NASA Astrophysics Data System (ADS)

He, Ming; Ou, Ya; Wang, Pei-I.; Lu, Toh-Ming

2010-05-01

It is known that Ta, a popular diffusion barrier material, can itself penetrate into low-k dielectrics under bias-temperature stress. In this work, we derived a model which directly correlates the diffusivity of Ta ions to the rate of flatband voltage shift (FBS) of the Ta/methyl silsesquixane (MSQ)/Si capacitors. From our experimentally measured constant FBS rate, the Ta diffusivity and activation energy were determined. It appears that an increase in the porosity of MSQ film enhances the Ta diffusivity but does not affect the associated activation energy. This suggests the Ta ion diffusion is mainly through interconnected pore surfaces.

Sampling biases in datasets of historical mean air temperature over land.

PubMed

Wang, Kaicun

2014-04-10

Global mean surface air temperature (Ta) has been reported to have risen by 0.74°C over the last 100 years. However, the definition of mean Ta is still a subject of debate. The most defensible definition might be the integral of the continuous temperature measurements over a day (Td0). However, for technological and historical reasons, mean Ta over land have been taken to be the average of the daily maximum and minimum temperature measurements (Td1). All existing principal global temperature analyses over land rely heavily on Td1. Here, I make a first quantitative assessment of the bias in the use of Td1 to estimate trends of mean Ta using hourly Ta observations at 5600 globally distributed weather stations from the 1970s to 2013. I find that the use of Td1 has a negligible impact on the global mean warming rate. However, the trend of Td1 has a substantial bias at regional and local scales, with a root mean square error of over 25% at 5° × 5° grids. Therefore, caution should be taken when using mean Ta datasets based on Td1 to examine high resolution details of warming trends.

Radiation Dry Bias of the Vaisala RS92 Humidity Sensor

NASA Technical Reports Server (NTRS)

Vomel, H.; Selkirk, H.; Miloshevich, L.; Valverde-Canossa, J.; Valdes, J.; Kyro, E.; Kivi, R.; Stolz, W.; Peng, G.; Diaz, J. A.

2007-01-01

The comparison of simultaneous humidity measurements by the Vaisala RS92 radiosonde and by the Cryogenic Frostpoint Hygrometer (CFH) launched at Alajuela, Cosla Rica, during July 2005 reveals a large solar radiation dry bias of the Vaisala RS92 humidity sensor and a minor temperature-dependent calibration error. For soundings launched at solar zenith angles between 10" and 30 , the average dry bias is on the order of 9% at the surface and increases to 50% at 15 km. A simple pressure- and temperature-dependent correction based on the comparison with the CFH can reduce this error to less than 7% at all altitudes up to 15.2 km, which is 700 m below the tropical tropopause. The correction does not depend on relative humidity, but is able to reproduce the relative humidity distribution observed by the CFH.

Is the global mean temperature trend too low?

NASA Astrophysics Data System (ADS)

Venema, Victor; Lindau, Ralf

2015-04-01

The global mean temperature trend may be biased due to similar technological and economic developments worldwide. In this study we want to present a number of recent results that suggest that the global mean temperature trend might be steeper as generally thought. In the Global Historical Climate Network version 3 (GHCNv3) the global land surface temperature is estimated to have increased by about 0.8°C between 1880 and 2012. In the raw temperature record, the increase is 0.6°C; the 0.2°C difference is due to homogenization adjustments. Given that homogenization can only reduce biases, this 0.2°C stems from a partial correction of bias errors and it seems likely that the real non-climatic trend bias will be larger. Especially in regions with sparser networks, homogenization will not be able to improve the trend much. Thus if the trend bias in these regions is similar to the bias for more dense networks (industrialized countries), one would expect the real bias to be larger. Stations in sparse networks are representative for a larger region and are given more weight in the computation of the global mean temperature. If all stations are given equal weight, the homogenization adjustments of the GHCNv3 dataset are about 0.4°C per century. In the subdaily HadISH dataset one break with mean size 0.12°C is found every 15 years for the period 1973-2013. That would be a trend bias of 0.78°C per century on a station by station basis. Unfortunately, these estimates strongly focus on Western countries having more stations. It is known from the literature that rich countries have a (statistically insignificant) stronger trend in the global datasets. Regional datasets can be better homogenized than global ones, the main reason being that global datasets do not contain all stations known to the weather services. Furthermore, global datasets use automatic homogenization methods and have less or no metadata. Thus while regional data can be biased themselves, comparing them with global datasets can provide some indication on biases. Compared to the global BEST dataset for the same countries, the national datasets of Austria, Italy and Switzerland have a 0.36°C per century stronger trend since 1901. For the trend since 1960 we can also take Australia, France and Slovenia into account and find a trend bias of 0.40°C per century. Relative to CRUCY the trend biases are smaller and only statistically significant for the period since 1980. The most direct way to study biases in the temperature records is by making parallel measurements with historical measurement set-ups. Several recent parallel data studies for the transition to Stevenson screens suggest larger biases: Austria 0.2°C, Spain 0.5 & 0.6°C. As well as older tropical ones: India 0.42°C and Sri Lanka 0.37°C. The smaller values from the Parker (1994) review mainly stem from parallel measurements from North-West Europe, which may have less problems with exposure. Furthermore, the influence of many historical transitions, especially the ones that could cause an artificial smaller trend, have not been studied in detail yet. We urgently need to study improvements of exposure (especially in the (sub-)tropics), increases in watering and irrigation, mechanical ventilation, better paints, relocations to airports, and relocations to suburbs of stations that started in the cities and from village centers to pasture, for example. Our current understanding surprisingly suggests that the more recent period may have the largest biases, but it could also be that even the best datasets are unable to improve earlier data sufficiently. If the temperature trend were actually larger it would reduce discrepancies between studies for a number of problems in climatology. For example, the estimates of transient climate sensitivity using instrumental data are lower as the one using climate models, volcanic eruptions or paleo data. Furthermore, several changes observed in the climate system are larger than expected. On the other hand, a large trend in the land surface temperature would make the discrepancy with the tropospheric temperature even larger (radiosondes and satellites) and it would introduce a larger difference between land and sea temperature trends. Concluding, at the moment there is no strong evidence yet that the temperature trend is underestimated. However, we do have a considerable amount of evidence that suggests that there is a moderate, but climatologically important bias that we should study with urgency. As far as we know there are no estimates for the remaining uncertainty in the global mean trend after homogenization. Also studies into the causes of cooling biases are a pressing need. (Many have contributed to this study, but it is not clear at this moment who would be official collaborators; they will be added later.)

Sensitivity of Coupled Tropical Pacific Model Biases to Convective Parameterization in CESM1

NASA Astrophysics Data System (ADS)

Woelfle, M. D.; Yu, S.; Bretherton, C. S.; Pritchard, M. S.

2018-01-01

Six month coupled hindcasts show the central equatorial Pacific cold tongue bias development in a GCM to be sensitive to the atmospheric convective parameterization employed. Simulations using the standard configuration of the Community Earth System Model version 1 (CESM1) develop a cold bias in equatorial Pacific sea surface temperatures (SSTs) within the first two months of integration due to anomalous ocean advection driven by overly strong easterly surface wind stress along the equator. Disabling the deep convection parameterization enhances the zonal pressure gradient leading to stronger zonal wind stress and a stronger equatorial SST bias, highlighting the role of pressure gradients in determining the strength of the cold bias. Superparameterized hindcasts show reduced SST bias in the cold tongue region due to a reduction in surface easterlies despite simulating an excessively strong low-level jet at 1-1.5 km elevation. This reflects inadequate vertical mixing of zonal momentum from the absence of convective momentum transport in the superparameterized model. Standard CESM1simulations modified to omit shallow convective momentum transport reproduce the superparameterized low-level wind bias and associated equatorial SST pattern. Further superparameterized simulations using a three-dimensional cloud resolving model capable of producing realistic momentum transport simulate a cold tongue similar to the default CESM1. These findings imply convective momentum fluxes may be an underappreciated mechanism for controlling the strength of the equatorial cold tongue. Despite the sensitivity of equatorial SST to these changes in convective parameterization, the east Pacific double-Intertropical Convergence Zone rainfall bias persists in all simulations presented in this study.

Regional Climate Simulations over North America: Interaction of Local Processes with Improved Large-Scale Flow.

NASA Astrophysics Data System (ADS)

Miguez-Macho, Gonzalo; Stenchikov, Georgiy L.; Robock, Alan

2005-04-01

The reasons for biases in regional climate simulations were investigated in an attempt to discern whether they arise from deficiencies in the model parameterizations or are due to dynamical problems. Using the Regional Atmospheric Modeling System (RAMS) forced by the National Centers for Environmental Prediction-National Center for Atmospheric Research reanalysis, the detailed climate over North America at 50-km resolution for June 2000 was simulated. First, the RAMS equations were modified to make them applicable to a large region, and its turbulence parameterization was corrected. The initial simulations showed large biases in the location of precipitation patterns and surface air temperatures. By implementing higher-resolution soil data, soil moisture and soil temperature initialization, and corrections to the Kain-Fritch convective scheme, the temperature biases and precipitation amount errors could be removed, but the precipitation location errors remained. The precipitation location biases could only be improved by implementing spectral nudging of the large-scale (wavelength of 2500 km) dynamics in RAMS. This corrected for circulation errors produced by interactions and reflection of the internal domain dynamics with the lateral boundaries where the model was forced by the reanalysis.

Validation of the Aura Microwave Limb Sounder Temperature and Geopotential Height Measurements

NASA Technical Reports Server (NTRS)

Schwartz, M. J.; Lambert, A.; Manney, G. L.; Read, W. G.; Livesey, N. J.; Froidevaux, L.; Ao, C. O.; Bernath, P. F.; Boone, C. D.; Cofield, R. E.;

A Quasi-Global Approach to Improve Day-Time Satellite Surface Soil Moisture Anomalies through the Land Surface Temperature Input

NASA Technical Reports Server (NTRS)

Parinussa, Robert M.; de Jeu, Richard A. M.; van Der Schalie, Robin; Crow, Wade T.; Lei, Fangni; Holmes, Thomas R. H.

2016-01-01

Passive microwave observations from various spaceborne sensors have been linked to the soil moisture of the Earth's surface layer. A new generation of passive microwave sensors are dedicated to retrieving this variable and make observations in the single theoretically optimal L-band frequency (1-2 GHz). Previous generations of passive microwave sensors made observations in a range of higher frequencies, allowing for simultaneous estimation of additional variables required for solving the radiative transfer equation. One of these additional variables is land surface temperature, which plays a unique role in the radiative transfer equation and has an influence on the final quality of retrieved soil moisture anomalies. This study presents an optimization procedure for soil moisture retrievals through a quasi-global precipitation-based verification technique, the so-called Rvalue metric. Various land surface temperature scenarios were evaluated in which biases were added to an existing linear regression, specifically focusing on improving the skills to capture the temporal variability of soil moisture. We focus on the relative quality of the day-time (01:30 pm) observations from the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E), as these are theoretically most challenging due to the thermal equilibrium theory, and existing studies indicate that larger improvements are possible for these observations compared to their night-time (01:30 am) equivalent. Soil moisture data used in this study were retrieved through the Land Parameter Retrieval Model (LPRM), and in line with theory, both satellite paths show a unique and distinct degradation as a function of vegetation density. Both the ascending (01:30 pm) and descending (01:30 am) paths of the publicly available and widely used AMSR-E LPRM soil moisture products were used for benchmarking purposes. Several scenarios were employed in which the land surface temperature input for the radiative transfer was varied by imposing a bias on an existing regression. These scenarios were evaluated through the Rvalue technique, resulting in optimal bias values on top of this regression. In a next step, these optimal bias values were incorporated in order to re-calibrate the existing linear regression, resulting in a quasi-global uniform LST relation for day-time observations. In a final step, day-time soil moisture retrievals using the re-calibrated land surface temperature relation were again validated through the Rvalue technique. Results indicate an average increasing Rvalue of 16.5%, which indicates a better performance obtained through the re-calibration. This number was confirmed through an independent Triple Collocation verification over the same domain, demonstrating an average root mean square error reduction of 15.3%. Furthermore, a comparison against an extensive in situ database (679 stations) also indicates a generally higher quality for the re-calibrated dataset. Besides the improved day-time dataset, this study furthermore provides insights on the relative quality of soil moisture retrieved from AMSR-E's day- and night-time observations.

Sensitivity of simulated South America Climate to the Land Surface Schemes in RegCM4

NASA Astrophysics Data System (ADS)

Llopart, Marta; da Rocha, Rosmeri; Reboita, Michelle; Cuadra, Santiago

2017-04-01

This work evaluates the impact of two land surface parameterizations on the simulated climate and its variability over South America (SA). Two numerical experiments using RegCM4 coupled with Biosphere-Atmosphere Transfer Scheme (RegBATS) and Community Land Model version 3.5 (RegCLM) land surface schemes are compared. For the period 1979-2008, RegCM4 simulations used 50 km horizontal grid spacing and the ERA-Interim reanalysis as initial and boundary conditions. For the period studied, both simulations represent the main observed spatial patterns of rainfall, air temperature and low level circulation over SA. However, concerning the precipitation intensity, RegCLM values are closer to the observations than RegBATS (it is in general, wetter) over most of SA. RegCLM also provides smaller biases for air temperature. Over the Amazon basin, the amplitudes of the annual cycles of the soil moisture, evapotranspiration and sensible heat flux are higher in RegBATS than in RegCLM. This indicates that RegBATS provides large amounts of water vapor to the atmosphere and has more available energy to increase the boundary layer and make it reach the level of free convection (higher sensible heat flux values) resulting in higher precipitation rates and a large wet bias. RegCLM is closer to the observations than RegBATS, presenting smaller wet and warm biases over the Amazon basin. On an interannual scale, the magnitudes of the anomalies of the precipitation and air temperature simulated by RegCLM are closer to the observations. In general, RegBATS simulates higher magnitude for the interannual variability signal.

Cloud Tolerance of Remote-Sensing Technologies to Measure Land Surface Temperature

NASA Technical Reports Server (NTRS)

Holmes, Thomas R. H.; Hain, Christopher R.; Anderson, Martha C.; Crow, Wade T.

2016-01-01

Conventional methods to estimate land surface temperature (LST) from space rely on the thermal infrared(TIR) spectral window and is limited to cloud-free scenes. To also provide LST estimates during periods with clouds, a new method was developed to estimate LST based on passive microwave(MW) observations. The MW-LST product is informed by six polar-orbiting satellites to create a global record with up to eight observations per day for each 0.25resolution grid box. For days with sufficient observations, a continuous diurnal temperature cycle (DTC) was fitted. The main characteristics of the DTC were scaled to match those of a geostationary TIR-LST product. This paper tests the cloud tolerance of the MW-LST product. In particular, we demonstrate its stable performance with respect to flux tower observation sites (four in Europe and nine in the United States), over a range of cloudiness conditions up to heavily overcast skies. The results show that TIR based LST has slightly better performance than MW-LST for clear-sky observations but suffers an increasing negative bias as cloud cover increases. This negative bias is caused by incomplete masking of cloud-covered areas within the TIR scene that affects many applications of TIR-LST. In contrast, for MW-LST we find no direct impact of clouds on its accuracy and bias. MW-LST can therefore be used to improve TIR cloud screening. Moreover, the ability to provide LST estimates for cloud-covered surfaces can help expand current clear-sky-only satellite retrieval products to all-weather applications.

The Met Office Global Coupled Model 3.0 and 3.1 (GC3.0 and GC3.1) Configurations

NASA Astrophysics Data System (ADS)

Williams, K. D.; Copsey, D.; Blockley, E. W.; Bodas-Salcedo, A.; Calvert, D.; Comer, R.; Davis, P.; Graham, T.; Hewitt, H. T.; Hill, R.; Hyder, P.; Ineson, S.; Johns, T. C.; Keen, A. B.; Lee, R. W.; Megann, A.; Milton, S. F.; Rae, J. G. L.; Roberts, M. J.; Scaife, A. A.; Schiemann, R.; Storkey, D.; Thorpe, L.; Watterson, I. G.; Walters, D. N.; West, A.; Wood, R. A.; Woollings, T.; Xavier, P. K.

2018-02-01

The Global Coupled 3 (GC3) configuration of the Met Office Unified Model is presented. Among other applications, GC3 is the basis of the United Kingdom's submission to the Coupled Model Intercomparison Project 6 (CMIP6). This paper documents the model components that make up the configuration (although the scientific descriptions of these components are in companion papers) and details the coupling between them. The performance of GC3 is assessed in terms of mean biases and variability in long climate simulations using present-day forcing. The suitability of the configuration for predictability on shorter time scales (weather and seasonal forecasting) is also briefly discussed. The performance of GC3 is compared against GC2, the previous Met Office coupled model configuration, and against an older configuration (HadGEM2-AO) which was the submission to CMIP5. In many respects, the performance of GC3 is comparable with GC2, however, there is a notable improvement in the Southern Ocean warm sea surface temperature bias which has been reduced by 75%, and there are improvements in cloud amount and some aspects of tropical variability. Relative to HadGEM2-AO, many aspects of the present-day climate are improved in GC3 including tropospheric and stratospheric temperature structure, most aspects of tropical and extratropical variability and top-of-atmosphere and surface fluxes. A number of outstanding errors are identified including a residual asymmetric sea surface temperature bias (cool northern hemisphere, warm Southern Ocean), an overly strong global hydrological cycle and insufficient European blocking.

Temporal Arctic longwave surface emissivity feedbacks in the Community Earth System Model

NASA Astrophysics Data System (ADS)

Kuo, C.; Feldman, D.; Huang, X.; Flanner, M.; Yang, P.; Chen, X.

2017-12-01

We have investigated how the inclusion of realistic and consistent surface emissivity in both land-surface and atmospheric components of the CESM coupled-climate model affects a wide range of climate variables. We did this by replacing the unit emissivity values in RRTMG_LW for water, fine-grained snow, and desert scenes with spectral emissivity values, and by replacing broadband emissivity values in surface components with the Planck-curve weighted counterparts. We find that this harmonized treatment of surface emissivity within CESM can be important for reducing high-latitude temperature biases. We also find that short-term effects of atmospheric dynamics and spectral information need to be considered to understand radiative effects in higher detail, and are possible with radiative kernels computed for every grid and time point for the entire model integration period. We find that conventional climatological feedback calculations indicate that sea-ice emissivity feedback is positive in sign, but that the radiative effects of the difference in emissivity between frozen and unfrozen surfaces exhibit seasonal dependence. Furthermore, this seasonality itself exhibits meridional asymmetry due to differences in sea-ice response to climate forcing between the Arctic and the Antarctic. In the Arctic, this seasonal, temporally higher order analysis exhibits increasing outgoing surface emissivity radiative response in a warming climate. While the sea-ice emissivity feedback and seasonal sea-ice emissivity radiative response amplitudes are a few percent of surface albedo feedbacks, the feedback analysis methods outlined in this work demonstrate that spatially and temporally localized feedback analysis can give insight into the mechanisms at work on those scales which differ in amplitude and sign from conventional climatological analyses. We note that the inclusion of this realistic physics leads to improved agreement between CESM model results and Arctic surface temperatures and sea-ice trends. This reduction of persistent high-latitude model biases suggests that the current unrealistic representation of surface emissivity in model component radiation routines may be an important contributing factor to cold-pole biases.

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

Xiang, Baoqiang; Zhao, Ming; Held, Isaac M.

The severity of the double Intertropical Convergence Zone (DI) problem in climate models can be measured by a tropical precipitation asymmetry index (PAI), indicating whether tropical precipitation favors the Northern Hemisphere or the Southern Hemisphere. Examination of 19 Coupled Model Intercomparison Project phase 5 models reveals that the PAI is tightly linked to the tropical sea surface temperature (SST) bias. As one of the factors determining the SST bias, the asymmetry of tropical net surface heat flux in Atmospheric Model Intercomparison Project (AMIP) simulations is identified as a skillful predictor of the PAI change from an AMIP to a coupledmore » simulation, with an intermodel correlation of 0.90. Using tropical top-of-atmosphere (TOA) fluxes, the correlations are lower but still strong. However, the extratropical asymmetries of surface and TOA fluxes in AMIP simulations cannot serve as useful predictors of the PAI change. Furthermore, this study suggests that the largest source of the DI bias is from the tropics and from atmospheric models.« less

Surface Energy Budget Disruption in the Northeast Pacific in Response to a Marine Heat Wave

NASA Astrophysics Data System (ADS)

Schmeisser, L.; Siedlecki, S. A.; Ackerman, T. P.; Bond, N. A.

2016-12-01

The surface energy budget of the ocean varies greatly over space and time as a result of ocean-atmosphere interactions. Changes in the budget due to variability in incident shortwave radiation can alter the thermal structure of the upper ocean, influence photosynthetic processes, and ultimately affect marine biogeochemistry. Thus, accurate representation of the surface energy budget over the oceans is essential for successfully modeling ocean processes and ocean-atmosphere interactions. Siedlecki et al. [Scientific Reports 6 (2016): 27203] show that NOAA's Climate Forecast System (CFS) shortwave radiation fields are biased high relative to CFS reanalysis data by about 50 W/m2 in the study area off the coast of Washington and Oregon. This bias varies in space and time and is known to exist in large scale climate models. The bias results in reduced skill in ocean forecasts at the surface, with specific impacts on sea surface temperature and biogeochemistry. In order to better understand the surface radiation balance over the ocean and the biases present in large scale climate models, we use several data sets to analyze an anomalous sea surface temperature event (marine heat wave, MHW) in the Northeast Pacific during 2014-2015. This `blob' of warm water disrupted ocean-atmosphere feedbacks in the region and altered the surface energy balance; thus, it provides a case study to better understand physical mechanisms at play in the surface radiation balance. CERES SYN1deg satellite data are compared to model output from CFS (1°x1° resolution) and WRF (12km resolution). We use all three fields to assess the impact of model resolution on the surface energy budget, as well as identify feedbacks in ocean-atmosphere processes that may differ between the observations and the models. Observational time series from 2009-15 of shortwave radiation, longwave radiation, and cloud parameters across 3 latitudinal lines (44.5N, 47N, 50N) in the Northeast Pacific (150W to 125W) clearly show disruption in cloud fraction, water content, and radiative fluxes during the MHW. The timing and spatial extent of the disruption differ in the models. The surface radiation budget for the Northeast Pacific over this time period from the observations and models is compared and discussed.

Subseasonal forecast skills and biases of global summer monsoons in the NCEP Climate Forecast System version 2

NASA Astrophysics Data System (ADS)

Liu, Xiangwen; Yang, Song; Li, Qiaoping; Kumar, Arun; Weaver, Scott; Liu, Shi

2014-03-01

Subseasonal forecast skills and biases of global summer monsoons are diagnosed using daily data from the hindcasts of 45-day integrations by the NCEP Climate Forecast System version 2. Predictions for subseasonal variability of zonal wind and precipitation are generally more skillful over the Asian and Australian monsoon regions than other monsoon regions. Climatologically, forecasts for the variations of dynamical monsoon indices have high skills at leads of about 2 weeks. However, apparent interannual differences exist, with high skills up to 5 weeks in exceptional cases. Comparisons for the relationships of monsoon indices with atmospheric circulation and precipitation patterns between skillful and unskillful forecasts indicate that skills for subseasonal variability of a monsoon index depend partially on the degree to which the observed variability of the index attributes to the variation of large-scale circulation. Thus, predictions are often more skillful when the index is closely linked to atmospheric circulation over a broad region than over a regional and narrow range. It is also revealed that, the subseasonal variations of biases of winds, precipitation, and surface temperature over various monsoon regions are captured by a first mode with seasonally independent biases and a second mode with apparent phase transition of biases during summer. The first mode indicates the dominance of overall weaker-than-observed summer monsoons over major monsoon regions. However, at certain stages of monsoon evolution, these underestimations are regionally offset or intensified by the time evolving biases portrayed by the second mode. This feature may be partially related to factors such as the shifts of subtropical highs and intertropical convergence zones, the reversal of biases of surface temperature over some monsoon regions, and the transition of regional circulation system. The significant geographical differences in bias growth with increasing lead time reflect the distinctions of initial memory capability of the climate system over different monsoon regions.

Downscaling with a nested regional climate model in near-surface fields over the contiguous United States: WRF dynamical downscaling

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

Wang, Jiali; Kotamarthi, Veerabhadra R.

The Weather Research and Forecasting (WRF) model is used for dynamic downscaling of 2.5 degree National Centers for Environmental Prediction-U.S. Department of Energy Reanalysis II (NCEP-R2) data for 1980-2010 at 12 km resolution over most of North America. The model's performance for surface air temperature and precipitation is evaluated by comparison with high-resolution observational data sets. The model's ability to add value is investigated by comparison with NCEP-R2 data and a 50 km regional climate simulation. The causes for major model bias are studied through additional sensitivity experiments with various model setup/integration approaches and physics representations. The WRF captures themore » main features of the spatial patterns and annual cycles of air temperature and precipitation over most of the contiguous United States. However, simulated air temperatures over the south central region and precipitation over the Great Plains and the Southwest have significant biases. Allowing longer spin-up time, reducing the nudging strength, or replacing the WRF Single-Moment 6-class microphysics with Morrison microphysics reduces the bias over some subregions. However, replacing the Grell-Devenyi cumulus parameterization with Kain-Fritsch shows no improvement. The 12 km simulation does add value above the NCEP-R2 data and the 50 km simulation over mountainous and coastal zones.« less

Implement a Sub-grid Turbulent Orographic Form Drag in WRF and its application to Tibetan Plateau

NASA Astrophysics Data System (ADS)

Zhou, X.; Yang, K.; Wang, Y.; Huang, B.

2017-12-01

Sub-grid-scale orographic variation exerts turbulent form drag on atmospheric flows. The Weather Research and Forecasting model (WRF) includes a turbulent orographic form drag (TOFD) scheme that adds the stress to the surface layer. In this study, another TOFD scheme has been incorporated in WRF3.7, which exerts an exponentially decaying drag on each model layer. To investigate the effect of the new scheme, WRF with the old and new one was used to simulate the climate over the complex terrain of the Tibetan Plateau. The two schemes were evaluated in terms of the direct impact (on wind) and the indirect impact (on air temperature, surface pressure and precipitation). Both in winter and summer, the new TOFD scheme reduces the mean bias in the surface wind, and clearly reduces the root mean square error (RMSEs) in comparisons with the station measurements (Figure 1). Meanwhile, the 2-m air temperature and surface pressure is also improved (Figure 2) due to the more warm air northward transport across south boundary of TP in winter. The 2-m air temperature is hardly improved in summer but the precipitation improvement is more obvious, with reduced mean bias and RMSEs. This is due to the weakening of water vapor flux (at low-level flow with the new scheme) crossing the Himalayan Mountains from South Asia.

Calibration and Validation of Aqua AIRS and AMSU Measurements using COSMIC Global Positioning System Radio Occultation Observations

NASA Astrophysics Data System (ADS)

Ho, S. P.; Peng, L.

2015-12-01

On board NASA Aqua satellite, the hyper-spectral infrared sounding from Atmospheric Infrared Sounder (AIRS) is the first of a new generation of operational remote sensors for upwelling atmospheric emission that provide excellent temperature and water vapor retrievals at middle atmosphere, which has significant impacts on short-term numerical weather forecasts. Also on board NASA Aqua satellite, Advanced Microwave Sounding Unit (AMSU) measurements provide the all weather temperature and water vapor profiles which are used as the first guess for AIRS inversion algorithm. However, due to lack of absolute on orbit calibration, both AIRS and AMSU also exhibit biases in retrieving atmospheric temperatures and moistures when compared with in situ measurements. These retrieval biases have diverse and complex dependencies on the temperature/moisture being measured, the season and geographical location, surface conditions, and sensor temperature, which is difficult to quantify. The purpose of this study is to demonstrate the usefulness of Global Positioning System (GPS) Radio Occultation (RO) data to serve as a climate calibration observatory in orbit to calibrate and validate AIRS and AMSU measurements. In this study, we use COSMIC RO data to simulate AMSU and AIRS brightness temperatures for the lower stratosphere (TLS) and compare them to AMSU TLS and those of AIRS brightness temperatures at the same height. Our analysis shows that because RO data do not contain mission-dependent biases and orbit drift errors, and are not affected by on-orbit heating and cooling of the satellite component, they are very useful to identify the AMSU time/location dependent biases for different NOAA missions and possible long term drift of the AIRS retrieved temperatures.

Graphene nanoribbon field effect transistor for nanometer-size on-chip temperature sensor

NASA Astrophysics Data System (ADS)

Banadaki, Yaser M.; Srivastava, Ashok; Sharifi, Safura

2016-04-01

Graphene has been extensively investigated as a promising material for various types of high performance sensors due to its large surface-to-volume ratio, remarkably high carrier mobility, high carrier density, high thermal conductivity, extremely high mechanical strength and high signal-to-noise ratio. The power density and the corresponding die temperature can be tremendously high in scaled emerging technology designs, urging the on-chip sensing and controlling of the generated heat in nanometer dimensions. In this paper, we have explored the feasibility of a thin oxide graphene nanoribbon (GNR) as nanometer-size temperature sensor for detecting local on-chip temperature at scaled bias voltages of emerging technology. We have introduced an analytical model for GNR FET for 22nm technology node, which incorporates both thermionic emission of high-energy carriers and band-to-band-tunneling (BTBT) of carriers from drain to channel regions together with different scattering mechanisms due to intrinsic acoustic phonons and optical phonons and line-edge roughness in narrow GNRs. The temperature coefficient of resistivity (TCR) of GNR FET-based temperature sensor shows approximately an order of magnitude higher TCR than large-area graphene FET temperature sensor by accurately choosing of GNR width and bias condition for a temperature set point. At gate bias VGS = 0.55 V, TCR maximizes at room temperature to 2.1×10-2 /K, which is also independent of GNR width, allowing the design of width-free GNR FET for room temperature sensing applications.

Ad hoc instrumentation methods in ecological studies produce highly biased temperature measurements

USGS Publications Warehouse

Terando, Adam J.; Youngsteadt, Elsa; Meineke, Emily K.; Prado, Sara G.

2017-01-01

In light of global climate change, ecological studies increasingly address effects of temperature on organisms and ecosystems. To measure air temperature at biologically relevant scales in the field, ecologists often use small, portable temperature sensors. Sensors must be shielded from solar radiation to provide accurate temperature measurements, but our review of 18 years of ecological literature indicates that shielding practices vary across studies (when reported at all), and that ecologists often invent and construct ad hoc radiation shields without testing their efficacy. We performed two field experiments to examine the accuracy of temperature observations from three commonly used portable data loggers (HOBO Pro, HOBO Pendant, and iButton hygrochron) housed in manufactured Gill shields or ad hoc, custom‐fabricated shields constructed from everyday materials such as plastic cups. We installed this sensor array (five replicates of 11 sensor‐shield combinations) at weather stations located in open and forested sites. HOBO Pro sensors with Gill shields were the most accurate devices, with a mean absolute error of 0.2°C relative to weather stations at each site. Error in ad hoc shield treatments ranged from 0.8 to 3.0°C, with the largest errors at the open site. We then deployed one replicate of each sensor‐shield combination at five sites that varied in the amount of urban impervious surface cover, which presents a further shielding challenge. Bias in sensors paired with ad hoc shields increased by up to 0.7°C for every 10% increase in impervious surface. Our results indicate that, due to variable shielding practices, the ecological literature likely includes highly biased temperature data that cannot be compared directly across studies. If left unaddressed, these errors will hinder efforts to predict biological responses to climate change. We call for greater standardization in how temperature data are recorded in the field, handled in analyses, and reported in publications.

Near Infrared Multispectral Mapping of Venus Supports the Hypothesis that Tessera Plateau Material was Formed in the Presence of Surface Water

NASA Astrophysics Data System (ADS)

Mueller, N. T.; Tsang, C.; Nunes, D. C.; Helbert, J.; Dyar, M. D.; Smrekar, S. E.

2017-12-01

The VIRTIS instrument on Venus Express observed surface thermal emission from the surface. Studies of 1020nm data showed that tessera plateaus, intensely tectonically deformed highlands that predate most other terrains, have significantly lower thermal emission than other highlands. Lower thermal emission could be due either to lower surface emissivity, supporting the hypothesis that tessera are analogous to continental crust on Earth, or to a bias of Magellan altimetry, which does not fully resolve the topographic relief of tessera terrain. To eliminate this ambiguity, we additionally investigate the spectral windows at 1100 and 1180nm. Data are reduced to surface emissivity using an atmospheric radiative transfer model to account for atmospheric scattering and absorption/emission. Magellan altimetry was used to model atmospheric column height and surface temperature. The model uses a binary (collision-induced) absorption coefficient for each window. It fits absolute radiance and gradient with surface elevation reasonably well, although there are indications that the assumed adiabatic temperature lapse rate is not appropriate globally. The 1100nm band has a relatively low signal-to-noise ratio at the latitudes of the tessera plateaus, but Alpha Regio is visible in both the 1020 and the 1180nm band. The difference in emissivity between Alpha and the adjacent corona Eve, which has a similar elevation as Alpha, is 3.6% at 1020nm, but only 2% at 1180nm. The altimetry bias equivalent to the 1020nm deviation is 230 m, while the equivalent is only 70m at 1180nm. An altimetry bias therefore cannot fully explain the observations, and there must be a real difference in emissivity. The observations are consistent with the hypothesis that Alpha Regio has a more felsic composition. The emissivity spectra of granites at Venus temperatures are lower than those of basalt at 1020nm, but the difference decreases or vanishes towards the 1180nm window. The most plausible explanation for continent-sized felsic plateaus would be a formation analogous to Earth's continents, i.e. differentiation of basaltic crust in the presence of water.

Comparing AIRS/AMSU-A Satellite and MERRA/MERRA-2 Reanalysis products with In-situ Station Observations at Summit, Greenland

NASA Astrophysics Data System (ADS)

Hearty, T. J., III; Vollmer, B.; Wei, J. C.; Huwe, P. M.; Albayrak, A.; Wu, D. L.; Cullather, R. I.; Meyer, D. L.; Lee, J. N.; Blaisdell, J. M.; Susskind, J.; Nowicki, S.

2017-12-01

The surface air and skin temperatures reported by the Atmospheric Infrared Sounder (AIRS), the Modern-Era Retrospective analysis for Research and Applications (MERRA), and MERRA-2 at Summit, Greenland are compared with near surface air temperatures measured at National Oceanic and Atmospheric Administration (NOAA) and Greenland Climate Network (GC-Net) weather stations. Therefore this investigation requires familiarity with a heterogeneous set of swath, grid, and point data in several different formats, different granularity, and different sampling. We discuss the current subsetting capabilities available at the GES DISC (Goddard Earth Sciences Data Information Services Center) to perform the inter-comparisons necessary to evaluate the quality and trustworthiness of these datasets. We also explore potential future services which may assist users with this type of intercomparison. We find the AIRS Surface Skin Temperature (TS) is best correlated with the NOAA 2 m air temperature (T2M) but it tends to be colder than the station measurements. The difference may be the result of the frequent near surface temperature inversions in the region. The AIRS Surface Air Temperature (SAT) is also well correlated with the NOAA T2M but it has a warm bias with respect to the NOAA T2M during the cold season and a larger standard error than surface temperature. This suggests that the extrapolation of the temperature profile to the surface is not valid for the strongest inversions. Comparing the temperature lapse rate derived from the 2 stations shows that the lapse rate can increase closer to the surface. We also find that the difference between the AIRS SAT and TS is sensitive to near surface inversions. The MERRA-2 surface and near surface temperatures show improvements over MERRA but little sensitivity to near surface temperature inversions.

Land surface energy budget during dry spells: global CMIP5 AMIP simulations vs. satellite observations

NASA Astrophysics Data System (ADS)

Gallego-Elvira, Belen; Taylor, Christopher M.; Harris, Phil P.; Ghent, Darren; Folwell, Sonja S.

2015-04-01

During extended periods without rain (dry spells), the soil can dry out due to vegetation transpiration and soil evaporation. At some point in this drying cycle, land surface conditions change from energy-limited to water-limited evapotranspiration, and this is accompanied by an increase of the ground and overlying air temperatures. Regionally, the characteristics of this transition determine the influence of soil moisture on air temperature and rainfall. Global Climate Models (GCMs) disagree on where and how strongly the surface energy budget is limited by soil moisture. Flux tower observations are improving our understanding of these dry down processes, but typical heterogeneous landscapes are too sparsely sampled to ascertain a representative regional response. Alternatively, satellite observations of land surface temperature (LST) provide indirect information about the surface energy partition at 1km resolution globally. In our study, we analyse how well the dry spell dynamics of LST are represented by GCMs across the globe. We use a spatially and temporally aggregated diagnostic to describe the composite response of LST during surface dry down in rain-free periods in distinct climatic regions. The diagnostic is derived from daytime MODIS-Terra LST observations and bias-corrected meteorological re-analyses, and compared against the outputs of historical climate simulations of seven models running the CMIP5 AMIP experiment. Dry spell events are stratified by antecedent precipitation, land cover type and geographic regions to assess the sensitivity of surface warming rates to soil moisture levels at the onset of a dry spell for different surface and climatic zones. In a number of drought-prone hot spot regions, we find important differences in simulated dry spell behaviour, both between models, and compared to observations. These model biases are likely to compromise seasonal forecasts and future climate projections.

Polarization Rotation and the Third Stokes Parameter: The Effects of Spacecraft Attitude and Faraday Rotation

NASA Technical Reports Server (NTRS)

Meissner, Thomas; Wentz, Frank J.

2006-01-01

The third Stokes parameter of ocean surface brightness temperatures measured by the WindSat instrument is sensitive to the rotation angle between the polarization vectors at the ocean surface and the instrument. This rotation angle depends on the spacecraft attitude (roll, pitch, yaw) as well as the Faraday rotation of the electromagnetic radiation passing through the Earth's ionosphere. Analyzing the WindSat antenna temperatures, we find biases in the third Stokes parameter as function of the along-scan position of up to 1.5 K in all feedhorns. This points to a misspecification of the reported spacecraft attitude. A single attitude correction of -0.16deg roll and 0.18deg pitch for the whole instrument eliminates all the biases. We also study the effect of Faraday rotation at 10.7 GHz on the accuracy of the third Stokes parameter and the sea surface wind direction retrieval and demonstrate how this error can be corrected using values from the International Reference Ionosphere for the total electron content when computing Faraday rotation.

Increased size selectivity of Si quantum dots on SiC at low substrate temperatures: An ion-assisted self-organization approach

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

Seo, D. H.; Das Arulsamy, A.; Rider, A. E.

A simple, effective, and innovative approach based on ion-assisted self-organization is proposed to synthesize size-selected Si quantum dots (QDs) on SiC substrates at low substrate temperatures. Using hybrid numerical simulations, the formation of Si QDs through a self-organization approach is investigated by taking into account two distinct cases of Si QD formation using the ionization energy approximation theory, which considers ionized in-fluxes containing Si{sup 3+} and Si{sup 1+} ions in the presence of a microscopic nonuniform electric field induced by a variable surface bias. The results show that the highest percentage of the surface coverage by 1 and 2 nmmore » size-selected QDs was achieved using a bias of -20 V and ions in the lowest charge state, namely, Si{sup 1+} ions in a low substrate temperature range (227-327 deg. C). As low substrate temperatures ({<=}500 deg. C) are desirable from a technological point of view, because (i) low-temperature deposition techniques are compatible with current thin-film Si-based solar cell fabrication and (ii) high processing temperatures can frequently cause damage to other components in electronic devices and destroy the tandem structure of Si QD-based third-generation solar cells, our results are highly relevant to the development of the third-generation all-Si tandem photovoltaic solar cells.« less

Increased size selectivity of Si quantum dots on SiC at low substrate temperatures: An ion-assisted self-organization approach

NASA Astrophysics Data System (ADS)

Seo, D. H.; Rider, A. E.; Das Arulsamy, A.; Levchenko, I.; Ostrikov, K.

2010-01-01

A simple, effective, and innovative approach based on ion-assisted self-organization is proposed to synthesize size-selected Si quantum dots (QDs) on SiC substrates at low substrate temperatures. Using hybrid numerical simulations, the formation of Si QDs through a self-organization approach is investigated by taking into account two distinct cases of Si QD formation using the ionization energy approximation theory, which considers ionized in-fluxes containing Si3+ and Si1+ ions in the presence of a microscopic nonuniform electric field induced by a variable surface bias. The results show that the highest percentage of the surface coverage by 1 and 2 nm size-selected QDs was achieved using a bias of -20 V and ions in the lowest charge state, namely, Si1+ ions in a low substrate temperature range (227-327 °C). As low substrate temperatures (≤500 °C) are desirable from a technological point of view, because (i) low-temperature deposition techniques are compatible with current thin-film Si-based solar cell fabrication and (ii) high processing temperatures can frequently cause damage to other components in electronic devices and destroy the tandem structure of Si QD-based third-generation solar cells, our results are highly relevant to the development of the third-generation all-Si tandem photovoltaic solar cells.

Sensitivity of the atmospheric water cycle to corrections of the sea surface temperature bias over southern Africa in a regional climate model

NASA Astrophysics Data System (ADS)

Weber, Torsten; Haensler, Andreas; Jacob, Daniela

2017-12-01

Regional climate models (RCMs) have been used to dynamically downscale global climate projections at high spatial and temporal resolution in order to analyse the atmospheric water cycle. In southern Africa, precipitation pattern were strongly affected by the moisture transport from the southeast Atlantic and southwest Indian Ocean and, consequently, by their sea surface temperatures (SSTs). However, global ocean models often have deficiencies in resolving regional to local scale ocean currents, e.g. in ocean areas offshore the South African continent. By downscaling global climate projections using RCMs, the biased SSTs from the global forcing data were introduced to the RCMs and affected the results of regional climate projections. In this work, the impact of the SST bias correction on precipitation, evaporation and moisture transport were analysed over southern Africa. For this analysis, several experiments were conducted with the regional climate model REMO using corrected and uncorrected SSTs. In these experiments, a global MPI-ESM-LR historical simulation was downscaled with the regional climate model REMO to a high spatial resolution of 50 × 50 km2 and of 25 × 25 km2 for southern Africa using a double-nesting method. The results showed a distinct impact of the corrected SST on the moisture transport, the meridional vertical circulation and on the precipitation pattern in southern Africa. Furthermore, it was found that the experiment with the corrected SST led to a reduction of the wet bias over southern Africa and to a better agreement with observations as without SST bias corrections.

Understanding Arctic surface temperature differences in reanalyses

NASA Astrophysics Data System (ADS)

Cullather, R. I.; Zhao, B.; Shuman, C. A.; Nowicki, S.

2017-12-01

Reanalyses in the Arctic are widely used for model evaluation and for understanding contemporary climate change. Nevertheless, differences among reanalyses in fundamental meteorological variables including surface air temperature are large. For example, the 1980-2009 mean surface air temperature for the north polar cap (70°N-90°N) among global reanalyses span a range of 2.4 K, which approximates the average warming trend from these reanalyses over the 30-year period of 2.1 K. Understanding these differences requires evaluation over the three principal surface domains of the Arctic: glaciated land, the unglaciated terrestrial surface, and sea ice/ocean. An examination is conducted of contemporary global reanalyses of the ECMWF Interim project, NASA MERRA, MERRA-2, JRA-55, and NOAA CFSR using available in situ data and assessments of the surface energy budget. Overly-simplistic representations of the Greenland Ice Sheet surface are found to be associated with local warm air temperature biases in winter. A review of progress made in the development of the MERRA-2 land-ice representation is presented. Large uncertainty is also found in temperatures over the Arctic tundra and boreal forest zone. But a key focus of temperature differences for northern high latitudes is the Arctic Ocean. Near-surface air temperature differences over the Arctic Ocean are found to be related to discrepancies in sea ice and sea surface temperature boundary data, which are severely compromised in current reanalyses. Issues with the modeled representation of sea ice cover are an additional factor in reanalysis temperature trends. Differences in the representation of the surface energy budget among the various reanalyses are also reviewed.

Understanding Arctic Surface Temperature Differences in Reanalyses

NASA Technical Reports Server (NTRS)

Cullather, Richard; Zhao, Bin; Shuman, Christopher; Nowicki, Sophie

2017-01-01

Reanalyses in the Arctic are widely used for model evaluation and for understanding contemporary climate change. Nevertheless, differences among reanalyses in fundamental meteorological variables including surface air temperature are large. For example, the 1980-2009 mean surface air temperature for the north polar cap (70ÂdegN-90ÂdegN) among global reanalyses span a range of 2.4 K, which approximates the average warming trend from these reanalyses over the 30-year period of 2.1 K. Understanding these differences requires evaluation over the three principal surface domains of the Arctic: glaciated land, the unglaciated terrestrial surface, and sea ice/ocean. An examination is conducted of contemporary global reanalyses of the ECMWF Interim project, NASA MERRA, MERRA-2, JRA-55, and NOAA CFSR using available in situ data and assessments of the surface energy budget. Overly-simplistic representations of the Greenland Ice Sheet surface are found to be associated with local warm air temperature biases in winter. A review of progress made in the development of the MERRA-2 land-ice representation is presented. Large uncertainty is also found in temperatures over the Arctic tundra and boreal forest zone. But a key focus of temperature differences for northern high latitudes is the Arctic Ocean. Near-surface air temperature differences over the Arctic Ocean are found to be related to discrepancies in sea ice and sea surface temperature boundary data, which are severely compromised in current reanalyses. Issues with the modeled representation of sea ice cover are an additional factor in reanalysis temperature trends. Differences in the representation of the surface energy budget among the various reanalyses are also reviewed.

A comparison of Argo nominal surface and near-surface temperature for validation of AMSR-E SST

NASA Astrophysics Data System (ADS)

Liu, Zenghong; Chen, Xingrong; Sun, Chaohui; Wu, Xiaofen; Lu, Shaolei

2017-05-01

Satellite SST (sea surface temperature) from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) is compared with in situ temperature observations from Argo profiling floats over the global oceans to evaluate the advantages of Argo NST (near-surface temperature: water temperature less than 1 m from the surface). By comparing Argo nominal surface temperature ( 5 m) with its NST, a diurnal cycle caused by daytime warming and nighttime cooling was found, along with a maximum warming of 0.08±0.36°C during 14:00-15:00 local time. Further comparisons between Argo 5-m temperature/Argo NST and AMSR-E SST retrievals related to wind speed, columnar water vapor, and columnar cloud water indicate warming biases at low wind speed (<5 m/s) and columnar water vapor >28 mm during daytime. The warming tendency is more remarkable for AMSR-E SST/Argo 5-m temperature compared with AMSR-E SST/Argo NST, owing to the effect of diurnal warming. This effect of diurnal warming events should be excluded before validation for microwave SST retrievals. Both AMSR-E nighttime SST/Argo 5-m temperature and nighttime SST/Argo NST show generally good agreement, independent of wind speed and columnar water vapor. From our analysis, Argo NST data demonstrated their advantages for validation of satellite-retrieved SST.

Effects of exchange bias on magnetotransport in permalloy kagome artificial spin ice

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

Le, B. L.; Rench, D. W.; Misra, R.

2015-02-01

We investigate the magnetotransport properties of connected kagome artificial spin ice networks composed of permalloy nanowires. Our data show clear evidence of magnetic switching among the wires, both in the longitudinal and transverse magnetoresistance. An unusual asymmetry with field sweep direction appears at temperatures below about 20 K that appears to be associated with exchange bias resulting from surface oxidation of permalloy, and which disappears in alumina-capped samples. These results demonstrate that exchange bias is a phenomenon that must be considered in understanding the physics of such artificial spin ice systems, and that opens up new possibilities for their control.

Nanostructuring of Palladium with Low-Temperature Helium Plasma

PubMed Central

Fiflis, P.; Christenson, M.P.; Connolly, N.; Ruzic, D.N.

2015-01-01

Impingement of high fluxes of helium ions upon metals at elevated temperatures has given rise to the growth of nanostructured layers on the surface of several metals, such as tungsten and molybdenum. These nanostructured layers grow from the bulk material and have greatly increased surface area over that of a not nanostructured surface. They are also superior to deposited nanostructures due to a lack of worries over adhesion and differences in material properties. Several palladium samples of varying thickness were biased and exposed to a helium helicon plasma. The nanostructures were characterized as a function of the thickness of the palladium layer and of temperature. Bubbles of ~100 nm in diameter appear to be integral to the nanostructuring process. Nanostructured palladium is also shown to have better catalytic activity than not nanostructured palladium. PMID:28347109

Nanostructuring of Palladium with Low-Temperature Helium Plasma.

PubMed

Fiflis, P; Christenson, M P; Connolly, N; Ruzic, D N

2015-11-25

Impingement of high fluxes of helium ions upon metals at elevated temperatures has given rise to the growth of nanostructured layers on the surface of several metals, such as tungsten and molybdenum. These nanostructured layers grow from the bulk material and have greatly increased surface area over that of a not nanostructured surface. They are also superior to deposited nanostructures due to a lack of worries over adhesion and differences in material properties. Several palladium samples of varying thickness were biased and exposed to a helium helicon plasma. The nanostructures were characterized as a function of the thickness of the palladium layer and of temperature. Bubbles of ~100 nm in diameter appear to be integral to the nanostructuring process. Nanostructured palladium is also shown to have better catalytic activity than not nanostructured palladium.

Satellite-Derived Sea Surface Temperature: Workshop-2

NASA Technical Reports Server (NTRS)

Njoku, E. G.

1984-01-01

Global accuracies and error characteristics of presently orbiting satellite sensors are examined. The workshops are intended to lead to a better understanding of present capabilities for sea surface temperature measurement and to improve measurement concepts for the future. Data from the Advanced Very High Resolution Radiometer AVHRR and Scanning Multichannel Microwave Radiometer is emphasized. Some data from the High Resolution Infrared Sounder HIRS and AVHRR are also examined. Comparisons of satellite data with ship and eXpendable BathyThermograph XBT measurement show standard deviations in the range 0.5 to 1.3 C with biases of less than 0.4 C, depending on the sensor, ocean region, and spatial/temporal averaging. The Sea Surface Temperature SST anomaly maps show good agreement in some cases, but a number of sensor related problems are identified.

Improving representation of canopy temperatures for modeling subcanopy incoming longwave radiation to the snow surface

NASA Astrophysics Data System (ADS)

Webster, Clare; Rutter, Nick; Jonas, Tobias

2017-09-01

A comprehensive analysis of canopy surface temperatures was conducted around a small and large gap at a forested alpine site in the Swiss Alps during the 2015 and 2016 snowmelt seasons (March-April). Canopy surface temperatures within the small gap were within 2-3°C of measured reference air temperature. Vertical and horizontal variations in canopy surface temperatures were greatest around the large gap, varying up to 18°C above measured reference air temperature during clear-sky days. Nighttime canopy surface temperatures around the study site were up to 3°C cooler than reference air temperature. These measurements were used to develop a simple parameterization for correcting reference air temperature for elevated canopy surface temperatures during (1) nighttime conditions (subcanopy shortwave radiation is 0 W m-2) and (2) periods of increased subcanopy shortwave radiation >400 W m-2 representing penetration of shortwave radiation through the canopy. Subcanopy shortwave and longwave radiation collected at a single point in the subcanopy over a 24 h clear-sky period was used to calculate a nighttime bulk offset of 3°C for scenario 1 and develop a multiple linear regression model for scenario 2 using reference air temperature and subcanopy shortwave radiation to predict canopy surface temperature with a root-mean-square error (RMSE) of 0.7°C. Outside of these two scenarios, reference air temperature was used to predict subcanopy incoming longwave radiation. Modeling at 20 radiometer locations throughout two snowmelt seasons using these parameterizations reduced the mean bias and RMSE to below 10 W m s-2 at all locations.

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.

Logarithmic singularities and quantum oscillations in magnetically doped topological insulators

NASA Astrophysics Data System (ADS)

Nandi, D.; Sodemann, Inti; Shain, K.; Lee, G. H.; Huang, K.-F.; Chang, Cui-Zu; Ou, Yunbo; Lee, S. P.; Ward, J.; Moodera, J. S.; Kim, P.; Yacoby, A.

2018-02-01

We report magnetotransport measurements on magnetically doped (Bi,Sb ) 2Te3 films grown by molecular beam epitaxy. In Hall bar devices, we observe logarithmic dependence of transport coefficients in temperature and bias voltage which can be understood to arise from electron-electron interaction corrections to the conductivity and self-heating. Submicron scale devices exhibit intriguing quantum oscillations at high magnetic fields with dependence on bias voltage. The observed quantum oscillations can be attributed to bulk and surface transport.

Validity of Core Temperature Measurements at 3 Rectal Depths During Rest, Exercise, Cold-Water Immersion, and Recovery

PubMed Central

Miller, Kevin C.; Hughes, Lexie E.; Long, Blaine C.; Adams, William M.; Casa, Douglas J.

2017-01-01

Context: No evidence-based recommendation exists regarding how far clinicians should insert a rectal thermistor to obtain the most valid estimate of core temperature. Knowing the validity of temperatures at different rectal depths has implications for exertional heat-stroke (EHS) management. Objective: To determine whether rectal temperature (Trec) taken at 4 cm, 10 cm, or 15 cm from the anal sphincter provides the most valid estimate of core temperature (as determined by esophageal temperature [Teso]) during similar stressors an athlete with EHS may experience. Design: Cross-sectional study. Setting: Laboratory. Patients or Other Participants: Seventeen individuals (14 men, 3 women: age = 23 ± 2 years, mass = 79.7 ± 12.4 kg, height = 177.8 ± 9.8 cm, body fat = 9.4% ± 4.1%, body surface area = 1.97 ± 0.19 m2). Intervention(s): Rectal temperatures taken at 4 cm, 10 cm, and 15 cm from the anal sphincter were compared with Teso during a 10-minute rest period; exercise until the participant's Teso reached 39.5°C; cold-water immersion (∼10°C) until all temperatures were ≤38°C; and a 30-minute postimmersion recovery period. The Teso and Trec were compared every minute during rest and recovery. Because exercise and cooling times varied, we compared temperatures at 10% intervals of total exercise and cooling durations for these periods. Main Outcome Measure(s): The Teso and Trec were used to calculate bias (ie, the difference in temperatures between sites). Results: Rectal depth affected bias (F2,24 = 6.8, P = .008). Bias at 4 cm (0.85°C ± 0.78°C) was higher than at 15 cm (0.65°C ± 0.68°C, P < .05) but not higher than at 10 cm (0.75°C ± 0.76°C, P > .05). Bias varied over time (F2,34 = 79.5, P < .001). Bias during rest (0.42°C ± 0.27°C), exercise (0.23°C ± 0.53°C), and recovery (0.65°C ± 0.35°C) was less than during cooling (1.72°C ± 0.65°C, P < .05). Bias during exercise was less than during postimmersion recovery (0.65°C ± 0.35°C, P < .05). Conclusions: When EHS is suspected, clinicians should insert the flexible rectal thermistor to 15 cm (6 in) because it is the most valid depth. The low level of bias during exercise suggests Trec is valid for diagnosing hyperthermia. Rectal temperature is a better indicator of pelvic organ temperature during cold-water immersion than is Teso. PMID:28207294

Validity of Core Temperature Measurements at 3 Rectal Depths During Rest, Exercise, Cold-Water Immersion, and Recovery.

PubMed

Miller, Kevin C; Hughes, Lexie E; Long, Blaine C; Adams, William M; Casa, Douglas J

2017-04-01

  No evidence-based recommendation exists regarding how far clinicians should insert a rectal thermistor to obtain the most valid estimate of core temperature. Knowing the validity of temperatures at different rectal depths has implications for exertional heat-stroke (EHS) management.   To determine whether rectal temperature (T rec ) taken at 4 cm, 10 cm, or 15 cm from the anal sphincter provides the most valid estimate of core temperature (as determined by esophageal temperature [T eso ]) during similar stressors an athlete with EHS may experience.   Cross-sectional study.   Laboratory.   Seventeen individuals (14 men, 3 women: age = 23 ± 2 years, mass = 79.7 ± 12.4 kg, height = 177.8 ± 9.8 cm, body fat = 9.4% ± 4.1%, body surface area = 1.97 ± 0.19 m 2 ).   Rectal temperatures taken at 4 cm, 10 cm, and 15 cm from the anal sphincter were compared with T eso during a 10-minute rest period; exercise until the participant's T eso reached 39.5°C; cold-water immersion (∼10°C) until all temperatures were ≤38°C; and a 30-minute postimmersion recovery period. The T eso and T rec were compared every minute during rest and recovery. Because exercise and cooling times varied, we compared temperatures at 10% intervals of total exercise and cooling durations for these periods.   The T eso and T rec were used to calculate bias (ie, the difference in temperatures between sites).   Rectal depth affected bias (F 2,24 = 6.8, P = .008). Bias at 4 cm (0.85°C ± 0.78°C) was higher than at 15 cm (0.65°C ± 0.68°C, P < .05) but not higher than at 10 cm (0.75°C ± 0.76°C, P > .05). Bias varied over time (F 2,34 = 79.5, P < .001). Bias during rest (0.42°C ± 0.27°C), exercise (0.23°C ± 0.53°C), and recovery (0.65°C ± 0.35°C) was less than during cooling (1.72°C ± 0.65°C, P < .05). Bias during exercise was less than during postimmersion recovery (0.65°C ± 0.35°C, P < .05).   When EHS is suspected, clinicians should insert the flexible rectal thermistor to 15 cm (6 in) because it is the most valid depth. The low level of bias during exercise suggests T rec is valid for diagnosing hyperthermia. Rectal temperature is a better indicator of pelvic organ temperature during cold-water immersion than is T eso .

Brillouin spectroscopy of fluid inclusions proposed as a paleothermometer for subsurface rocks.

PubMed

El Mekki-Azouzi, Mouna; Tripathi, Chandra Shekhar Pati; Pallares, Gaël; Gardien, Véronique; Caupin, Frédéric

2015-08-28

As widespread, continuous instrumental Earth surface air temperature records are available only for the last hundred fifty years, indirect reconstructions of past temperatures are obtained by analyzing "proxies". Fluid inclusions (FIs) present in virtually all rock minerals including exogenous rocks are routinely used to constrain formation temperature of crystals. The method relies on the presence of a vapour bubble in the FI. However, measurements are sometimes biased by surface tension effects. They are even impossible when the bubble is absent (monophasic FI) for kinetic or thermodynamic reasons. These limitations are common for surface or subsurface rocks. Here we use FIs in hydrothermal or geodic quartz crystals to demonstrate the potential of Brillouin spectroscopy in determining the formation temperature of monophasic FIs without the need for a bubble. Hence, this novel method offers a promising way to overcome the above limitations.

Brillouin spectroscopy of fluid inclusions proposed as a paleothermometer for subsurface rocks

PubMed Central

Mekki-Azouzi, Mouna El; Tripathi, Chandra Shekhar Pati; Pallares, Gaël; Gardien, Véronique; Caupin, Frédéric

2015-01-01

As widespread, continuous instrumental Earth surface air temperature records are available only for the last hundred fifty years, indirect reconstructions of past temperatures are obtained by analyzing “proxies”. Fluid inclusions (FIs) present in virtually all rock minerals including exogenous rocks are routinely used to constrain formation temperature of crystals. The method relies on the presence of a vapour bubble in the FI. However, measurements are sometimes biased by surface tension effects. They are even impossible when the bubble is absent (monophasic FI) for kinetic or thermodynamic reasons. These limitations are common for surface or subsurface rocks. Here we use FIs in hydrothermal or geodic quartz crystals to demonstrate the potential of Brillouin spectroscopy in determining the formation temperature of monophasic FIs without the need for a bubble. Hence, this novel method offers a promising way to overcome the above limitations. PMID:26316328

Sensitivity of simulated South America climate to the land surface schemes in RegCM4

NASA Astrophysics Data System (ADS)

Llopart, Marta; da Rocha, Rosmeri P.; Reboita, Michelle; Cuadra, Santiago

2017-12-01

This work evaluates the impact of two land surface parameterizations on the simulated climate and its variability over South America (SA). Two numerical experiments using RegCM4 coupled with the Biosphere-Atmosphere Transfer Scheme (RegBATS) and the Community Land Model version 3.5 (RegCLM) land surface schemes are compared. For the period 1979-2008, RegCM4 simulations used 50 km horizontal grid spacing and the ERA-Interim reanalysis as initial and boundary conditions. For the period studied, both simulations represent the main observed spatial patterns of rainfall, air temperature and low level circulation over SA. However, with regard to the precipitation intensity, RegCLM values are closer to the observations than RegBATS (it is wetter in general) over most of SA. RegCLM also produces smaller biases for air temperature. Over the Amazon basin, the amplitudes of the annual cycles of the soil moisture, evapotranspiration and sensible heat flux are higher in RegBATS than in RegCLM. This indicates that RegBATS provides large amounts of water vapor to the atmosphere and has more available energy to increase the boundary layer thickness and cause it to reach the level of free convection (higher sensible heat flux values) resulting in higher precipitation rates and a large wet bias. RegCLM is closer to the observations than RegBATS, presenting smaller wet and warm biases over the Amazon basin. On an interannual scale, the magnitudes of the anomalies of the precipitation and air temperature simulated by RegCLM are closer to the observations. In general, RegBATS simulates higher magnitude for the interannual variability signal.

A new dynamical downscaling approach with GCM bias corrections and spectral nudging

NASA Astrophysics Data System (ADS)

Xu, Zhongfeng; Yang, Zong-Liang

2015-04-01

To improve confidence in regional projections of future climate, a new dynamical downscaling (NDD) approach with both general circulation model (GCM) bias corrections and spectral nudging is developed and assessed over North America. GCM biases are corrected by adjusting GCM climatological means and variances based on reanalysis data before the GCM output is used to drive a regional climate model (RCM). Spectral nudging is also applied to constrain RCM-based biases. Three sets of RCM experiments are integrated over a 31 year period. In the first set of experiments, the model configurations are identical except that the initial and lateral boundary conditions are derived from either the original GCM output, the bias-corrected GCM output, or the reanalysis data. The second set of experiments is the same as the first set except spectral nudging is applied. The third set of experiments includes two sensitivity runs with both GCM bias corrections and nudging where the nudging strength is progressively reduced. All RCM simulations are assessed against North American Regional Reanalysis. The results show that NDD significantly improves the downscaled mean climate and climate variability relative to other GCM-driven RCM downscaling approach in terms of climatological mean air temperature, geopotential height, wind vectors, and surface air temperature variability. In the NDD approach, spectral nudging introduces the effects of GCM bias corrections throughout the RCM domain rather than just limiting them to the initial and lateral boundary conditions, thereby minimizing climate drifts resulting from both the GCM and RCM biases.

METRIC model for the estimation and mapping of evapotranspiration in a super intensive olive orchard in Southern Portugal

NASA Astrophysics Data System (ADS)

Pôças, Isabel; Nogueira, António; Paço, Teresa A.; Sousa, Adélia; Valente, Fernanda; Silvestre, José; Andrade, José A.; Santos, Francisco L.; Pereira, Luís S.; Allen, Richard G.

2013-04-01

Satellite-based surface energy balance models have been successfully applied to estimate and map evapotranspiration (ET). The METRICtm model, Mapping EvapoTranspiration at high Resolution using Internalized Calibration, is one of such models. METRIC has been widely used over an extensive range of vegetation types and applications, mostly focusing annual crops. In the current study, the single-layer-blended METRIC model was applied to Landsat5 TM and Landsat7 ETM+ images to produce estimates of evapotranspiration (ET) in a super intensive olive orchard in Southern Portugal. In sparse woody canopies as in olive orchards, some adjustments in METRIC application related to the estimation of vegetation temperature and of momentum roughness length and sensible heat flux (H) for tall vegetation must be considered. To minimize biases in H estimates due to uncertainties in the definition of momentum roughness length, the Perrier function based on leaf area index and tree canopy architecture, associated with an adjusted estimation of crop height, was used to obtain momentum roughness length estimates. Additionally, to minimize the biases in surface temperature simulations, due to soil and shadow effects, the computation of radiometric temperature considered a three-source condition, where Ts=fcTc+fshadowTshadow+fsunlitTsunlit. As such, the surface temperature (Ts), derived from the thermal band of the Landsat images, integrates the temperature of the canopy (Tc), the temperature of the shaded ground surface (Tshadow), and the temperature of the sunlit ground surface (Tsunlit), according to the relative fraction of vegetation (fc), shadow (fshadow) and sunlit (fsunlit) ground surface, respectively. As the sunlit canopies are the primary source of energy exchange, the effective temperature for the canopy was estimated by solving the three-source condition equation for Tc. To evaluate METRIC performance to estimate ET over the olive grove, several parameters derived from the algorithm were tested against data collected in the field, including eddy covariance ET, surface temperature over the canopy and soil temperature in shaded and sunlit conditions. Additionally, the results were also compared with results published in the literature. The information obtained so far revealed very interesting perspectives for the use of METRIC in the estimation and mapping of ET in super intensive olive orchards. Thereby, this approach might constitute a useful tool towards the improvement of the efficiency of irrigation water management in this crop. The study described is still under way, and thus further applications of METRIC algorithm to a larger number of images and to olive groves with different tree density are planned.

Optimal Extraction of Tropospheric Ozone Column by Simultaneous Use of OMI and TES Data and the Surface Temperature

NASA Astrophysics Data System (ADS)

Mobasheri, M. R.; Shirazi, H.

2015-12-01

This article aims to increase the accuracy of Ozone data from tropospheric column (TOC) of the OMI and TES satellite instruments. To validate the estimated amount of satellite data, Ozonesonde data is used. The vertical resolution in both instruments in the tropospheric atmosphere decreases so that the degree of freedom signals (DOFS) on the average for TES is reduced to 2 and for OMI is reduced to1. But this decline in accuracy in estimation of tropospheric ozone is more obvious in urban areas so that estimated ozone in both instruments alone in non-urban areas show a high correlation with Ozonesonde. But in urban areas this correlation is significantly reduced, due to the ozone pre-structures and consequently an increase on surface-level ozone in urban areas. In order to improve the accuracy of satellite data, the average tropospheric ozone data from the two instruments were used. The aim is to increase the vertical resolution of ozone profile and the results clearly indicate an increase in correlations, but nevertheless the satellite data have a positive bias towards the earth data. To reduce the bias, with the solar flux and nitrogen dioxide values and surface temperatures are calculated as factors of ozone production on the earth's surface and formation of mathematical equations based on coefficients for each of the mentioned values and multiplication of these coefficients by satellite data and repeated comparison with the values of Ozonesonde, the results showed that bias in urban areas is greatly reduced.

Effect of atomic layer deposition temperature on current conduction in Al2O3 films formed using H2O oxidant

NASA Astrophysics Data System (ADS)

Hiraiwa, Atsushi; Matsumura, Daisuke; Kawarada, Hiroshi

2016-08-01

To develop high-performance, high-reliability gate insulation and surface passivation technologies for wide-bandgap semiconductor devices, the effect of atomic layer deposition (ALD) temperature on current conduction in Al2O3 films is investigated based on the recently proposed space-charge-controlled field emission model. Leakage current measurement shows that Al2O3 metal-insulator-semiconductor capacitors formed on the Si substrates underperform thermally grown SiO2 capacitors at the same average field. However, using equivalent oxide field as a more practical measure, the Al2O3 capacitors are found to outperform the SiO2 capacitors in the cases where the capacitors are negatively biased and the gate material is adequately selected to reduce virtual dipoles at the gate/Al2O3 interface. The Al2O3 electron affinity increases with the increasing ALD temperature, but the gate-side virtual dipoles are not affected. Therefore, the leakage current of negatively biased Al2O3 capacitors is approximately independent of the ALD temperature because of the compensation of the opposite effects of increased electron affinity and permittivity in Al2O3. By contrast, the substrate-side sheet of charge increases with increasing ALD temperature above 210 °C and hence enhances the current of positively biased Al2O3 capacitors more significantly at high temperatures. Additionally, an anomalous oscillatory shift of the current-voltage characteristics with ALD temperature was observed in positively biased capacitors formed by low-temperature (≤210 °C) ALD. This shift is caused by dipoles at the Al2O3/underlying SiO2 interface. Although they have a minimal positive-bias leakage current, the low-temperature-grown Al2O3 films cause the so-called blisters problem when heated above 400 °C. Therefore, because of the absence of blistering, a 450 °C ALD process is presently the most promising technology for growing high-reliability Al2O3 films.

Large exchange bias effect in NiFe2O4/CoO nanocomposites

NASA Astrophysics Data System (ADS)

Mohan, Rajendra; Prasad Ghosh, Mritunjoy; Mukherjee, Samrat

2018-03-01

In this work, we report the exchange bias effect of NiFe2O4/CoO nanocomposites, synthesized via chemical co-precipitation method. Four samples of different particle size ranging from 4 nm to 31 nm were prepared with the annealing temperature varying from 200 °C to 800 °C. X-ray diffraction analysis of all the samples confirmed the presence of cubic spinel phase of Nickel ferrite along with CoO phase without trace of any impurity. Sizes of the particles were studied from transmission electron micrographs and were found to be in agreement with those estimated from x-ray diffraction. Field cooled (FC) hysteresis loops at 5 K revealed an exchange bias (HE) of 2.2 kOe for the sample heated at 200 °C which decreased with the increase of particle size. Exchange bias expectedly vanished at 300 K due to high thermal energy (kBT) and low effective surface anisotropy. M-T curves revealed a blocking temperature of 135 K for the sample with smaller particle size.

The Continuation of Cloud Statistics for NASA Climate Change Studies

NASA Technical Reports Server (NTRS)

Wylie, Donald P.

2001-01-01

The weather systems, cyclones, and anticyclones, along with air trajectories and cloud forms, are compared to past studies of the Arctic to assess compatibility of the four month study of the Arctic Cloud Experiment flights of the First ISCCP Regional Experiment (FIRE/ACE) with past climatologies. The frequency and movement of cyclones (lows) and anticyclones (highs) followed the general eastward and northeastward directions indicated by past studies. Most cyclones (lows) came from eastern Siberia and the Bering Sea to the south and moved north across the Bering Straight or Alaska into the Arctic Ocean. They generally weakened in central pressure as they moved poleward. Anticyclones (highs) were most common in the eastern Beaufort Sea near Canada in June and July as predicted from previous studies. However, many cyclones and anticyclones moved in westward directions which is rare in other latitudes. Erratic changes in shape and intensity on a daily basis also were observed. The National Center for Environmental Prediction (NCEP) analysis generally reflected the Surface Heat Budget in the Arctic (SHEBA) Ship World Meteorological Organization (WMO) observations which it used. However, NCEP temperatures were biased warm by 1.0 to 1.5 C in April and early May. In July when the surface temperature were at the freezing/thawing point, the NCEP analysis changed to a cold bias of -1.0 C. Dew points had smaller biases except for July where they were biased cold by -1.4 C. Wind speeds had a -2 m/s low bias for the six windiest days. Surface barometric pressures had consistently low biases from -1.2 to -2.8 hPa in all four months. Air parcel historical trajectories were mainly from the south or from local anticyclonic gyres in the Beaufort Sea. Most air came to the SHEBA Ship from the north Pacific Ocean or from Alaska and Canada and occasionally from eastern Siberia. Very few trajectories traced back across the pole to Europe and Central Asia. Cloud cover was high, as expected, from 69-86% of the time. Satellite data also indicate frequent stratus, altostratus, and cirrus clouds (occurring 61% of the time) above the expected boundary layer fog and Arctic stratus clouds.

Assessing impacts of PBL and surface layer schemes in simulating the surface–atmosphere interactions and precipitation over the tropical ocean using observations from AMIE/DYNAMO

DOE PAGES

Qian, Yun; Yan, Huiping; Berg, Larry K.; ...

2016-10-28

Accuracy of turbulence parameterization in representing Planetary Boundary Layer (PBL) processes in climate models is critical for predicting the initiation and development of clouds, air quality issues, and underlying surface-atmosphere-cloud interactions. In this study, we 1) evaluate WRF model-simulated spatial patterns of precipitation and surface fluxes, as well as vertical profiles of potential temperature, humidity, moist static energy and moisture tendency terms as simulated by WRF at various spatial resolutions and with PBL, surface layer and shallow convection schemes against measurements, 2) identify model biases by examining the moisture tendency terms contributed by PBL and convection processes through nudging experiments,more » and 3) evaluate the dependence of modeled surface latent heat (LH) fluxes onPBL and surface layer schemes over the tropical ocean. The results show that PBL and surface parameterizations have surprisingly large impacts on precipitation, convection initiation and surface moisture fluxes over tropical oceans. All of the parameterizations tested tend to overpredict moisture in PBL and free atmosphere, and consequently result in larger moist static energy and precipitation. Moisture nudging tends to suppress the initiation of convection and reduces the excess precipitation. The reduction in precipitation bias in turn reduces the surface wind and LH flux biases, which suggests that the model drifts at least partly because of a positive feedback between precipitation and surface fluxes. The updated shallow convection scheme KF-CuP tends to suppress the initiation and development of deep convection, consequently decreasing precipitation. The Eta surface layer scheme predicts more reasonable LH fluxes and the LH-Wind Speed relationship than the MM5 scheme, especially when coupled with the MYJ scheme. By examining various parameterization schemes in WRF, we identify sources of biases and weaknesses of current PBL, surface layer and shallow convection schemes in reproducing PBL processes, the initiation of convection and intra-seasonal variability of precipitation.« less

Predicting the severity of spurious “double ITCZ” problem in CMIP5 coupled models from AMIP simulations [Tropical versus extratropical origins of the spurious 'double ITCZ' in coupled climate models

DOE PAGES

Xiang, Baoqiang; Zhao, Ming; Held, Isaac M.; ...

2017-02-13

The severity of the double Intertropical Convergence Zone (DI) problem in climate models can be measured by a tropical precipitation asymmetry index (PAI), indicating whether tropical precipitation favors the Northern Hemisphere or the Southern Hemisphere. Examination of 19 Coupled Model Intercomparison Project phase 5 models reveals that the PAI is tightly linked to the tropical sea surface temperature (SST) bias. As one of the factors determining the SST bias, the asymmetry of tropical net surface heat flux in Atmospheric Model Intercomparison Project (AMIP) simulations is identified as a skillful predictor of the PAI change from an AMIP to a coupledmore » simulation, with an intermodel correlation of 0.90. Using tropical top-of-atmosphere (TOA) fluxes, the correlations are lower but still strong. However, the extratropical asymmetries of surface and TOA fluxes in AMIP simulations cannot serve as useful predictors of the PAI change. Furthermore, this study suggests that the largest source of the DI bias is from the tropics and from atmospheric models.« less

Downwelling Longwave Fluxes at Continental Surfaces-A Comparison of Observations with GCM Simulations and Implications for the Global Land-Surface Radiation Budget.

NASA Astrophysics Data System (ADS)

Garratt, J. R.; Prata, A. J.

1996-03-01

Previous work suggests that general circulation (global climate) models have excess net radiation at land surfaces, apparently due to overestimates in downwelling shortwave flux and underestimates in upwelling long-wave flux. Part of this excess, however, may be compensated for by an underestimate in downwelling longwave flux. Long term observations of the downwelling longwave component at several land stations in Europe, the United States, Australia, and Antarctica suggest that climate models (four are used, as in previous studies) underestimate this flux component on an annual basis by up to 10 W m2, yet with low statistical significance. It is probable that the known underestimate in boundary-layer air temperature contributes to this, as would low model cloudiness and neglect of minor gases such as methane, nitrogen oxide, and the freons. The bias in downwelling longwave flux, together with those found earlier for downwelling shortwave and upwlling long-wave fluxes, are consistent with the model bias found previously for net radiation. All annually averaged fluxes and biases are deduced for global land as a whole.

Select strengths and biases of models in representing the Arctic winter boundary layer over sea ice: the Larcform 1 single column model intercomparison

NASA Astrophysics Data System (ADS)

Pithan, Felix; Ackerman, Andrew; Angevine, Wayne M.; Hartung, Kerstin; Ickes, Luisa; Kelley, Maxwell; Medeiros, Brian; Sandu, Irina; Steeneveld, Gert-Jan; Sterk, H. A. M.; Svensson, Gunilla; Vaillancourt, Paul A.; Zadra, Ayrton

2016-09-01

Weather and climate models struggle to represent lower tropospheric temperature and moisture profiles and surface fluxes in Arctic winter, partly because they lack or misrepresent physical processes that are specific to high latitudes. Observations have revealed two preferred states of the Arctic winter boundary layer. In the cloudy state, cloud liquid water limits surface radiative cooling, and temperature inversions are weak and elevated. In the radiatively clear state, strong surface radiative cooling leads to the build-up of surface-based temperature inversions. Many large-scale models lack the cloudy state, and some substantially underestimate inversion strength in the clear state. Here, the transformation from a moist to a cold dry air mass is modeled using an idealized Lagrangian perspective. The trajectory includes both boundary layer states, and the single-column experiment is the first Lagrangian Arctic air formation experiment (Larcform 1) organized within GEWEX GASS (Global atmospheric system studies). The intercomparison reproduces the typical biases of large-scale models: some models lack the cloudy state of the boundary layer due to the representation of mixed-phase microphysics or to the interaction between micro- and macrophysics. In some models, high emissivities of ice clouds or the lack of an insulating snow layer prevent the build-up of surface-based inversions in the radiatively clear state. Models substantially disagree on the amount of cloud liquid water in the cloudy state and on turbulent heat fluxes under clear skies. Observations of air mass transformations including both boundary layer states would allow for a tighter constraint of model behavior.

Surface wave effects in the NEMO ocean model: Forced and coupled experiments

NASA Astrophysics Data System (ADS)

Breivik, Øyvind; Mogensen, Kristian; Bidlot, Jean-Raymond; Balmaseda, Magdalena Alonso; Janssen, Peter A. E. M.

2015-04-01

The NEMO general circulation ocean model is extended to incorporate three physical processes related to ocean surface waves, namely the surface stress (modified by growth and dissipation of the oceanic wavefield), the turbulent kinetic energy flux from breaking waves, and the Stokes-Coriolis force. Experiments are done with NEMO in ocean-only (forced) mode and coupled to the ECMWF atmospheric and wave models. Ocean-only integrations are forced with fields from the ERA-Interim reanalysis. All three effects are noticeable in the extratropics, but the sea-state-dependent turbulent kinetic energy flux yields by far the largest difference. This is partly because the control run has too vigorous deep mixing due to an empirical mixing term in NEMO. We investigate the relation between this ad hoc mixing and Langmuir turbulence and find that it is much more effective than the Langmuir parameterization used in NEMO. The biases in sea surface temperature as well as subsurface temperature are reduced, and the total ocean heat content exhibits a trend closer to that observed in a recent ocean reanalysis (ORAS4) when wave effects are included. Seasonal integrations of the coupled atmosphere-wave-ocean model consisting of NEMO, the wave model ECWAM, and the atmospheric model of ECMWF similarly show that the sea surface temperature biases are greatly reduced when the mixing is controlled by the sea state and properly weighted by the thickness of the uppermost level of the ocean model. These wave-related physical processes were recently implemented in the operational coupled ensemble forecast system of ECMWF.

Indian Ocean corals reveal crucial role of World War II bias for twentieth century warming estimates.

PubMed

Pfeiffer, M; Zinke, J; Dullo, W-C; Garbe-Schönberg, D; Latif, M; Weber, M E

2017-10-31

The western Indian Ocean has been warming faster than any other tropical ocean during the 20 th century, and is the largest contributor to the global mean sea surface temperature (SST) rise. However, the temporal pattern of Indian Ocean warming is poorly constrained and depends on the historical SST product. As all SST products are derived from the International Comprehensive Ocean-Atmosphere dataset (ICOADS), it is challenging to evaluate which product is superior. Here, we present a new, independent SST reconstruction from a set of Porites coral geochemical records from the western Indian Ocean. Our coral reconstruction shows that the World War II bias in the historical sea surface temperature record is the main reason for the differences between the SST products, and affects western Indian Ocean and global mean temperature trends. The 20 th century Indian Ocean warming pattern portrayed by the corals is consistent with the SST product from the Hadley Centre (HadSST3), and suggests that the latter should be used in climate studies that include Indian Ocean SSTs. Our data shows that multi-core coral temperature reconstructions help to evaluate the SST products. Proxy records can provide estimates of 20 th century SST that are truly independent from the ICOADS data base.

Surface morphological, electrical and transport properties of rapidly annealed double layers Ru/Cr Schottky structure on n-type InP

NASA Astrophysics Data System (ADS)

Shanthi Latha, K.; Rajagopal Reddy, V.

2017-07-01

The electrical and transport properties of a fabricated bilayer Ru/Cr/ n-InP Schottky diode (SD) have been investigated at different annealing temperatures. Atomic force microscopy results have showed that the overall surface morphology of the Ru/Cr/ n-InP SD is fairly smooth at elevated temperatures. High barrier height is achieved for the diode annealed at 300 °C compared to the as-deposited, annealed at 200 and 400 °C diodes. The series resistance and shunt resistance of the Ru/Cr/ n-InP SD are estimated by current-voltage method at different annealing temperatures. The barrier heights and series resistance are also determined by Cheung's and modified Norde functions. The interface state density of the Ru/Cr/ n-InP SD is found to be decreased after annealing at 300 °C and then slightly increased upon annealing at 400 °C. The difference between barrier heights obtained from current-voltage and capacitance-voltage is also discussed. Experimental results have showed that the Poole-Frenkel emission is found to be dominant in the lower bias region whereas Schottky emission is dominant in the higher bias region for the Ru/Cr/ n-InP SDs irrespective of annealing temperatures.

Simple physical-empirical model of the precipitation distribution based on a tropical sea surface temperature threshold and the effects of climate change

NASA Astrophysics Data System (ADS)

Jauregui, Yakelyn R.; Takahashi, Ken

2018-03-01

The observed nonlinear relationship between tropical sea surface temperature (T_s) and precipitation ( P) on climate timescales, by which a threshold (T_c) must be exceeded by T_s in order for deep convection to occur, is the basis of a physical-empirical model (PEM) that we fitted to observational data and CMIP5 climate model output and used to show that, with essentially only two constant parameters (T_c and the sensitivity a_1 of P to T_s>T_c), it provides a useful first-order description of the climatological and interannual variability of the large-scale distribution of tropical P given T_s, as well as of the biases of the Global Climate Models (GCMs). A substantial limitation is its underestimation of the peak P in the convergence zones, as the necessary processes associated with the atmospheric circulation are not considered. The pattern of the intermodel correlation between the mean T_s-T_c for each GCM and the average P distribution is in agreement with the double ITCZ bias, featuring roughly zonally-symmetric off-equatorial maxima, rather than being regionally or hemispherically restricted. The inter-comparison of GCMs indicates a relationship between T_c with the near-equatorial low-level (850 hPa) tropospheric temperature, consistent with the interpretation that it is a measure of the convective inhibition (CIN). The underestimation of T_c is linked to the cold free tropospheric bias in the GCMs. However, the discrepancy among the observational datasets is a limitation for assessing the GCM biases from the PEM framework quantitatively. Under the RCP4.5 climate change scenario, T_c increases slightly more than the mean tropical T_s, implying a stabilizing trend consistent with the amplified free tropospheric warming relative to the surface. However, since a_1 increases by 10-50%/°C with the surface warming, its effect dominates and results in generally positive precipitation change (Δ P) in the equatorial regions. In the equatorial eastern-central Pacific cold tongue, Δ (T_s-T_c) is positive, but the absolute T_s-T_c remains small, which explains the double band pattern of Δ P along the equatorial flanks of the spuriously strong double ITCZs. When the GCM biases are corrected in the PEM, the positive Δ P in the southeast Pacific and Atlantic oceans is substantially reduced.

Comparison of MODIS-derived land surface temperature with air temperature measurements

NASA Astrophysics Data System (ADS)

Georgiou, Andreas; Akçit, Nuhcan

2017-09-01

Air surface temperature is an important parameter for a wide range of applications such as agriculture, hydrology and climate change studies. Air temperature data is usually obtained from measurements made in meteorological stations, providing only limited information about spatial patterns over wide areas. The use of remote sensing data can help overcome this problem, particularly in areas with low station density, having the potential to improve the estimation of air surface temperature at both regional and global scales. Land Surface (skin) Temperatures (LST) derived from Moderate Resolution Imaging Spectroradiometer (MODIS) sensor aboard the Terra and Aqua satellite platforms provide spatial estimates of near-surface temperature values. In this study, LST values from MODIS are compared to groundbased near surface air (Tair) measurements obtained from 14 observational stations during 2011 to 2015, covering coastal, mountainous and urban areas over Cyprus. Combining Terra and Aqua LST-8 Day and Night acquisitions into a mean monthly value, provide a large number of LST observations and a better overall agreement with Tair. Comparison between mean monthly LSTs and mean monthly Tair for all sites and all seasons pooled together yields a very high correlation and biases. In addition, the presented high standard deviation can be explained by the influence of surface heterogeneity within MODIS 1km2 grid cells, the presence of undetected clouds and the inherent difference between LST and Tair. However, MODIS LST data proved to be a reliable proxy for surface temperature and mostly for studies requiring temperature reconstruction in areas with lack of observational stations.

Reversal of Thermoelectric Current in Tubular Nanowires

NASA Astrophysics Data System (ADS)

Erlingsson, Sigurdur I.; Manolescu, Andrei; Nemnes, George Alexandru; Bardarson, Jens H.; Sanchez, David

2017-07-01

We calculate the charge current generated by a temperature bias between the two ends of a tubular nanowire. We show that in the presence of a transversal magnetic field the current can change sign; i.e., electrons can either flow from the hot to the cold reservoir, or in the opposite direction, when the temperature bias increases. This behavior occurs when the magnetic field is sufficiently strong, such that Landau and snaking states are created, and the energy dispersion is nonmonotonic with respect to the longitudinal wave vector. The sign reversal can survive in the presence of impurities. We predict this result for core-shell nanowires, for uniform nanowires with surface states due to the Fermi level pinning, and for topological insulator nanowires.

The Impact of Parameterized Convection on Climatological Precipitation in Atmospheric Global Climate Models

NASA Astrophysics Data System (ADS)

Maher, Penelope; Vallis, Geoffrey K.; Sherwood, Steven C.; Webb, Mark J.; Sansom, Philip G.

2018-04-01

Convective parameterizations are widely believed to be essential for realistic simulations of the atmosphere. However, their deficiencies also result in model biases. The role of convection schemes in modern atmospheric models is examined using Selected Process On/Off Klima Intercomparison Experiment simulations without parameterized convection and forced with observed sea surface temperatures. Convection schemes are not required for reasonable climatological precipitation. However, they are essential for reasonable daily precipitation and constraining extreme daily precipitation that otherwise develops. Systematic effects on lapse rate and humidity are likewise modest compared with the intermodel spread. Without parameterized convection Kelvin waves are more realistic. An unexpectedly large moist Southern Hemisphere storm track bias is identified. This storm track bias persists without convection schemes, as does the double Intertropical Convergence Zone and excessive ocean precipitation biases. This suggests that model biases originate from processes other than convection or that convection schemes are missing key processes.

Evaluation of Historical and Projected Surface Air Temperature Simulations over China in CMIP5

NASA Astrophysics Data System (ADS)

Chen, L.; Frauenfeld, O. W.

2013-12-01

Projections of future temperature in China are crucial for assessments of climate change and implementation of appropriate adaptation and mitigation strategies. With the upcoming Intergovernmental Panel on Climate Change (IPCC) 5th Assessment Report (AR5), the fifth phase of the Coupled Model Intercomparison Project (CMIP5) was developed for assessing the latest state-of-the-art climate models and their projections. In this study, monthly surface air temperature from 20 CMIP5 models and four experiments (historical, RCP 2.6, RCP 4.5, and RCP 8.5) were used to investigate the temperature variability over China during the 20th century, and future changes for the 21st century. Two observational datasets (CRU TS 3.1 and the global terrestrial air temperature dataset from the University of Delaware) were adopted to evaluate the performance of the CMIP5 multimodel ensemble average, the performance of individual models, as well as the possible improvements in CMIP5 relative to CMIP3. Results show that both CMIP3 and CMIP5 have cold biases over most parts of China. CMIP5 displays a slightly better agreement with the observations than CMIP3, but substantial cold biases still exist over the Tibetan Plateau, especially in the cold season. These biases are also characterized by the greatest discrepancies among the individual models, indicating the models' limitations over this mountainous region. Both CMIP3 and CMIP5 show poor agreement with observed 20th-century temperature trends such that the spatial and seasonal patterns of the trends are not captured in the multimodel ensemble averages. Comparing individual models we find that MPI-ESM-LR, CanESM2, MIROC-ESM, and CCSM4 exhibit better skill than the other models in this part of the world. Projections of future temperature suggest that there will be a gradual increase in annual surface air temperature in China during the 21st century at a rate of 0.60°C/decade and 0.27°C/decade under the RCP 8.5 and RCP 4.5 scenarios, respectively. RCP 2.6 shows the slowest warming at a rate of 0.10°C/decade for the whole 21st century, but temperature will increase until 2040, and then remain stable or even decrease slightly. Based on the three emission scenarios, annual temperatures are projected to rise by 1.7-5.7°C by the end of the 21st century, and the greatest warming will occur over northern China and the Tibetan Plateau.

Contributions of the atmosphere-land and ocean-sea ice model components to the tropical Atlantic SST bias in CESM1

NASA Astrophysics Data System (ADS)

Song, Z.; Lee, S. K.; Wang, C.; Kirtman, B. P.; Qiao, F.

2016-02-01

In order to identify and quantify intrinsic errors in the atmosphere-land and ocean-sea ice model components of the Community Earth System Model version 1 (CESM1) and their contributions to the tropical Atlantic sea surface temperature (SST) bias in CESM1, we propose a new method of diagnosis and apply it to a set of CESM1 simulations. Our analyses of the model simulations indicate that both the atmosphere-land and ocean-sea ice model components of CESM1 contain large errors in the tropical Atlantic. When the two model components are fully coupled, the intrinsic errors in the two components emerge quickly within a year with strong seasonality in their growth rates. In particular, the ocean-sea ice model contributes significantly in forcing the eastern equatorial Atlantic warm SST bias in early boreal summer. Further analysis shows that the upper thermocline water underneath the eastern equatorial Atlantic surface mixed layer is too warm in a stand-alone ocean-sea ice simulation of CESM1 forced with observed surface flux fields, suggesting that the mixed layer cooling associated with the entrainment of upper thermocline water is too weak in early boreal summer. Therefore, although we acknowledge the potential importance of the westerly wind bias in the western equatorial Atlantic and the low-level stratus cloud bias in the southeastern tropical Atlantic, both of which originate from the atmosphere-land model, we emphasize here that solving those problems in the atmosphere-land model alone does not resolve the equatorial Atlantic warm bias in CESM1.

Novel Methods to Explore Building Energy Sensitivity to Climate and Heat Waves Using PNNL's BEND Model

NASA Astrophysics Data System (ADS)

Burleyson, C. D.; Voisin, N.; Taylor, T.; Xie, Y.; Kraucunas, I.

2017-12-01

The DOE's Pacific Northwest National Laboratory (PNNL) has been developing the Building ENergy Demand (BEND) model to simulate energy usage in residential and commercial buildings responding to changes in weather, climate, population, and building technologies. At its core, BEND is a mechanism to aggregate EnergyPlus simulations of a large number of individual buildings with a diversity of characteristics over large spatial scales. We have completed a series of experiments to explore methods to calibrate the BEND model, measure its ability to capture interannual variability in energy demand due to weather using simulations of two distinct weather years, and understand the sensitivity to the number and location of weather stations used to force the model. The use of weather from "representative cities" reduces computational costs, but often fails to capture spatial heterogeneity that may be important for simulations aimed at understanding how building stocks respond to a changing climate (Fig. 1). We quantify the potential reduction in temperature and load biases from using an increasing number of weather stations across the western U.S., ranging from 8 to roughly 150. Using 8 stations results in an average absolute summertime temperature bias of 4.0°C. The mean absolute bias drops to 1.5°C using all available stations. Temperature biases of this magnitude translate to absolute summertime mean simulated load biases as high as 13.8%. Additionally, using only 8 representative weather stations can lead to a 20-40% bias of peak building loads under heat wave or cold snap conditions, a significant error for capacity expansion planners who may rely on these types of simulations. This analysis suggests that using 4 stations per climate zone may be sufficient for most purposes. Our novel approach, which requires no new EnergyPlus simulations, could be useful to other researchers designing or calibrating aggregate building model simulations - particularly those looking at the impact of future climate scenarios. Fig. 1. An example of temperature bias that results from using 8 representative weather stations: (a) surface temperature from NLDAS on 5-July 2008 at 2000 UTC; (b) temperature from 8 representative stations at the same time mapped to all counties within a given IECC climate zone; (c) the difference between (a) and (b).

Probabilistic precipitation and temperature downscaling of the Twentieth Century Reanalysis over France

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

Caillouet, Laurie; Vidal, Jean -Philippe; Sauquet, Eric

This work proposes a daily high-resolution probabilistic reconstruction of precipitation and temperature fields in France over the 1871–2012 period built on the NOAA Twentieth Century global extended atmospheric reanalysis (20CR). The objective is to fill in the spatial and temporal data gaps in surface observations in order to improve our knowledge on the local-scale climate variability from the late nineteenth century onwards. The SANDHY (Stepwise ANalogue Downscaling method for HYdrology) statistical downscaling method, initially developed for quantitative precipitation forecast, is used here to bridge the scale gap between large-scale 20CR predictors and local-scale predictands from the Safran high-resolution near-surface reanalysis,more » available from 1958 onwards only. SANDHY provides a daily ensemble of 125 analogue dates over the 1871–2012 period for 608 climatically homogeneous zones paving France. Large precipitation biases in intermediary seasons are shown to occur in regions with high seasonal asymmetry like the Mediterranean. Moreover, winter and summer temperatures are respectively over- and under-estimated over the whole of France. Two analogue subselection methods are therefore developed with the aim of keeping the structure of the SANDHY method unchanged while reducing those seasonal biases. The calendar selection keeps the analogues closest to the target calendar day. The stepwise selection applies two new analogy steps based on similarity of the sea surface temperature (SST) and the large-scale 2 m temperature ( T). Comparisons to the Safran reanalysis over 1959–2007 and to homogenized series over the whole twentieth century show that biases in the interannual cycle of precipitation and temperature are reduced with both methods. The stepwise subselection moreover leads to a large improvement of interannual correlation and reduction of errors in seasonal temperature time series. When the calendar subselection is an easily applicable method suitable in a quantitative precipitation forecast context, the stepwise subselection method allows for potential season shifts and SST trends and is therefore better suited for climate reconstructions and climate change studies. Furthermore, the probabilistic downscaling of 20CR over the period 1871–2012 with the SANDHY probabilistic downscaling method combined with the stepwise subselection thus constitutes a perfect framework for assessing the recent observed meteorological events but also future events projected by climate change impact studies and putting them in a historical perspective.« less

Probabilistic precipitation and temperature downscaling of the Twentieth Century Reanalysis over France

DOE PAGES

Caillouet, Laurie; Vidal, Jean -Philippe; Sauquet, Eric; ...

2016-03-16

This work proposes a daily high-resolution probabilistic reconstruction of precipitation and temperature fields in France over the 1871–2012 period built on the NOAA Twentieth Century global extended atmospheric reanalysis (20CR). The objective is to fill in the spatial and temporal data gaps in surface observations in order to improve our knowledge on the local-scale climate variability from the late nineteenth century onwards. The SANDHY (Stepwise ANalogue Downscaling method for HYdrology) statistical downscaling method, initially developed for quantitative precipitation forecast, is used here to bridge the scale gap between large-scale 20CR predictors and local-scale predictands from the Safran high-resolution near-surface reanalysis,more » available from 1958 onwards only. SANDHY provides a daily ensemble of 125 analogue dates over the 1871–2012 period for 608 climatically homogeneous zones paving France. Large precipitation biases in intermediary seasons are shown to occur in regions with high seasonal asymmetry like the Mediterranean. Moreover, winter and summer temperatures are respectively over- and under-estimated over the whole of France. Two analogue subselection methods are therefore developed with the aim of keeping the structure of the SANDHY method unchanged while reducing those seasonal biases. The calendar selection keeps the analogues closest to the target calendar day. The stepwise selection applies two new analogy steps based on similarity of the sea surface temperature (SST) and the large-scale 2 m temperature ( T). Comparisons to the Safran reanalysis over 1959–2007 and to homogenized series over the whole twentieth century show that biases in the interannual cycle of precipitation and temperature are reduced with both methods. The stepwise subselection moreover leads to a large improvement of interannual correlation and reduction of errors in seasonal temperature time series. When the calendar subselection is an easily applicable method suitable in a quantitative precipitation forecast context, the stepwise subselection method allows for potential season shifts and SST trends and is therefore better suited for climate reconstructions and climate change studies. Furthermore, the probabilistic downscaling of 20CR over the period 1871–2012 with the SANDHY probabilistic downscaling method combined with the stepwise subselection thus constitutes a perfect framework for assessing the recent observed meteorological events but also future events projected by climate change impact studies and putting them in a historical perspective.« less

Sea Ice Surface Temperature Product from the Moderate Resolution Imaging Spectroradiometer (MODIS)

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Key, Jeffrey R.; Casey, Kimberly A.; Riggs, George A.; Cavalieri, Donald J.

2003-01-01

Global sea ice products are produced from the Earth Observing System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS) on board both the Terra and Aqua satellites. Daily sea ice extent and ice-surface temperature (IST) products are available at 1- and 4-km resolution. Validation activities have been undertaken to assess the accuracy of the MODIS IST product at the South Pole station in Antarctica and in the Arctic Ocean using near-surface air-temperature data from a meteorological station and drifting buoys. Results from the study areas show that under clear skies, the MODIS ISTs are very close to those of the near-surface air temperatures with a bias of -1.1 and -1.2 K, and an uncertainty of 1.6 and 1.7 K, respectively. It is shown that the uncertainties would be reduced if the actual temperature of the ice surface were reported instead of the near-surface air temperature. It is not possible to get an accurate IST from MODIS in the presence of even very thin clouds or fog, however using both the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) and the MODIS on the Aqua satellite, it may be possible to develop a relationship between MODIS-derived IST and ice temperature derived from the AMSR-E. Since the AMSR-E measurements are generally unaffected by cloud cover, they may be used to complement the MODIS IST measurements.

The role of land surface fluxes in Saudi-KAU AGCM: Temperature climatology over the Arabian Peninsula for the period 1981-2010

NASA Astrophysics Data System (ADS)

Ashfaqur Rahman, M.; Almazroui, Mansour; Nazrul Islam, M.; O'Brien, Enda; Yousef, Ahmed Elsayed

2018-02-01

A new version of the Community Land Model (CLM) was introduced to the Saudi King Abdulaziz University Atmospheric Global Climate Model (Saudi-KAU AGCM) for better land surface component representation, and so to enhance climate simulation. CLM replaced the original land surface model (LSM) in Saudi-KAU AGCM, with the aim of simulating more accurate land surface fluxes globally, but especially over the Arabian Peninsula. To evaluate the performance of Saudi-KAU AGCM, simulations were completed with CLM and LSM for the period 1981-2010. In comparison with LSM, CLM generates surface air temperature values that are closer to National Centre for Environmental Prediction (NCEP) observations. The global annual averages of land surface air temperature are 9.51, 9.52, and 9.57 °C for NCEP, CLM, and LSM respectively, although the same atmospheric radiative and surface forcing from Saudi-KAU AGCM are provided to both LSM and CLM at every time step. The better temperature simulations when using CLM can be attributed to the more comprehensive plant functional type and hierarchical tile approach to the land cover type in CLM, along with better parameterization of upward land surface fluxes compared to LSM. At global scale, CLM exhibits smaller annual and seasonal mean biases of temperature with respect to NCEP data. Moreover, at regional scale, CLM demonstrates reasonable seasonal and annual mean temperature over the Arabian Peninsula as compared to the Climatic Research Unit (CRU) data. Finally, CLM generated better matches to single point-wise observations of surface air temperature and surface fluxes for some case studies.

Optimization of a Radiative Transfer Forward Operator for Simulating SMOS Brightness Temperatures over the Upper Mississippi Basin, USA

NASA Technical Reports Server (NTRS)

Lievens, H.; Verhoest, N. E. C.; Martens, B.; VanDenBerg, M. J.; Bitar, A. Al; Tomer, S. Kumar; Merlin, O.; Cabot, F.; Kerr, Y.; DeLannoy, G. J. M.;

Low-temperature scanning tunneling microscopy of ring-like surface electronic structures around Co islands on InAs(110) surfaces.

PubMed

Muzychenko, D A; Schouteden, K; Savinov, S V; Maslova, N S; Panov, V I; Van Haesendonck, C

2009-08-01

We report on the experimental observation by scanning tunneling microscopy at low temperature of ring-like features that appear around Co metal islands deposited on a clean (110) oriented surface of cleaved p-type InAs crystals. These features are visible in spectroscopic images within a certain range of negative tunneling bias voltages due to the presence of a negative differential conductance in the current-voltage dependence. A theoretical model is introduced, which takes into account non-equilibrium effects in the small tunneling junction area. In the framework of this model the appearance of the ring-like features is explained in terms of interference effects between electrons tunneling directly and indirectly (via a Co island) between the tip and the InAs surface.

Improvement of the positive bias stability of a-IGZO TFTs by the HCN treatment

NASA Astrophysics Data System (ADS)

Kim, Myeong-Ho; Choi, Myung-Jea; Kimura, Katsuya; Kobayashi, Hikaru; Choi, Duck-Kyun

2016-12-01

In recent years, many researchers have attempted to improve the bias stability of amorphous indium gallium zinc oxide (a-IGZO) thin-film transistors (TFTs). In this study, the hydrogen cyanide (HCN) treatment was carried out to improve the positive bias stability of bottom-gate a-IGZO TFTs. The HCN treatment was performed using a 0.1 M HCN solution with a pH of 10 at room temperature. Before applying the positive bias stress, there were no differences in the major electrical properties, including the saturation mobility (μsat), threshold voltage (Vth), and subthreshold swing (S/S), between HCN-treated and non-HCN-treated devices. However, after applying the positive bias stress, the HCN-treated device showed superior bias stability compared to the non-HCN-treated device. This difference is associated with the passivation of the defect states and the surface of the back-channel layer of the HCN-treated device by cyanide ions.

Improving Satellite Retrieved Infrared Sea Surface Temperatures in Aerosol-Contaminated Regions

NASA Astrophysics Data System (ADS)

Luo, B.; Minnett, P. J.; Szczodrak, G.; Kilpatrick, K. A.

2017-12-01

Infrared satellite observations of sea surface temperature (SST) have become essential for many applications in meteorology, climatology, and oceanography. Applications often require high accuracy SST data: for climate research and monitoring an absolute uncertainty of 0.1K and stability of better than 0.04K per decade are required. Tropospheric aerosol concentrations increase infrared signal attenuation and prevent the retrieval of accurate satellite SST. We compare satellite-derived skin SST with measurements from the Marine-Atmospheric Emitted Radiance Interferometer (M-AERI) deployed on ships during the Aerosols and Ocean Science Expeditions (AEROSE) and with quality-controlled drifter temperatures. After match-up with in-situ SST and filtering of cloud contaminated data, the results indicate that SST retrieved from MODIS (Moderate Resolution Imaging Spectroradiometer) aboard the Terra and Aqua satellites have negative (cool) biases compared to shipboard radiometric measurements. There is also a pronounced negative bias in the Saharan outflow area that can introduce SST errors >1 K at aerosol optical depths > 0.5. In this study, we present a new method to derive night-time Saharan Dust Index (SDI) algorithms based on simulated brightness temperatures at infrared wavelengths of 3.9, 10.8 and 12.0 μm, derived using RTTOV. We derived correction coefficients for Aqua MODIS measurements by regression of the SST errors against the SDI. The biases and standard deviations are reduced by 0.25K and 0.19K after the SDI correction. The goal of this study is to understand better the characteristics and physical mechanisms of aerosol effects on satellite retrieved infrared SST, as well as to derive empirical formulae for improved accuracies in aerosol-contaminated regions.

Recent land cover changes and sensitivity of the model simulations to various land cover datasets for China

NASA Astrophysics Data System (ADS)

Chen, Liang; Ma, Zhuguo; Mahmood, Rezaul; Zhao, Tianbao; Li, Zhenhua; Li, Yanping

2017-08-01

Reliable land cover data are important for improving numerical simulation by regional climate model, because the land surface properties directly affect climate simulation by partitioning of energy, water and momentum fluxes and by determining temperature and moisture at the interface between the land surface and atmosphere. China has experienced significant land cover change in recent decades and accurate representation of these changes is, hence, essential. In this study, we used a climate model to examine the changes experienced in the regional climate because of the different land cover data in recent decades. Three sets of experiments are performed using the same settings, except for the land use/cover (LC) data for the years 1990, 2000, 2009, and the model default LC data. Three warm season periods are selected, which represented a wet (1998), normal (2000) and a dry year (2011) for China in each set of experiment. The results show that all three sets of land cover experiments simulate a warm bias relative to the control with default LC data for near-surface temperature in summertime in most parts of China. It is especially noticeable in the southwest China and south of the Yangtze River, where significant changes of LC occurred. Deforestation in southwest China and to the south of Yangtze River in the experiment cases may have contributed to the negative precipitation bias relative to the control cases. Large LC changes in northwestern Tibetan Plateau for 2000 and 2009 datasets are also associated with changes in surface temperature, precipitation, and heat fluxes. Wind anomalies and energy budget changes are consistent with the precipitation and temperature changes.

Modelling temporal variance of component temperatures and directional anisotropy over vegetated canopy

NASA Astrophysics Data System (ADS)

Bian, Zunjian; du, yongming; li, hua

2016-04-01

Land surface temperature (LST) as a key variable plays an important role on hydrological, meteorology and climatological study. Thermal infrared directional anisotropy is one of essential factors to LST retrieval and application on longwave radiance estimation. Many approaches have been proposed to estimate directional brightness temperatures (DBT) over natural and urban surfaces. While less efforts focus on 3-D scene and the surface component temperatures used in DBT models are quiet difficult to acquire. Therefor a combined 3-D model of TRGM (Thermal-region Radiosity-Graphics combined Model) and energy balance method is proposed in the paper for the attempt of synchronously simulation of component temperatures and DBT in the row planted canopy. The surface thermodynamic equilibrium can be final determined by the iteration strategy of TRGM and energy balance method. The combined model was validated by the top-of-canopy DBTs using airborne observations. The results indicated that the proposed model performs well on the simulation of directional anisotropy, especially the hotspot effect. Though we find that the model overestimate the DBT with Bias of 1.2K, it can be an option as a data reference to study temporal variance of component temperatures and DBTs when field measurement is inaccessible

Response of water temperature to surface wave effects in the Baltic Sea: simulations with the coupled NEMO-WAM model

NASA Astrophysics Data System (ADS)

Alari, Victor; Staneva, Joanna; Breivik, Øyvind; Bidlot, Jean-Raymond; Mogensen, Kristian; Janssen, Peter

2016-04-01

The effects of wind waves on the Baltic Sea water temperature has been studied by coupling the hydrodynamical model NEMO with the wave model WAM. The wave forcing terms that have been taken into consideration are: Stokes-Coriolis force, seastate dependent energy flux and sea-state dependent momentum flux. The combined role of these processes as well as their individual contributions on simulated temperature is analysed. The results indicate a pronounced effect of waves on surface temperature, on the distribution of vertical temperature and on upwellinǵs. In northern parts of the Baltic Sea a warming of the surface layer occurs in the wave included simulations. This in turn reduces the cold bias between simulated and measured data. The warming is primarily caused by sea-state dependent energy flux. Wave induced cooling is mostly observed in near coastal areas and is mainly due to Stokes-Coriolis forcing. The latter triggers effect of intensifying upwellings near the coasts, depending on the direction of the wind. The effect of sea-state dependent momentum flux is predominantly to warm the surface layer. During the summer the wave induced water temperature changes were up to 1 °C.

Temperature distribution in an aircraft tire at low ground speeds

NASA Technical Reports Server (NTRS)

Mccarty, J. L.; Tanner, J. A.

1983-01-01

An experimental study was conducted to define temperature profiles of 22 x 5.5, type 7, bias ply aircraft tires subjected to freely rolling, yawed rolling, and light braking conditions. Temperatures along the inner wall of freely rolling tires were greater than those near the outer surface. The effect of increasing tire deflection was to increase the temperature within the shoulder and sidewall areas of the tire carcass. The effect of cornering and braking was to increase the treat temperature. For taxi operations at fixed yaw angles, temperature profiles were not symmetric. Increasing the ground speed produced only moderate increases in tread temperature, whereas temperatures in the carcass shoulder and sidewall were essentially unaffected.

Impact of bias-corrected reanalysis-derived lateral boundary conditions on WRF simulations

NASA Astrophysics Data System (ADS)

Moalafhi, Ditiro Benson; Sharma, Ashish; Evans, Jason Peter; Mehrotra, Rajeshwar; Rocheta, Eytan

2017-08-01

Lateral and lower boundary conditions derived from a suitable global reanalysis data set form the basis for deriving a dynamically consistent finer resolution downscaled product for climate and hydrological assessment studies. A problem with this, however, is that systematic biases have been noted to be present in the global reanalysis data sets that form these boundaries, biases which can be carried into the downscaled simulations thereby reducing their accuracy or efficacy. In this work, three Weather Research and Forecasting (WRF) model downscaling experiments are undertaken to investigate the impact of bias correcting European Centre for Medium range Weather Forecasting Reanalysis ERA-Interim (ERA-I) atmospheric temperature and relative humidity using Atmospheric Infrared Sounder (AIRS) satellite data. The downscaling is performed over a domain centered over southern Africa between the years 2003 and 2012. The sample mean and the mean as well as standard deviation at each grid cell for each variable are used for bias correction. The resultant WRF simulations of near-surface temperature and precipitation are evaluated seasonally and annually against global gridded observational data sets and compared with ERA-I reanalysis driving field. The study reveals inconsistencies between the impact of the bias correction prior to downscaling and the resultant model simulations after downscaling. Mean and standard deviation bias-corrected WRF simulations are, however, found to be marginally better than mean only bias-corrected WRF simulations and raw ERA-I reanalysis-driven WRF simulations. Performances, however, differ when assessing different attributes in the downscaled field. This raises questions about the efficacy of the correction procedures adopted.

Detecting drift bias and exposure errors in solar and photosynthetically active radiation data

USDA-ARS?s Scientific Manuscript database

All-black thermopile pyranometers are commonly used to measure solar radiation. Ensuring that the sensors are stable and free of drift is critical to accurately measure small variations in global solar irradiance (K'), which is a potential driver of changes in surface temperature. We demonstrate tha...

Body temperature measurement in mice during acute illness: implantable temperature transponder versus surface infrared thermometry.

PubMed

Mei, Jie; Riedel, Nico; Grittner, Ulrike; Endres, Matthias; Banneke, Stefanie; Emmrich, Julius Valentin

2018-02-23

Body temperature is a valuable parameter in determining the wellbeing of laboratory animals. However, using body temperature to refine humane endpoints during acute illness generally lacks comprehensiveness and exposes to inter-observer bias. Here we compared two methods to assess body temperature in mice, namely implanted radio frequency identification (RFID) temperature transponders (method 1) to non-contact infrared thermometry (method 2) in 435 mice for up to 7 days during normothermia and lipopolysaccharide (LPS) endotoxin-induced hypothermia. There was excellent agreement between core and surface temperature as determined by method 1 and 2, respectively, whereas the intra- and inter-subject variation was higher for method 2. Nevertheless, using machine learning algorithms to determine temperature-based endpoints both methods had excellent accuracy in predicting death as an outcome event. Therefore, less expensive and cumbersome non-contact infrared thermometry can serve as a reliable alternative for implantable transponder-based systems for hypothermic responses, although requiring standardization between experimenters.

Biasing experiments on the Advanced Toroidal Facility

NASA Astrophysics Data System (ADS)

Uckan, T.; Isler, R. C.; Jernigan, T. C.; Lyon, J. F.; Mioduszewski, P. K.; Murakami, M.; Rasmussen, D. A.; Wilgen, J. B.; Aceto, S. C.; Zielinski, J. J.

1992-09-01

Biasing experiments have been carried out in 1 T plasmas with approximately 200 kW of electron cyclotron heating (ECH) in the current-fire Advanced Toroidal Facility (ATF) torsatron. Two rail limiters, one at the top and one at the bottom of the device, located at the last closed flux surface (LCFS), are, biased at positive and negative potentials with respect to the vacuum vessel. When the limiters are positively biased at up to 300 V and the plasma density is controlled with a significantly reduced gas feed, the H(sub alpha) radiation from both the limiter and the wall drops, indicating reduced particle recycling as a result of improved particle confinement. For bias voltages around +100 V, there is almost no change of plasma stored energy W(sub p), but W(sub p) then drops with the higher biasing voltages. Positive biasing has caused the core plasma density profile to become peaked and the electric field to become more negative inside the LCFS. At the same time, edge plasma fluctuations are reduced significantly and their power spectrum becomes less broad. The propagation direction of these electrostatic fluctuations reverses to the ion diamagnetic direction, and their wavelengths become longer. The resulting fluctuation-induced particle flux is also reduced. Power deposition on the limiters is lower as a result of reduced edge plasma density and temperature. Negative biasing yields somewhat less improvement in the particle confinement while having almost no apparent effect on W(sub p) or on the core and the edge plasma density and temperature profiles. Simultaneous measurements of the plasma potential profile indicate almost no significant change. Biasing has almost no effect on the intrinsic impurity levels in the plasma.

Spatiotemporal Evaluation of Reanalysis and In-situ Surface Air Temperature over Ethiopia

NASA Astrophysics Data System (ADS)

Tesfaye, T.

2017-12-01

Tewodros Woldemariam Tesfaye*1, C.T. Dhanya 2,and A.K. Gosain3 1Research Scholar, Department of Civil Engineering, Indian Institute of Technology Delhi, New Delhi-110016, India 2Assistant Professor, Department of Civil Engineering, Indian Institute of Technology Delhi, New Delhi-110016, India 3 Professor, Department of Civil Engineering, Indian Institute of Technology Delhi, New Delhi-110016, India, *e-mail: tewodros2002@gmail.com Abstract: Water resources management and modelling studies are often constrained by the scarcity of observed data, especially of the two major variables i.e., precipitation and temperature. Modellers, hence, rely on reanalysis datasets as a substitute; though its performance heavily vary depending on the data availability and regional characteristics. The present study aims at examining the ability of frequently used reanalysis datasets in capturing the spatiotemporal characteristics of maximum and minimum surface temperatures over Ethiopia and to highlight the biases, if any, in these over Ethiopian region. We considered ERA-Interim, NCEP 2, MERRA and CFSR reanalysis datasets and compared these with temperature observations from 15 synoptic stations spread over Ethiopia. In addition to the long term averages and annual cycle, a critical comparison of various extreme indices such as diurnal temperature range, warm days, warm nights, cool days, cool nights, summer days and tropical nights are also undertaken. Our results indicate that, the performance of CFSR followed by NCEP 2 is better in capturing majority of the aspects. ERA-Interim suffers a huge additive bias in the simulation of various aspects of minimum temperature in all the stations considered; while its performance is better for maximum temperature. The inferior performance of ERA-Interim is noted to be only because of the difficulty in simulating minimum temperature. Key words: ERA Interim; NCEP Reanalysis; MERRA; CFSR; Diurnal temperature range; reanalysis performance.

LS3MIP (v1.0) Contribution to CMIP6: The Land Surface, Snow and Soil Moisture Model Intercomparison Project Aims, Setup and Expected Outcome.

NASA Technical Reports Server (NTRS)

Van Den Hurk, Bart; Kim, Hyungjun; Krinner, Gerhard; Seneviratne, Sonia I.; Derksen, Chris; Oki, Taikan; Douville, Herve; Colin, Jeanne; Ducharne, Agnes; Cheruy, Frederique;

LS3MIP (v1.0) contribution to CMIP6: the Land Surface, Snow and Soilmoisture Model Intercomparison Project – aims, setup and expected outcome

DOE PAGES

van den Hurk, Bart; Kim, Hyungjun; Krinner, Gerhard; ...

2016-08-24

The Land Surface, Snow and Soil Moisture Model Intercomparison Project (LS3MIP) is designed to provide a comprehensive assessment of land surface, snow and soil moisture feedbacks on climate variability and climate change, and to diagnose systematic biases in the land modules of current Earth system models (ESMs). Furthermore, the solid and liquid water stored at the land surface has a large influence on the regional climate, its variability and predictability, including effects on the energy, water and carbon cycles. Notably, snow and soil moisture affect surface radiation and flux partitioning properties, moisture storage and land surface memory. They both stronglymore » affect atmospheric conditions, in particular surface air temperature and precipitation, but also large-scale circulation patterns. But, models show divergent responses and representations of these feedbacks as well as systematic biases in the underlying processes. LS3MIP will provide the means to quantify the associated uncertainties and better constrain climate change projections, which is of particular interest for highly vulnerable regions (densely populated areas, agricultural regions, the Arctic, semi-arid and other sensitive terrestrial ecosystems). The experiments are subdivided in two components, the first addressing systematic land biases in offline mode (“LMIP”, building upon the 3rd phase of Global Soil Wetness Project; GSWP3) and the second addressing land feedbacks attributed to soil moisture and snow in an integrated framework (“LFMIP”, building upon the GLACE-CMIP blueprint).« less

LS3MIP (v1.0) contribution to CMIP6: the Land Surface, Snow and Soilmoisture Model Intercomparison Project – aims, setup and expected outcome

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

van den Hurk, Bart; Kim, Hyungjun; Krinner, Gerhard

The Land Surface, Snow and Soil Moisture Model Intercomparison Project (LS3MIP) is designed to provide a comprehensive assessment of land surface, snow and soil moisture feedbacks on climate variability and climate change, and to diagnose systematic biases in the land modules of current Earth system models (ESMs). Furthermore, the solid and liquid water stored at the land surface has a large influence on the regional climate, its variability and predictability, including effects on the energy, water and carbon cycles. Notably, snow and soil moisture affect surface radiation and flux partitioning properties, moisture storage and land surface memory. They both stronglymore » affect atmospheric conditions, in particular surface air temperature and precipitation, but also large-scale circulation patterns. But, models show divergent responses and representations of these feedbacks as well as systematic biases in the underlying processes. LS3MIP will provide the means to quantify the associated uncertainties and better constrain climate change projections, which is of particular interest for highly vulnerable regions (densely populated areas, agricultural regions, the Arctic, semi-arid and other sensitive terrestrial ecosystems). The experiments are subdivided in two components, the first addressing systematic land biases in offline mode (“LMIP”, building upon the 3rd phase of Global Soil Wetness Project; GSWP3) and the second addressing land feedbacks attributed to soil moisture and snow in an integrated framework (“LFMIP”, building upon the GLACE-CMIP blueprint).« less

Importance of Preserving Cross-correlation in developing Statistically Downscaled Climate Forcings and in estimating Land-surface Fluxes and States

NASA Astrophysics Data System (ADS)

Das Bhowmik, R.; Arumugam, S.

2015-12-01

Multivariate downscaling techniques exhibited superiority over univariate regression schemes in terms of preserving cross-correlations between multiple variables- precipitation and temperature - from GCMs. This study focuses on two aspects: (a) develop an analytical solutions on estimating biases in cross-correlations from univariate downscaling approaches and (b) quantify the uncertainty in land-surface states and fluxes due to biases in cross-correlations in downscaled climate forcings. Both these aspects are evaluated using climate forcings available from both historical climate simulations and CMIP5 hindcasts over the entire US. The analytical solution basically relates the univariate regression parameters, co-efficient of determination of regression and the co-variance ratio between GCM and downscaled values. The analytical solutions are compared with the downscaled univariate forcings by choosing the desired p-value (Type-1 error) in preserving the observed cross-correlation. . For quantifying the impacts of biases on cross-correlation on estimating streamflow and groundwater, we corrupt the downscaled climate forcings with different cross-correlation structure.

An evaluation of a zero-heat-flux cutaneous thermometer in cardiac surgical patients.

PubMed

Eshraghi, Yashar; Nasr, Vivian; Parra-Sanchez, Ivan; Van Duren, Albert; Botham, Mark; Santoscoy, Thomas; Sessler, Daniel I

2014-09-01

Although core temperature can be measured invasively, there are currently no widely available, reliable, noninvasive thermometers for its measurement. We thus compared a prototype zero-heat-flux thermometer with simultaneous measurements from a pulmonary artery catheter. Specifically, we tested the hypothesis that zero-heat-flux temperatures are sufficiently accurate for routine clinical use. Core temperature was measured from the thermistor of a standard pulmonary artery catheter and with a prototype zero-heat-flux deep-tissue thermometer in 105 patients having nonemergent cardiac surgery. Zero-heat-flux probes were positioned on the lateral forehead and lateral neck. Skin surface temperature probes were attached to the forehead just adjacent to the zero-heat-flux probe. Temperatures were recorded at 1-minute intervals, excluding the period of cardiopulmonary bypass, and for the first 4 postoperative hours. Zero-heat-flux and pulmonary artery temperatures were compared with bias analysis; differences exceeding 0.5°C were considered to be potentially clinically important. The mean duration in the operating room was 279 ± 75 minutes, and the mean cross-clamp time was 118 ± 50 minutes. All subjects were monitored for an additional 4 hours in the intensive care unit. The average overall difference between forehead zero-heat-flux and pulmonary artery temperatures (i.e., forehead minus pulmonary artery) was -0.23°C (95% limits of agreement of ±0.82); 78% of the differences were ≤0.5°C. The average intraoperative temperature difference was -0.08°C (95% limits of agreement of ±0.88); 84% of the differences were ≤0.5°C. The average postoperative difference was -0.32°C (95% limits of agreement of ±0.75); 84% of the differences were ≤0.5°C. Bias and precision values for neck site were similar to the forehead values. Uncorrected forehead skin temperature showed an increasing negative bias as core temperature decreased. Core temperature can be noninvasively measured using the zero-heat-flux method. Bias was small, but precision was slightly worse than our designated 0.5°C limits compared with measurements from a pulmonary artery catheter.

Monolithic prestressed ceramic devices and method for making same

NASA Technical Reports Server (NTRS)

Haertling, Gene H. (Inventor)

1996-01-01

Monolithic, internally asymmetrically stress biased electrically active ceramic devices and a method for making same is disclosed. The first step in the method of the present invention is to fabricate a ceramic element having first and second opposing surfaces. Next, only the first surface is chemically reduced by heat treatment in a reducing atmosphere. This produces a concave shaped, internally asymmetrically stress biased ceramic element and an electrically conducting, chemically reduced layer on the first surface which serves as one of the electrodes of the device. Another electrode can be deposited on the second surface to complete the device. In another embodiment of the present invention two dome shaped ceramic devices can be placed together to form a completed clamshell structure or an accordion type structure. In a further embodiment, the clamshell or accordion type structures can be placed on top of one another. In another embodiment, a pair of dome shaped ceramic devices having opposing temperature characteristics can be placed on top of each other to produce an athermalized ceramic device.

Select strengths and biases of models in representing the Arctic winter boundary layer over sea ice: the Larcform 1 single column model intercomparison

DOE PAGES

Pithan, Felix; Ackerman, Andrew; Angevine, Wayne M.; ...

2016-08-27

We struggle to represent lower tropospheric temperature and moisture profiles and surface fluxes in Artic winter using weather and climate models, partly because they lack or misrepresent physical processes that are specific to high latitudes. Observations have revealed two preferred states of the Arctic winter boundary layer. In the cloudy state, cloud liquid water limits surface radiative cooling, and temperature inversions are weak and elevated. In the radiatively clear state, strong surface radiative cooling leads to the build-up of surface-based temperature inversions. Many large-scale models lack the cloudy state, and some substantially underestimate inversion strength in the clear state. Themore » transformation from a moist to a cold dry air mass is modeled using an idealized Lagrangian perspective. The trajectory includes both boundary layer states, and the single-column experiment is the first Lagrangian Arctic air formation experiment (Larcform 1) organized within GEWEX GASS (Global atmospheric system studies). The intercomparison reproduces the typical biases of large-scale models: some models lack the cloudy state of the boundary layer due to the representation of mixed-phase microphysics or to the interaction between micro- and macrophysics. In some models, high emissivities of ice clouds or the lack of an insulating snow layer prevent the build-up of surface-based inversions in the radiatively clear state. Models substantially disagree on the amount of cloud liquid water in the cloudy state and on turbulent heat fluxes under clear skies. Finally, observations of air mass transformations including both boundary layer states would allow for a tighter constraint of model behavior.« less

Select strengths and biases of models in representing the Arctic winter boundary layer over sea ice: the Larcform 1 single column model intercomparison

PubMed Central

Pithan, Felix; Ackerman, Andrew; Angevine, Wayne M.; Hartung, Kerstin; Ickes, Luisa; Kelley, Maxwell; Medeiros, Brian; Sandu, Irina; Steeneveld, Gert-Jan; Sterk, HAM; Svensson, Gunilla; Vaillancourt, Paul A.; Zadra, Ayrton

2017-01-01

Weather and climate models struggle to represent lower tropospheric temperature and moisture profiles and surface fluxes in Arctic winter, partly because they lack or misrepresent physical processes that are specific to high latitudes. Observations have revealed two preferred states of the Arctic winter boundary layer. In the cloudy state, cloud liquid water limits surface radiative cooling, and temperature inversions are weak and elevated. In the radiatively clear state, strong surface radiative cooling leads to the build-up of surface-based temperature inversions. Many large-scale models lack the cloudy state, and some substantially underestimate inversion strength in the clear state. Here, the transformation from a moist to a cold dry air mass is modelled using an idealized Lagrangian perspective. The trajectory includes both boundary layer states, and the single-column experiment is the first Lagrangian Arctic air formation experiment (Larcform 1) organized within GEWEX GASS (Global atmospheric system studies). The intercomparison reproduces the typical biases of large-scale models: Some models lack the cloudy state of the boundary layer due to the representation of mixed-phase micro-physics or to the interaction between micro-and macrophysics. In some models, high emissivities of ice clouds or the lack of an insulating snow layer prevent the build-up of surface-based inversions in the radiatively clear state. Models substantially disagree on the amount of cloud liquid water in the cloudy state and on turbulent heat fluxes under clear skies. Observations of air mass transformations including both boundary layer states would allow for a tighter constraint of model behaviour. PMID:28966718

Select strengths and biases of models in representing the Arctic winter boundary layer over sea ice: the Larcform 1 single column model intercomparison.

PubMed

Pithan, Felix; Ackerman, Andrew; Angevine, Wayne M; Hartung, Kerstin; Ickes, Luisa; Kelley, Maxwell; Medeiros, Brian; Sandu, Irina; Steeneveld, Gert-Jan; Sterk, Ham; Svensson, Gunilla; Vaillancourt, Paul A; Zadra, Ayrton

2016-09-01

Weather and climate models struggle to represent lower tropospheric temperature and moisture profiles and surface fluxes in Arctic winter, partly because they lack or misrepresent physical processes that are specific to high latitudes. Observations have revealed two preferred states of the Arctic winter boundary layer. In the cloudy state, cloud liquid water limits surface radiative cooling, and temperature inversions are weak and elevated. In the radiatively clear state, strong surface radiative cooling leads to the build-up of surface-based temperature inversions. Many large-scale models lack the cloudy state, and some substantially underestimate inversion strength in the clear state. Here, the transformation from a moist to a cold dry air mass is modelled using an idealized Lagrangian perspective. The trajectory includes both boundary layer states, and the single-column experiment is the first L agrangian Arc tic air form ation experiment (Larcform 1) organized within GEWEX GASS (Global atmospheric system studies). The intercomparison reproduces the typical biases of large-scale models: Some models lack the cloudy state of the boundary layer due to the representation of mixed-phase micro-physics or to the interaction between micro-and macrophysics. In some models, high emissivities of ice clouds or the lack of an insulating snow layer prevent the build-up of surface-based inversions in the radiatively clear state. Models substantially disagree on the amount of cloud liquid water in the cloudy state and on turbulent heat fluxes under clear skies. Observations of air mass transformations including both boundary layer states would allow for a tighter constraint of model behaviour.

Effect of atomic layer deposition temperature on current conduction in Al{sub 2}O{sub 3} films formed using H{sub 2}O oxidant

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

Hiraiwa, Atsushi, E-mail: hiraiwa@aoni.waseda.jp, E-mail: qs4a-hriw@asahi-net.or.jp; Matsumura, Daisuke; Kawarada, Hiroshi, E-mail: kawarada@waseda.jp

To develop high-performance, high-reliability gate insulation and surface passivation technologies for wide-bandgap semiconductor devices, the effect of atomic layer deposition (ALD) temperature on current conduction in Al{sub 2}O{sub 3} films is investigated based on the recently proposed space-charge-controlled field emission model. Leakage current measurement shows that Al{sub 2}O{sub 3} metal-insulator-semiconductor capacitors formed on the Si substrates underperform thermally grown SiO{sub 2} capacitors at the same average field. However, using equivalent oxide field as a more practical measure, the Al{sub 2}O{sub 3} capacitors are found to outperform the SiO{sub 2} capacitors in the cases where the capacitors are negatively biased andmore » the gate material is adequately selected to reduce virtual dipoles at the gate/Al{sub 2}O{sub 3} interface. The Al{sub 2}O{sub 3} electron affinity increases with the increasing ALD temperature, but the gate-side virtual dipoles are not affected. Therefore, the leakage current of negatively biased Al{sub 2}O{sub 3} capacitors is approximately independent of the ALD temperature because of the compensation of the opposite effects of increased electron affinity and permittivity in Al{sub 2}O{sub 3}. By contrast, the substrate-side sheet of charge increases with increasing ALD temperature above 210 °C and hence enhances the current of positively biased Al{sub 2}O{sub 3} capacitors more significantly at high temperatures. Additionally, an anomalous oscillatory shift of the current-voltage characteristics with ALD temperature was observed in positively biased capacitors formed by low-temperature (≤210 °C) ALD. This shift is caused by dipoles at the Al{sub 2}O{sub 3}/underlying SiO{sub 2} interface. Although they have a minimal positive-bias leakage current, the low-temperature-grown Al{sub 2}O{sub 3} films cause the so-called blisters problem when heated above 400 °C. Therefore, because of the absence of blistering, a 450 °C ALD process is presently the most promising technology for growing high-reliability Al{sub 2}O{sub 3} films.« less

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.

Influence of temperature fluctuations on equilibrium
ice sheet volume

NASA Astrophysics Data System (ADS)

Bøgeholm Mikkelsen, Troels; Grinsted, Aslak; Ditlevsen, Peter

2018-01-01

Forecasting the future sea level relies on accurate modeling of the response of the Greenland and Antarctic ice sheets to changing temperatures. The surface mass balance (SMB) of the Greenland Ice Sheet (GrIS) has a nonlinear response to warming. Cold and warm anomalies of equal size do not cancel out and it is therefore important to consider the effect of interannual fluctuations in temperature. We find that the steady-state volume of an ice sheet is biased toward larger size if interannual temperature fluctuations are not taken into account in numerical modeling of the ice sheet. We illustrate this in a simple ice sheet model and find that the equilibrium ice volume is approximately 1 m SLE (meters sea level equivalent) smaller when the simple model is forced with fluctuating temperatures as opposed to a stable climate. It is therefore important to consider the effect of interannual temperature fluctuations when designing long experiments such as paleo-spin-ups. We show how the magnitude of the potential bias can be quantified statistically. For recent simulations of the Greenland Ice Sheet, we estimate the bias to be 30 Gt yr-1 (24-59 Gt yr-1, 95 % credibility) for a warming of 3 °C above preindustrial values, or 13 % (10-25, 95 % credibility) of the present-day rate of ice loss. Models of the Greenland Ice Sheet show a collapse threshold beyond which the ice sheet becomes unsustainable. The proximity of the threshold will be underestimated if temperature fluctuations are not taken into account. We estimate the bias to be 0.12 °C (0.10-0.18 °C, 95 % credibility) for a recent estimate of the threshold. In light of our findings it is important to gauge the extent to which this increased variability will influence the mass balance of the ice sheets.

Seasonal Prediction of Regional Surface Air Temperature and First-flowering Date in South Korea using Dynamical Downscaling

NASA Astrophysics Data System (ADS)

Ahn, J. B.; Hur, J.

2015-12-01

The seasonal prediction of both the surface air temperature and the first-flowering date (FFD) over South Korea are produced using dynamical downscaling (Hur and Ahn, 2015). Dynamical downscaling is performed using Weather Research and Forecast (WRF) v3.0 with the lateral forcing from hourly outputs of Pusan National University (PNU) coupled general circulation model (CGCM) v1.1. Gridded surface air temperature data with high spatial (3km) and temporal (daily) resolution are obtained using the physically-based dynamical models. To reduce systematic bias, simple statistical correction method is then applied to the model output. The FFDs of cherry, peach and pear in South Korea are predicted for the decade of 1999-2008 by applying the corrected daily temperature predictions to the phenological thermal-time model. The WRF v3.0 results reflect the detailed topographical effect, despite having cold and warm biases for warm and cold seasons, respectively. After applying the correction, the mean temperature for early spring (February to April) well represents the general pattern of observation, while preserving the advantages of dynamical downscaling. The FFD predictabilities for the three species of trees are evaluated in terms of qualitative, quantitative and categorical estimations. Although FFDs derived from the corrected WRF results well predict the spatial distribution and the variation of observation, the prediction performance has no statistical significance or appropriate predictability. The approach used in the study may be helpful in obtaining detailed and useful information about FFD and regional temperature by accounting for physically-based atmospheric dynamics, although the seasonal predictability of flowering phenology is not high enough. Acknowledgements This work was carried out with the support of the Rural Development Administration Cooperative Research Program for Agriculture Science and Technology Development under Grant Project No. PJ009953 and Project No. PJ009353, Republic of Korea. Reference Hur, J., J.-B. Ahn, 2015. Seasonal Prediction of Regional Surface Air Temperature and First-flowering Date over South Korea, Int. J. Climatol., DOI: 10.1002/joc.4323.

Investigation of the UK37' vs. SST relationship for Atlantic Ocean suspended particulate alkenones: An alternative regression model and discussion of possible sampling bias

NASA Astrophysics Data System (ADS)

Gould, Jessica; Kienast, Markus; Dowd, Michael

2017-05-01

Alkenone unsaturation, expressed as the UK37' index, is closely related to growth temperature of prymnesiophytes, thus providing a reliable proxy to infer past sea surface temperatures (SSTs). Here we address two lingering uncertainties related to this SST proxy. First, calibration models developed for core-top sediments and those developed for surface suspended particulates organic material (SPOM) show systematic offsets, raising concerns regarding the transfer of the primary signal into the sedimentary record. Second, questions remain regarding changes in slope of the UK37' vs. growth temperature relationship at the temperature extremes. Based on (re)analysis of 31 new and 394 previously published SPOM UK37' data from the Atlantic Ocean, a new regression model to relate UK37' to SST is introduced; the Richards curve (Richards, 1959). This non-linear regression model provides a robust calibration of the UK37' vs. SST relationship for Atlantic SPOM samples and uniquely accounts for both the fact that the UK37' index is a proportion, and so must lie between 0 and 1, as well as for the observed reduction in slope at the warm and cold ends of the temperature range. As with prior fits of SPOM UK37' vs. SST, the Richards model is offset from traditional regression models of sedimentary UK37' vs. SST. We posit that (some of) this offset can be attributed to the seasonally and depth biased sampling of SPOM material.

Evaluation of the ASOS impact on climatic normals and assessment of variable-length time periods in calculation of normals

NASA Astrophysics Data System (ADS)

Kauffman, Chad Matthew

The temperature and precipitation that describe the norm of daily, monthly, and seasonal climate conditions are ``climate normals.'' They are usually calculated based on climate data covering a 30-year period, and updated in every 10 years. The next update will take place in year 2001. Because of the advent of the Automated Surface Observations Systems (ASOS) beginning in early 1990s and recognized temperature bias between ASOS and the conventional temperature sensors there is an uncertainty of how the ASOS data should be used to calculate the 1971-2000 temperature normal. This study examined the uncertainty and offered a method to minimize it. It showed that the ASOS bias has a measurable impact on the new 30-year temperature normal. The impact varies among stations and climate regions. Some stations with a cooling trend in ASOS temperature have a cooler normal for their temperature, while others with a warming trend have a warmer normal for temperature. These quantitative evaluations of ASOS effect for stations and regions can be used to reduce ASOS bias in temperature normals. This study also evaluated temperature normals for different length periods and compared them to the 30-year normal. It showed that the difference between the normals, is smaller in maritime climate than in continental temperate climate. In the former, the six- year normal describes a similar temperature variation as the 30-year normal does. In the latter, the 18-year normal starts to resemble the temperature variation that the 30-year normal describes. These results provide a theoretical basis for applying different normals in different regions. The study further compared temperature normal for different periods and identified a seasonal shift in climate change in the southwestern U.S. where the summer maximum temperature has shifted to a late summer month and the winter minimum temperature shifted to an early winter month in the past 30 years.

Implementation of a turbulent orographic form drag scheme in WRF and its application to the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Zhou, Xu; Yang, Kun; Wang, Yan

2018-04-01

Sub-grid-scale orographic variation (smaller than 5 km) exerts turbulent form drag on atmospheric flows and significantly retards the wind speed. The Weather Research and Forecasting model (WRF) includes a turbulent orographic form drag (TOFD) scheme that adds the drag to the surface layer. In this study, another TOFD scheme has been incorporated in WRF3.7, which exerts an exponentially decaying drag from the surface layer to upper layers. To investigate the effect of the new scheme, WRF with the old scheme and with the new one was used to simulate the climate over the complex terrain of the Tibetan Plateau from May to October 2010. The two schemes were evaluated in terms of the direct impact (on wind fields) and the indirect impact (on air temperature and precipitation). The new TOFD scheme alleviates the mean bias in the surface wind components, and clearly reduces the root mean square error (RMSEs) in seasonal mean wind speed (from 1.10 to 0.76 m s-1), when referring to the station observations. Furthermore, the new TOFD scheme also generally improves the simulation of wind profile, as characterized by smaller biases and RMSEs than the old one when referring to radio sounding data. Meanwhile, the simulated precipitation with the new scheme is improved, with reduced mean bias (from 1.34 to 1.12 mm day-1) and RMSEs, which is due to the weakening of water vapor flux at low-level atmosphere with the new scheme when crossing the Himalayan Mountains. However, the simulation of 2-m air temperature is little improved.

Effects of southeastern Pacific sea surface temperature on the double-ITCZ bias in NCAR CESM1

NASA Astrophysics Data System (ADS)

Song, F.; Zhang, G. J.

2016-12-01

The double-intertropical convergence zone (ITCZ) is a long-standing bias in the coupled general circulation models (CGCMs). The warm biases in southeastern Pacific (SEP) sea surface temperature (SST) are also evident in many CGCMs. In this study, the role of SEP SST in the double-ITCZ is investigated by prescribing the observed SEP SST in the Community Earth System Model version 1 (CESM1). Both the double-ITCZ and dry equator problems are significantly improved with SEP SST prescribed. The colder SST over the SEP increases the southeasterly winds extending outside the prescribed SST region, cooling the ocean there via increased evaporation. The enhanced descending motion over the SEP strengthens the Walker circulation, so the low-level wind convergence in the tropical western Pacific is increased. The reduced wind speed leads to warmer SST and stronger convection there. The stronger convection in turn leads to more cloud and reduces the incoming solar radiation, cooling the SST. These competing effects between radiative heat flux and latent heat flux make the atmospheric heat flux secondary to the ocean dynamics in the western Pacific warming. The increased easterly winds over the equatorial Pacific enhance upwelling and shoal the thermocline over the eastern Pacific. This Bjerknes feedback plays an important role in the improvement of dry equator. The changes of surface wind and wind curl also lead to weaker South Equatorial Countercurrent and stronger South Equatorial Current, preventing the warm water from expanding eastward, thereby improving both the double-ITCZ and dry equator.

Assessment of South Asian Summer Monsoon Simulation in CMIP5-Coupled Climate Models During the Historical Period (1850-2005)

NASA Astrophysics Data System (ADS)

Prasanna, Venkatraman

2016-04-01

This paper evaluates the performance of 29 state-of-art CMIP5-coupled atmosphere-ocean general circulation models (AOGCM) in their representation of regional characteristics of monsoon simulation over South Asia. The AOGCMs, despite their relatively coarse resolution, have shown some reasonable skill in simulating the mean monsoon and precipitation variability over the South Asian monsoon region. However, considerable biases do exist with reference to the observed precipitation and also inter-model differences. The monsoon rainfall and surface flux bias with respect to the observations from the historical run for the period nominally from 1850 to 2005 are discussed in detail. Our results show that the coupled model simulations over South Asia exhibit large uncertainties from one model to the other. The analysis clearly brings out the presence of large systematic biases in coupled simulation of boreal summer precipitation, evaporation, and sea surface temperature (SST) in the Indian Ocean, often exceeding 50 % of the climatological values. Many of the biases are common to many models. Overall, the coupled models need further improvement in realistically portraying boreal summer monsoon over the South Asian monsoon region.

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.

Evaluation of Greenland near surface air temperature datasets

DOE PAGES

Reeves Eyre, J. E. Jack; Zeng, Xubin

2017-07-05

Near-surface air temperature (SAT) over Greenland has important effects on mass balance of the ice sheet, but it is unclear which SAT datasets are reliable in the region. Here extensive in situ SAT measurements ( ∼  1400 station-years) are used to assess monthly mean SAT from seven global reanalysis datasets, five gridded SAT analyses, one satellite retrieval and three dynamically downscaled reanalyses. Strengths and weaknesses of these products are identified, and their biases are found to vary by season and glaciological regime. MERRA2 reanalysis overall performs best with mean absolute error less than 2 °C in all months. Ice sheet-average annual mean SAT frommore » different datasets are highly correlated in recent decades, but their 1901–2000 trends differ even in sign. Compared with the MERRA2 climatology combined with gridded SAT analysis anomalies, thirty-one earth system model historical runs from the CMIP5 archive reach  ∼  5 °C for the 1901–2000 average bias and have opposite trends for a number of sub-periods.« less

Evaluation of Greenland near surface air temperature datasets

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

Reeves Eyre, J. E. Jack; Zeng, Xubin

Near-surface air temperature (SAT) over Greenland has important effects on mass balance of the ice sheet, but it is unclear which SAT datasets are reliable in the region. Here extensive in situ SAT measurements ( ∼  1400 station-years) are used to assess monthly mean SAT from seven global reanalysis datasets, five gridded SAT analyses, one satellite retrieval and three dynamically downscaled reanalyses. Strengths and weaknesses of these products are identified, and their biases are found to vary by season and glaciological regime. MERRA2 reanalysis overall performs best with mean absolute error less than 2 °C in all months. Ice sheet-average annual mean SAT frommore » different datasets are highly correlated in recent decades, but their 1901–2000 trends differ even in sign. Compared with the MERRA2 climatology combined with gridded SAT analysis anomalies, thirty-one earth system model historical runs from the CMIP5 archive reach  ∼  5 °C for the 1901–2000 average bias and have opposite trends for a number of sub-periods.« less

Operational correction and validation of the VIIRS TEB longwave infrared band calibration bias during blackbody temperature changes

NASA Astrophysics Data System (ADS)

Wang, Wenhui; Cao, Changyong; Ignatov, Alex; Li, Zhenglong; Wang, Likun; Zhang, Bin; Blonski, Slawomir; Li, Jun

2017-09-01

The Suomi NPP VIIRS thermal emissive bands (TEB) have been performing very well since data became available on January 20, 2012. The longwave infrared bands at 11 and 12 um (M15 and M16) are primarily used for sea surface temperature (SST) retrievals. A long standing anomaly has been observed during the quarterly warm-up-cool-down (WUCD) events. During such event daytime SST product becomes anomalous with a warm bias shown as a spike in the SST time series on the order of 0.2 K. A previous study (CAO et al. 2017) suggested that the VIIRS TEB calibration anomaly during WUCD is due to a flawed theoretical assumption in the calibration equation and proposed an Ltrace method to address the issue. This paper complements that study and presents operational implementation and validation of the Ltrace method for M15 and M16. The Ltrace method applies bias correction during WUCD only. It requires a simple code change and one-time calibration parameter look-up-table update. The method was evaluated using colocated CrIS observations and the SST algorithm. Our results indicate that the method can effectively reduce WUCD calibration anomaly in M15, with residual bias of 0.02 K after the correction. It works less effectively for M16, with residual bias of 0.04 K. The Ltrace method may over-correct WUCD calibration biases, especially for M16. However, the residual WUCD biases are small in both bands. Evaluation results using the SST algorithm show that the method can effectively remove SST anomaly during WUCD events.

Growth, Structural, Electronic, and Magnetic Characterization of GaN, CrN, Fe Islands on CrN, and Fe/CrN Bilayer Thin Films

NASA Astrophysics Data System (ADS)

Alam, Khan

As a part of my Ph.D research, initially I was involved in construction and calibration of an ultra-high vacuum thin film facility, and later on I studied structural, electronic, and magnetic properties of GaN, CrN, Fe/CrN bilayers, and Fe islands on CrN thin films. All of these films were grown by molecular beam epitaxy and characterized with a variety of state-of-the-art techniques including variable temperature reflection high energy electron diffraction, low temperature scanning tunneling microscopy and spectroscopy, variable temperature vibrating sample magnetometry, variable temperature neutron diffraction and reflectometry, variable temperature x-ray diffraction, x-ray reflectometry, Rutherford backscattering, Auger electron spectroscopy, and cross-sectional tunneling electron microscopy. The experimental results are furthermore understood by comparing with numerical calculations using generalized gradient approximation, local density approximation with Hubbard correction, Refl1D, and data analysis and visual environment program. In my first research project, I studied Ga gas adatoms on GaN surfaces. We discovered frozen-out gallium gas adatoms on atomically smooth c(6x12) GaN(0001¯) surface using low temperature scanning tunneling microscopy. We identified adsorption sites of the Ga adatoms on c(6x12) reconstructed surface. Their bonding is determined by measuring low unoccupied molecular orbital level. Absorption sites of the Ga gas adatoms on centered 6x12 are identified, and their asymmetric absorption on the chiral domains is investigated. In second project, I investigated magneto-structural phase transition in chromium nitride (CrN) thin films. The CrN thin films are grown by molecular beam epitaxy. Structural and magnetic transition are studied using variable temperature reflection high energy electron diffraction and variable temperature neutron diffraction. We observed a structural phase transition at the surface at 277+/-2 K, and a sharp, first-order magnetic phase transition from paramagnetic (room temperature) to antiferromagnetic (low temperature) at 280+/-3 K. Our experiments suggest that the structural transition in CrN thin films occur in out-of-plane direction, and epitaxial constraints suppress the in-plane transition; therefore, the low temperature crystal structure of CrN is tetragonal. This new model explains our structural and magnetic data at low temperatures, but it is different than the previously published orthorhombic model. In third project, I studied exchange bias and exchange spring effect in MBE grown Fe/CrN bilayer thin films. We grew Fe/CrN bilayer thin films on MgO(001) substrate by molecular beam epitaxy, and studied them using variable temperature vibrating sample magnetometry, polarized neutron reflectometry, x-ray reflectivity, and cross-sectional transmission electron microscopy. We observed exchange bias and exchange spring effect in all bilayer thin films. We studied the relationship of exchange bias, blocking temperature, and coercivity with Fe and CrN layers thicknesses. We used polarized neutron beam reflectometry to see if spins at Fe/CrN interface are pinned. We found a thin ferromagnetically ordered CrN layer at the interface. In my final project, I studied growth of submonolayer Fe islands on CrN thin films. These films are prepared in two stages: first, a CrN layer is grown by MBE and then a submonolayer Fe is deposited at room temperature from a carefully degassed e-beam evaporator. The films are studied at liquid helium temperature using low temperature scanning tunneling microscopy and spectroscopy. Islands are seen in STM images, after the Fe deposition, at the edges as well as at the center of atomically flat CrN terraces. However, numerical calculations performed by our collaborator Ponce-P'erez from Benem'erita Universidad Aut'onoma de Puebla show that the Fe islands are energetically unstable on the surface. The Fe atoms substitute Cr atoms in the surface layer and the Cr atoms comes out and form islands. In order to find out elemental composition of the islands, we attempted to map local density of state by measuring differential conductance spectra as a function of bias voltage using LT-STS. We observed three characteristically different spectra; one in the CrN substrate and two in the islands. The CrN substrate curve has a "U" shape near Fermi level and a peak at ≈ 105 mV. The islands spectra show Kondo-like resonances at Fermi level; some islands produce a peak whereas others produce a dip the dI/dV curves near Fermi level. Further investigations are needed to determine the origin of the peak and dip in the island curves, as well as to find the composition of the islands.

Longitudinal biases in the Seychelles Dome simulated by 35 ocean-atmosphere coupled general circulation models

NASA Astrophysics Data System (ADS)

Nagura, Motoki; Sasaki, Wataru; Tozuka, Tomoki; Luo, Jing-Jia; Behera, Swadhin K.; Yamagata, Toshio

2013-02-01

Seychelles Dome refers to the shallow climatological thermocline in the southwestern Indian Ocean, where ocean wave dynamics efficiently affect sea surface temperature, allowing sea surface temperature anomalies to be predicted up to 1-2 years in advance. Accurate reproduction of the dome by ocean-atmosphere coupled general circulation models (CGCMs) is essential for successful seasonal predictions in the Indian Ocean. This study examines the Seychelles Dome as simulated by 35 CGCMs, including models used in phase five of the Coupled Model Intercomparison Project (CMIP5). Among the 35 CGCMs, 14 models erroneously produce an upwelling dome in the eastern half of the basin whereas the observed Seychelles Dome is located in the southwestern tropical Indian Ocean. The annual mean Ekman pumping velocity in these models is found to be almost zero in the southern off-equatorial region. This result is inconsistent with observations, in which Ekman upwelling acts as the main cause of the Seychelles Dome. In the models reproducing an eastward-displaced dome, easterly biases are prominent along the equator in boreal summer and fall, which result in shallow thermocline biases along the Java and Sumatra coasts via Kelvin wave dynamics and a spurious upwelling dome in the region. Compared to the CMIP3 models, the CMIP5 models are even worse in simulating the dome longitudes.

Model Development for MODIS Thermal Band Electronic Crosstalk

NASA Technical Reports Server (NTRS)

Chang, Tiejun; Wu, Aisheng; Geng, Xu; Li, Yonghonh; Brinkman, Jake; Keller, Graziela; Xiong, Xiaoxiong

2016-01-01

MODerate-resolution Imaging Spectroradiometer (MODIS) has 36 bands. Among them, 16 thermal emissive bands covering a wavelength range from 3.8 to 14.4 m. After 16 years on-orbit operation, the electronic crosstalk of a few Terra MODIS thermal emissive bands developed substantial issues that cause biases in the EV brightness temperature measurements and surface feature contamination. The crosstalk effects on band 27 with center wavelength at 6.7 m and band 29 at 8.5 m increased significantly in recent years, affecting downstream products such as water vapor and cloud mask. The crosstalk effect is evident in the near-monthly scheduled lunar measurements, from which the crosstalk coefficients can be derived. The development of an alternative approach is very helpful for independent verification.In this work, a physical model was developed to assess the crosstalk impact on calibration as well as in Earth view brightness temperature retrieval. This model was applied to Terra MODIS band 29 empirically to correct the Earth brightness temperature measurements. In the model development, the detectors nonlinear response is considered. The impact of the electronic crosstalk is assessed in two steps. The first step consists of determining the impact on calibration using the on-board blackbody (BB). Due to the detectors nonlinear response and large background signal, both linear and nonlinear coefficients are affected by the crosstalk from sending bands. The second step is to calculate the effects on the Earth view brightness temperature retrieval. The effects include those from affected calibration coefficients and the contamination of Earth view measurements. This model links the measurement bias with crosstalk coefficients, detector non-linearity, and the ratio of Earth measurements between the sending and receiving bands. The correction of the electronic cross talk can be implemented empirically from the processed bias at different brightness temperature. The implementation can be done through two approaches. As routine calibration assessment for thermal infrared bands, the trending over select Earth scenes is processed for all the detectors in a band and the band averaged bias is derived at a certain time. In this case, the correction of an affected band can be made using the regression of the model with band averaged bias and then corrections of detector differences are applied. The second approach requires the trending for individual detectors and the bias for each detector is used for regression with the model. A test using the first approach was made for Terra MODIS band 29 with the biases derived from long-term trending of brightness temperature over ocean and Dome-C.

Biases of the MET Temperature and Relative Humidity Sensor (HMP45) Report

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

Kyrouac, Jenni; Theisen, Adam

The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility Data Quality (DQ) Office was alerted to a potential bias in the surface meteorological instrumentation (MET) temperature when compared with a nearby Mesonet station. This led to an investigation into this problem that was expanded to include many of the other extended facilities (EF) and both the temperature and relative humidity (RH) variables. For this study, the Mesonet was used as the standard reference due to results that showed an increased accuracy in high-humidity environments along with the fact that the Mesonet had previous documented a problemmore » with the HMP45C sensors. Some differences between the sites were taken into account during the analysis: 1. ARM MET sensors were upgraded from an HMP35 to an HMP45 throughout 2007 2. Mesonet switched to aspirated shields in 2009 – To mitigate the differences between aspirated and non-aspirated measurements, data were only analyzed when the wind speed was higher than 3 m/s. This reduced the uncertainty for the non-aspirated measurements from 1.51 ºC to 0.4 ºC. 3. ARM MET is mounted 0.5m higher than the Mesonet station (2.0m versus 1.5m) – This is assumed to have a negligible effect on the differences. 4. Sites were not co-located – For some locations, the distances between sites were as much as 45 km. As part of the investigation into the differences, the Mesonet had reported that the HMP45 sensors had a low-temperature bias in high-humidity environments. This was verified at two different sites where the ARM measurements were compared with the Mesonet measurements. The Mesonet provided redundant temperature measurements from two different sensors at each site. These measurements compared fairly well, while the ARM sensor showed a bias overnight when the humidities were higher. After reviewing the yearly average differences in the data and analyzing the RH data during fog events when we assume it should be 100%, we determined that a majority of the sites have a bias in the RH compared to the Mesonet sites, but that only a few sites show a bias in the temperature measurements that are outside the range of instrument uncertainties. We note that there can be a lot of variability across some of the distances between the MET and Mesonet sites and these biases reported herein should not be used as offsets.« less

Enhanced exchange bias in MnN/CoFe bilayers after high-temperature annealing

NASA Astrophysics Data System (ADS)

Dunz, M.; Schmalhorst, J.; Meinert, M.

2018-05-01

We report an exchange bias of more than 2700 Oe at room temperature in MnN/CoFe bilayers after high-temperature annealing. We studied the dependence of exchange bias on the annealing temperature for different MnN thicknesses in detail and found that samples with tMnN > 32nm show an increase of exchange bias for annealing temperatures higher than TA = 400 °C. Maximum exchange bias values exceeding 2000 Oe with reasonably small coercive fields around 600 Oe are achieved for tMnN = 42, 48 nm. The median blocking temperature of those systems is determined to be 180 °C after initial annealing at TA = 525 °C. X-ray diffraction measurements and Auger depth profiling show that the large increase of exchange bias after high-temperature annealing is accompanied by strong nitrogen diffusion into the Ta buffer layer of the stacks.

CuInP₂S₆ Room Temperature Layered Ferroelectric.

PubMed

Belianinov, A; He, Q; Dziaugys, A; Maksymovych, P; Eliseev, E; Borisevich, A; Morozovska, A; Banys, J; Vysochanskii, Y; Kalinin, S V

2015-06-10

We explore ferroelectric properties of cleaved 2-D flakes of copper indium thiophosphate, CuInP2S6 (CITP), and probe size effects along with limits of ferroelectric phase stability, by ambient and ultra high vacuum scanning probe microscopy. CITP belongs to the only material family known to display ferroelectric polarization in a van der Waals, layered crystal at room temperature and above. Our measurements directly reveal stable, ferroelectric polarization as evidenced by domain structures, switchable polarization, and hysteresis loops. We found that at room temperature the domain structure of flakes thicker than 100 nm is similar to the cleaved bulk surfaces, whereas below 50 nm polarization disappears. We ascribe this behavior to a well-known instability of polarization due to depolarization field. Furthermore, polarization switching at high bias is also associated with ionic mobility, as evidenced both by macroscopic measurements and by formation of surface damage under the tip at a bias of 4 V-likely due to copper reduction. Mobile Cu ions may therefore also contribute to internal screening mechanisms. The existence of stable polarization in a van-der-Waals crystal naturally points toward new strategies for ultimate scaling of polar materials, quasi-2D, and single-layer materials with advanced and nonlinear dielectric properties that are presently not found in any members of the growing "graphene family".

Electrical and Dielectric Properties of a n-Si Schottky Barrier Diode with Bismuth Titanate Interlayer: Effect of Temperature

NASA Astrophysics Data System (ADS)

Yıldırım, M.; Şahin, C.; Altındal, Ş.; Durmuş, P.

2017-03-01

An Au/Bi4Ti3O12/ n-Si Schottky barrier diode (SBD) was fabricated with a 51 nm Bi4Ti3O12 interfacial layer. Admittance measurements of the fabricated SBD were carried out in the bias voltage ( V) range of -4 V and 6 V. Capacitance ( C) and conductance ( G/ω) measurements were carried out in a wide temperature range of 120-380 K so that temperature effects on electrical and dielectric properties of the SBD were investigated. Main electrical parameters were extracted from reverse bias C -2- V plots. It was found that variance of electrical and dielectric parameters of the SBD with temperature is basically different for low and high temperature regions. A fair number (˜1012 eV-1 cm-2) was obtained for surface states ( N ss); however, N ss first decreased then increased with temperature. This result was associated with increased defects with temperature and higher activation energy in the high temperature region. Dielectric parameters of the SBD were also extracted and the dielectric constant of SBD was found as ˜10 at room temperature. Application of modulus formalism to the admittance data revealed temperature-activated dielectric relaxation at 340 K. Results showed that the temperature has considerable effects on electrical and dielectric properties of Au/Bi4Ti3O12/ n-Si SBD.

Plasma processing of superconducting radio frequency cavities

NASA Astrophysics Data System (ADS)

Upadhyay, Janardan

The development of plasma processing technology of superconducting radio frequency (SRF) cavities not only provides a chemical free and less expensive processing method, but also opens up the possibility for controlled modification of the inner surfaces of the cavity for better superconducting properties. The research was focused on the transition of plasma etching from two dimensional flat surfaces to inner surfaces of three dimensional (3D) structures. The results could be applicable to a variety of inner surfaces of 3D structures other than SRF cavities. Understanding the Ar/Cl2 plasma etching mechanism is crucial for achieving the desired modification of Nb SRF cavities. In the process of developing plasma etching technology, an apparatus was built and a method was developed to plasma etch a single cell Pill Box cavity. The plasma characterization was done with the help of optical emission spectroscopy. The Nb etch rate at various points of this cavity was measured before processing the SRF cavity. Cylindrical ring-type samples of Nb placed on the inner surface of the outer wall were used to measure the dependence of the process parameters on plasma etching. The measured etch rate dependence on the pressure, rf power, dc bias, temperature, Cl2 concentration and diameter of the inner electrode was determined. The etch rate mechanism was studied by varying the temperature of the outer wall, the dc bias on the inner electrode and gas conditions. In a coaxial plasma reactor, uniform plasma etching along the cylindrical structure is a challenging task due to depletion of the active radicals along the gas flow direction. The dependence of etch rate uniformity along the cylindrical axis was determined as a function of process parameters. The formation of dc self-biases due to surface area asymmetry in this type of plasma and its variation on the pressure, rf power and gas composition was measured. Enhancing the surface area of the inner electrode to reduce the asymmetry was studied by changing the contour of the inner electrode. The optimized contour of the electrode based on these measurements was chosen for SRF cavity processing.

Magnetic field induced suppression of the forward bias current in Bi2Se3/Si Schottky barrier diodes

NASA Astrophysics Data System (ADS)

Jin, Haoming; Hebard, Arthur

Schottky diodes formed by van der Waals bonding between freshly cleaved flakes of the topological insulator Bi2Se3 and doped silicon substrates show electrical characteristics in good agreement with thermionic emission theory. The motivation is to use magnetic fields to modulate the conductance of the topologically protected conducting surface state. This surface state in close proximity to the semiconductor surface may play an important role in determining the nature of the Schottky barrier. Current-voltage (I-V) and capacitance-voltage (C-V) characteristics were obtained for temperatures in the range 50-300 K and magnetic fields, both perpendicular and parallel to the interface, as high as 7 T. The I-V curve shows more than 6 decades linearity on semi-logarithmic plots, allowing extraction of parameters such as ideality (η), zero-voltage Schottky barrier height (SBH), and series resistance (Rs). In forward bias we observe a field-induced decrease in current which becomes increasingly more pronounced at higher voltages and lower temperature, and is found to be correlated with changes in Rs rather than other barrier parameters. A comparison of changes in Rs in both field direction will be made with magnetoresistance in Bi2Se3 transport measurement. The work is supported by NSF through DMR 1305783.

Analytical modeling of the temporal evolution of hot spot temperatures in silicon solar cells

NASA Astrophysics Data System (ADS)

Wasmer, Sven; Rajsrima, Narong; Geisemeyer, Ino; Fertig, Fabian; Greulich, Johannes Michael; Rein, Stefan

2018-03-01

We present an approach to predict the equilibrium temperature of hot spots in crystalline silicon solar cells based on the analysis of their temporal evolution right after turning on a reverse bias. For this end, we derive an analytical expression for the time-dependent heat diffusion of a breakdown channel that is assumed to be cylindrical. We validate this by means of thermography imaging of hot spots right after turning on a reverse bias. The expression allows to be used to extract hot spot powers and radii from short-term measurements, targeting application in inline solar cell characterization. The extracted hot spot powers are validated at the hands of long-term dark lock-in thermography imaging. Using a look-up table of expected equilibrium temperatures determined by numerical and analytical simulations, we utilize the determined hot spot properties to predict the equilibrium temperatures of about 100 industrial aluminum back-surface field solar cells and achieve a high correlation coefficient of 0.86 and a mean absolute error of only 3.3 K.

Rigid particulate matter sensor

DOEpatents

Hall, Matthew [Austin, TX

2011-02-22

A sensor to detect particulate matter. The sensor includes a first rigid tube, a second rigid tube, a detection surface electrode, and a bias surface electrode. The second rigid tube is mounted substantially parallel to the first rigid tube. The detection surface electrode is disposed on an outer surface of the first rigid tube. The detection surface electrode is disposed to face the second rigid tube. The bias surface electrode is disposed on an outer surface of the second rigid tube. The bias surface electrode is disposed to face the detection surface electrode on the first rigid tube. An air gap exists between the detection surface electrode and the bias surface electrode to allow particulate matter within an exhaust stream to flow between the detection and bias surface electrodes.

Short-Term Retrospective Land Data Assimilation Schemes

NASA Technical Reports Server (NTRS)

Houser, P. R.; Cosgrove, B. A.; Entin, J. K.; Lettenmaier, D.; ODonnell, G.; Mitchell, K.; Marshall, C.; Lohmann, D.; Schaake, J. C.; Duan, Q.;

Presence of glassy state and large exchange bias in nanocrystalline BiFeO3

NASA Astrophysics Data System (ADS)

Srivastav, Simant Kumar; Johari, Anima; Patel, S. K. S.; Gajbhiye, N. S.

2017-11-01

We investigated the static and dynamic aspects of the magnetic properties for single phase nanocrystalline BiFeO3 with average crystallite size of 35 nm. The frequency dependence of the peak is observed in the real part of ac susceptibility χ‧ac vs T measurement and described well by the Vogel-Fulcher law as well as the power law. These analyses indicated the existence of cluster glass state with significant interaction among the spin clusters and results in cluster-glass like cooperative freezing at low temperature. The influence of temperature and magnetic field cooling on the exchange bias effect is investigated. A training effect is also observed. We have reported a significantly high ZFC & FC exchange bias of 200 Oe & 450 Oe at 300 K and 900 Oe & 2100 Oe at 5 K. The obtained results are interpreted in the framework of core-shell model, where the core of the BFO nanoparticles shows antiferromagnetic behavior and surrounded by CG-like ferromagnetic (FM) shell associated to uncompensated surface spins.

Temperature trend biases

NASA Astrophysics Data System (ADS)

Venema, Victor; Lindau, Ralf

2016-04-01

In an accompanying talk we show that well-homogenized national dataset warm more than temperatures from global collections averaged over the region of common coverage. In this poster we want to present auxiliary work about possible biases in the raw observations and on how well relative statistical homogenization can remove trend biases. There are several possible causes of cooling biases, which have not been studied much. Siting could be an important factor. Urban stations tend to move away from the centre to better locations. Many stations started inside of urban areas and are nowadays more outside. Even for villages the temperature difference between the centre and edge can be 0.5°C. When a city station moves to an airport, which often happened around WWII, this takes the station (largely) out of the urban heat island. During the 20th century the Stevenson screen was established as the dominant thermometer screen. This screen protected the thermometer much better against radiation than earlier designs. Deficits of earlier measurement methods have artificially warmed the temperatures in the 19th century. Newer studies suggest we may have underestimated the size of this bias. Currently we are in a transition to Automatic Weather Stations. The net global effect of this transition is not clear at this moment. Irrigation on average decreases the 2m-temperature by about 1 degree centigrade. At the same time, irrigation has increased significantly during the last century. People preferentially live in irrigated areas and weather stations serve agriculture. Thus it is possible that there is a higher likelihood that weather stations are erected in irrigated areas than elsewhere. In this case irrigation could lead to a spurious cooling trend. In the Parallel Observations Science Team of the International Surface Temperature Initiative (ISTI-POST) we are studying influence of the introduction of Stevenson screens and Automatic Weather Stations using parallel measurements, as well as the influence of relocations. Previous validation studies of statistical homogenizations unfortunately have some caveats when it comes to the large-scale trends. The main problem is that the validation datasets had a relatively large signal to noise ratio (SNR), i.e., they had a large break variance relative to the variance of the noise of the difference time series. Our recent work on multiple breakpoint detection methods shows that SNR is very important and that for a SNR around 0.5 the segmentation is about as good as a random segmentation. If the corrections are computed with a composite reference that also contains breaks, the bias due to network-wide transitions that are executed over short periods will reduce the obvious breaks in the single stations, but may not reduce the large-scale bias much. The joint correction method using a decomposition approach (ANOVA) can remove the bias when all breaks (predictors) are known. Any error in the predictors will, however, lead to undercorrection of any large-scale trend biases.

High Sensitivity Stress Sensor Based on Hybrid Materials

NASA Technical Reports Server (NTRS)

Cao, Xian-An (Inventor)

2014-01-01

A sensing device is used to detect the spatial distributions of stresses applied by physical contact with the surface of the sensor or induced by pressure, temperature gradients, and surface absorption. The sensor comprises a hybrid active layer that includes luminophores doped in a polymeric or organic host, altogether embedded in a matrix. Under an electrical bias, the sensor simultaneously converts stresses into electrical and optical signals. Among many applications, the device may be used for tactile sensing and biometric imaging.

Mapping the downwelling atmospheric radiation at the Earth's surface: A research strategy

NASA Technical Reports Server (NTRS)

Raschke, E.

1986-01-01

A strategy is presented along with background material for determining downward atmospheric radiation at the Earth's surface on a regional scale but over the entire globe, using available information on the temperature and humidity of the air near the ground and at cloud base altitudes. Most of these parameters can be inferred from satellite radiance measurements. Careful validation of the derived radiances will be required using ground-based direct measurements of radiances, to avoid systematic biases of these derived field quantities.

High temperature current mirror amplifier

DOEpatents

Patterson, III, Raymond B.

1984-05-22

A high temperature current mirror amplifier having biasing means in the transdiode connection of the input transistor for producing a voltage to maintain the base-collector junction reversed-biased and a current means for maintaining a current through the biasing means at high temperatures so that the base-collector junction of the input transistor remained reversed-biased. For accuracy, a second current mirror is provided with a biasing means and current means on the input leg.

Dynamical downscaling of regional climate over eastern China using RSM with multiple physics scheme ensembles

NASA Astrophysics Data System (ADS)

Peishu, Zong; Jianping, Tang; Shuyu, Wang; Lingyun, Xie; Jianwei, Yu; Yunqian, Zhu; Xiaorui, Niu; Chao, Li

2017-08-01

The parameterization of physical processes is one of the critical elements to properly simulate the regional climate over eastern China. It is essential to conduct detailed analyses on the effect of physical parameterization schemes on regional climate simulation, to provide more reliable regional climate change information. In this paper, we evaluate the 25-year (1983-2007) summer monsoon climate characteristics of precipitation and surface air temperature by using the regional spectral model (RSM) with different physical schemes. The ensemble results using the reliability ensemble averaging (REA) method are also assessed. The result shows that the RSM model has the capacity to reproduce the spatial patterns, the variations, and the temporal tendency of surface air temperature and precipitation over eastern China. And it tends to predict better climatology characteristics over the Yangtze River basin and the South China. The impact of different physical schemes on RSM simulations is also investigated. Generally, the CLD3 cloud water prediction scheme tends to produce larger precipitation because of its overestimation of the low-level moisture. The systematic biases derived from the KF2 cumulus scheme are larger than those from the RAS scheme. The scale-selective bias correction (SSBC) method improves the simulation of the temporal and spatial characteristics of surface air temperature and precipitation and advances the circulation simulation capacity. The REA ensemble results show significant improvement in simulating temperature and precipitation distribution, which have much higher correlation coefficient and lower root mean square error. The REA result of selected experiments is better than that of nonselected experiments, indicating the necessity of choosing better ensemble samples for ensemble.

Globally-Gridded Interpolated Night-Time Marine Air Temperatures 1900-2014

NASA Astrophysics Data System (ADS)

Junod, R.; Christy, J. R.

2016-12-01

Over the past century, climate records have pointed to an increase in global near-surface average temperature. Near-surface air temperature over the oceans is a relatively unused parameter in understanding the current state of climate, but is useful as an independent temperature metric over the oceans and serves as a geographical and physical complement to near-surface air temperature over land. Though versions of this dataset exist (i.e. HadMAT1 and HadNMAT2), it has been strongly recommended that various groups generate climate records independently. This University of Alabama in Huntsville (UAH) study began with the construction of monthly night-time marine air temperature (UAHNMAT) values from the early-twentieth century through to the present era. Data from the International Comprehensive Ocean and Atmosphere Data Set (ICOADS) were used to compile a time series of gridded UAHNMAT, (20S-70N). This time series was homogenized to correct for the many biases such as increasing ship height, solar deck heating, etc. The time series of UAHNMAT, once adjusted to a standard reference height, is gridded to 1.25° pentad grid boxes and interpolated using the kriging interpolation technique. This study will present results which quantify the variability and trends and compare to current trends of other related datasets that include HadNMAT2 and sea-surface temperatures (HadISST & ERSSTv4).

Method for construction of a biased potential for hyperdynamic simulation of atomic systems

NASA Astrophysics Data System (ADS)

Duda, E. V.; Kornich, G. V.

2017-10-01

An approach to constructing a biased potential for hyperdynamic simulation of atomic systems is considered. Using this approach, the diffusion of an atom adsorbed on the surface of a two-dimensional crystal and a vacancy in the bulk of the crystal are simulated. The influence of the variation in the potential barriers due to thermal vibrations of atoms on the results of calculations is discussed. It is shown that the bias of the potential in the hyperdynamic simulation makes it possible to obtain statistical samples of transitions of atomic systems between states, similar to those given by classical molecular dynamics. However, hyperdynamics significantly accelerates computations in comparison with molecular dynamics in the case of temperature-activated transitions and the associated processes in atomic systems.

Radiometric traceability diagnosis and bias correction for the Suomi NPP VIIRS long-wave infrared channels during blackbody unsteady states

NASA Astrophysics Data System (ADS)

Cao, Changyong; Wang, Wenhui; Blonski, Slawomir; Zhang, Bin

2017-05-01

The Suomi National Polar-orbiting Partnership Program (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) Thermal Emissive Bands (TEBs) have been performing well since the data became available on 20 January 2012, and the Sensor Data Record data reached validated maturity on 18 March 2014. While overall the validation has shown that these channels have an estimated absolute uncertainty on the order of 0.1 K based on extensive comparisons, there is a remaining issue that persisted over the years. A calibration bias on the order of 0.1 K is introduced in channels such as M15 during the quarterly blackbody temperature warm-up/cooldown, and the bias is further amplified by the sea surface temperature (SST) retrieval algorithm up to 0.3 K in the global daily-averaged products which causes an apparent spike in the SST time series. Our investigation reveals that this bias is caused by a fundamental but flawed theoretical assumption in the VIIRS calibration equation, which states that the shape of the calibration curve is assumed unchanged from prelaunch to postlaunch without any constrains. While the assumption may work to account for long-term degradation, it has a shortcoming during the blackbody unsteady state. In this study, we present a diagnostic and correction method with a compensatory term (Ltrace) to reconcile the assumption such that it removes the calibration bias during the blackbody temperature changes. The methodology has been tested using historical data, and the results are very positive. The implementation has minimal impacts on the operational data processing system and is readily available for use in operations.

Correcting Borehole Temperture Profiles for the Effects of Postglacial Warming

NASA Astrophysics Data System (ADS)

Rath, V.; Gonzalez-Rouco, J. F.

2010-09-01

Though the investigation of observed borehole temperatures has proved to be a valuable tool for the reconstruction of ground surface temperature histories, there are many open questions concerning the signifcance and accuracy of the reconstructions from these data. In particular, the temperature signal of the warming after the Last glacial Maximum (LGM) is still present in borehole temperature proiles. It also influences the relatively shallow boreholes used in current paleoclimate inversions to estimate temperature changes in the last centuries. This is shown using Monte Carlo experiments on past surface temperature change, using plausible distributions for the most important parameters, i.e.,amplitude and timing of the glacial-interglacial transition, the prior average temperature, and petrophysical properties. It has been argued that the signature of the last glacial-interglacial transition could be responsible for the high amplitudes of millennial temperature reconstructions. However, in shallow boreholes the additional effect of past climate can reasonably approximated by a linear variation of temperature with depth, and thus be accommodated by a "biased" background heat flow. This is good news for borehole climatology. A simple correction based on subtracting an appropriate prior surface temperature history shows promising results reducing these errors considerably, in particular with deeper boreholes, where the warming signal in heat flow can no longer be approximated linearly. We will show examples from North America and Eurasia, comparing temperatures reduced the proposed algoritm with AOGCM modeling results.

Multispectral pyrometry for surface temperature measurement of oxidized Zircaloy claddings

NASA Astrophysics Data System (ADS)

Bouvry, B.; Cheymol, G.; Ramiandrisoa, L.; Javaudin, B.; Gallou, C.; Maskrot, H.; Horny, N.; Duvaut, T.; Destouches, C.; Ferry, L.; Gonnier, C.

2017-06-01

Non-contact temperature measurement in a nuclear reactor is still a huge challenge because of the numerous constraints to consider, such as the high temperature, the steam atmosphere, and irradiation. A device is currently developed at CEA to study the nuclear fuel claddings behavior during a Loss-of-Coolant Accident. As a first step of development, we designed and tested an optical pyrometry procedure to measure the surface temperature of nuclear fuel claddings without any contact, under air, in the temperature range 700-850 °C. The temperature of Zircaloy-4 cladding samples was retrieved at various temperature levels. We used Multispectral Radiation Thermometry with the hypothesis of a constant emissivity profile in the spectral ranges 1-1.3 μm and 1.45-1.6 μm. To allow for comparisons, a reference temperature was provided by a thermocouple welded on the cladding surface. Because of thermal losses induced by the presence of the thermocouple, a heat transfer simulation was also performed to estimate the bias. We found a good agreement between the pyrometry measurement and the temperature reference, validating the constant emissivity profile hypothesis used in the MRT estimation. The expanded measurement uncertainty (k = 2) of the temperature obtained by the pyrometry method was ±4 °C, for temperatures between 700 and 850 °C. Emissivity values, between 0.86 and 0.91 were obtained.

Climate-driven uncertainties in modeling terrestrial gross primary production: a site level to global-scale analysis.

PubMed

Barman, Rahul; Jain, Atul K; Liang, Miaoling

2014-05-01

We used a land surface model to quantify the causes and extents of biases in terrestrial gross primary production (GPP) due to the use of meteorological reanalysis datasets. We first calibrated the model using meteorology and eddy covariance data from 25 flux tower sites ranging from the tropics to the northern high latitudes and subsequently repeated the site simulations using two reanalysis datasets: NCEP/NCAR and CRUNCEP. The results show that at most sites, the reanalysis-driven GPP bias was significantly positive with respect to the observed meteorology-driven simulations. Notably, the absolute GPP bias was highest at the tropical evergreen tree sites, averaging up to ca. 0.45 kg C m(-2)  yr(-1) across sites (ca. 15% of site level GPP). At the northern mid-/high-latitude broadleaf deciduous and the needleleaf evergreen tree sites, the corresponding annual GPP biases were up to 20%. For the nontree sites, average annual biases of up to ca. 20-30% were simulated within savanna, grassland, and shrubland vegetation types. At the tree sites, the biases in short-wave radiation and humidity strongly influenced the GPP biases, while the nontree sites were more affected by biases in factors controlling water stress (precipitation, humidity, and air temperature). In this study, we also discuss the influence of seasonal patterns of meteorological biases on GPP. Finally, using model simulations for the global land surface, we discuss the potential impacts of site-level reanalysis-driven biases on the global estimates of GPP. In a broader context, our results can have important consequences on other terrestrial ecosystem fluxes (e.g., net primary production, net ecosystem production, energy/water fluxes) and reservoirs (e.g., soil carbon stocks). In a complementary study (Barman et al., ), we extend the present analysis for latent and sensible heat fluxes, thus consistently integrating the analysis of climate-driven uncertainties in carbon, energy, and water fluxes using a single modeling framework. © 2013 John Wiley & Sons Ltd.

Inversion of AMSR-E observations for land surface temperature estimation: 2. Global comparison with infrared satellite temperature

NASA Astrophysics Data System (ADS)

Ermida, S. L.; Jiménez, C.; Prigent, C.; Trigo, I. F.; DaCamara, C. C.

2017-03-01

A comparison of land surface temperature (Ts) derived from the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) with infrared Ts is presented. The infrared Ts include clear-sky estimates from the Moderate Resolution Imaging Spectroradiometer (MODIS), the Spinning Enhanced Visible and Infrared Imager, the Geostationary Operational Environmental Satellite (GOES) Imager, and the Japanese Meteorological Imager. The higher discrepancies between AMSR-E and MODIS are observed over deserts and snow-covered areas. The former seems to be associated with Ts underestimation by MODIS, whereas the latter is mostly related to uncertainties in microwave emissivity over snow/ice. Ts differences between AMSR-E and MODIS are significantly reduced after masking out snow and deserts, with a bias change from 2.6/4.6 K to 3.0/1.4 K for daytime/nighttime and a standard deviation (STD) decrease from 7.3/7.9 K to 5.1/3.9 K. When comparing with all infrared sensors, the STD of the differences between microwave and infrared Ts is generally higher than between IR retrievals. However, the biases between microwave and infrared Ts are, in some cases, of the same order as the ones observed between infrared products. This is the case for GOES, with daytime biases with respect to AMSR-E and MODIS of 0.45 K and 0.60 K, respectively. While the infrared Ts are clear-sky estimates, AMSR-E also provides Ts under cloudy conditions. For frequently cloudy regions, this results in a large increase of available Ts estimates (>250%), making the microwave Ts a very powerful complement of the infrared estimates.

Temperature Dependence of Faraday Effect-Induced Bias Error in a Fiber Optic Gyroscope

PubMed Central

Li, Xuyou; Guang, Xingxing; Xu, Zhenlong; Li, Guangchun

2017-01-01

Improving the performance of interferometric fiber optic gyroscope (IFOG) in harsh environments, such as magnetic field and temperature field variation, is necessary for its practical applications. This paper presents an investigation of Faraday effect-induced bias error of IFOG under varying temperature. Jones matrix method is utilized to formulize the temperature dependence of Faraday effect-induced bias error. Theoretical results show that the Faraday effect-induced bias error changes with the temperature in the non-skeleton polarization maintaining (PM) fiber coil. This phenomenon is caused by the temperature dependence of linear birefringence and Verdet constant of PM fiber. Particularly, Faraday effect-induced bias errors of two polarizations always have opposite signs that can be compensated optically regardless of the changes of the temperature. Two experiments with a 1000 m non-skeleton PM fiber coil are performed, and the experimental results support these theoretical predictions. This study is promising for improving the bias stability of IFOG. PMID:28880203

Temperature Dependence of Faraday Effect-Induced Bias Error in a Fiber Optic Gyroscope.

PubMed

Li, Xuyou; Liu, Pan; Guang, Xingxing; Xu, Zhenlong; Guan, Lianwu; Li, Guangchun

2017-09-07

Improving the performance of interferometric fiber optic gyroscope (IFOG) in harsh environments, such as magnetic field and temperature field variation, is necessary for its practical applications. This paper presents an investigation of Faraday effect-induced bias error of IFOG under varying temperature. Jones matrix method is utilized to formulize the temperature dependence of Faraday effect-induced bias error. Theoretical results show that the Faraday effect-induced bias error changes with the temperature in the non-skeleton polarization maintaining (PM) fiber coil. This phenomenon is caused by the temperature dependence of linear birefringence and Verdet constant of PM fiber. Particularly, Faraday effect-induced bias errors of two polarizations always have opposite signs that can be compensated optically regardless of the changes of the temperature. Two experiments with a 1000 m non-skeleton PM fiber coil are performed, and the experimental results support these theoretical predictions. This study is promising for improving the bias stability of IFOG.

Electronegative plasma diagnostic by laser photo-detachment combined with negatively biased Langmuir probe

NASA Astrophysics Data System (ADS)

Oudini, N.; Sirse, N.; Taccogna, F.; Ellingboe, A. R.; Bendib, A.

2018-05-01

We propose a new technique for diagnosing negative ion properties using Langmuir probe assisted pulsed laser photo-detachment. While the classical technique uses a laser pulse to convert negative ions into electron-atom pairs and a positively biased Langmuir probe tracking the change of electron saturation current, the proposed method uses a negatively biased Langmuir probe to track the temporal evolution of positive ion current. The negative bias aims to avoid the parasitic electron current inherent to probe tip surface ablation. In this work, we show through analytical and numerical approaches that, by knowing electron temperature and performing photo-detachment at two different laser wavelengths, it is possible to deduce plasma electronegativity (ratio of negative ion to electron densities) α, and anisothermicity (ratio of electron to negative ion temperatures) γ-. We present an analytical model that links the change in the collected positive ion current to plasma electronegativity and anisothermicity. Particle-In-Cell simulation is used as a numerical experiment covering a wide range of α and γ- to test the new analysis technique. The new technique is sensitive to α in the range 0.5 < α < 10 and yields γ- for large α, where negative ion flux affects the probe sheath behavior, typically α > 1.

Interfacial magnetism and exchange coupling in BiFeO3-CuO nanocomposite.

PubMed

Chakrabarti, Kaushik; Sarkar, Babusona; Ashok, Vishal Dev; Das, Kajari; Chaudhuri, Sheli Sinha; De, S K

2013-12-20

Ferromagnetic BiFeO3 nanocrystals of average size 9 nm were used to form a composite with antiferromagnetic CuO nanosheets, with the composition (x)BiFeO3/(100-x)CuO, x = 0, 20, 40, 50, 60, 80 and 100. The dispersion of BiFeO3 nanocrystals into the CuO matrix was confirmed by x-ray diffraction and transmission electron microscopy. The ferromagnetic ordering as observed in pure BiFeO3 occurs mainly due to the reduction in the particle size as compared to the wavelength (62 nm) of the spiral modulated spin structure of the bulk BiFeO3. Surface spin disorder of BiFeO3 nanocrystals gives rise to an exponential behavior of magnetization with temperature. Strong magnetic exchange coupling between the BiFeO3 nanocrystal and the CuO matrix induces an interfacial superparamagnetic phase with a blocking temperature of about 80 K. Zero field and field cooled magnetizations are analyzed by a ferromagnetic core and disordered spin shell model. The temperature dependence of the calculated saturation magnetization exhibits three magnetic contributions in three temperature regimes. The BiFeO3/CuO nanocomposites reveal an exchange bias effect below 170 K. The maximum exchange bias field HEB is 1841 Oe for x = 50 at 5 K under field cooling of 50 kOe. The exchange bias coupling results in an increase of coercivity of 1934 Oe at 5 K. Blocked spins within an interfacial region give rise to a remarkable exchange bias effect in the nanocomposite due to strong magnetic exchange coupling between the BiFeO3 nanocrystals and the CuO nanosheets.

Recent Advances in the Salinity Retrieval Algorithms for Aquarius and SMAP

NASA Astrophysics Data System (ADS)

Meissner, T.; Wentz, F. J.

2016-12-01

Our presentation discusses the latest improvements in the salinity retrievals for both Aquarius and SMAP since the last releases. The Aquarius V4.0 was released in June 2015 and the SMAP V 1.0 was released in November 2015. Upcoming releases are planned for SMAP (V 2.0) in August 2016 and for Aquarius (V 5.0) late 2017. The full 360o look capability of SMAP makes it possible to take observations from the forward and backward looking direction at the same instance of time. This two-look capability strongly aids the salinity retrievals. One of the largest spurious contaminations in the salinity retrievals is caused by the galaxy that is reflected from the ocean surface. Because in most instances the reflected galaxy appears only in either the forward or the backward look, it is possible to determine its contribution by taking the difference of the measured SMAP brightness temperatures between the two looks. Our result suggests that the surface roughness that is used in the galactic correction needs to be increased and also the strength of some of the galactic sources need to be slightly adjusted. The improved galaxy correction is getting implemented in upcoming Aquarius and SMAP salinity releases and strongly aids the mitigation of residual zonal and temporal biases that are observed in both products. Another major cause of the observed zonal biases in SMAP is the emissive SMAP mesh antenna. In order to correct for it the physical temperature of the antenna is needed. No direct measurements but only a thermal model are available. We discuss recent improvements in the correction for the emissive SMAP antenna and show how most of the zonal biases in V1.0 can be mitigated. Finally, we show that observed salty biases at higher Northern latitudes can be explained by inaccuracies in the model that is used in correcting for the absorption by atmospheric oxygen. These biases can be decreased by fine-tuning the parameters in the absorption model.

Moderate temperature detector development

NASA Technical Reports Server (NTRS)

Marciniec, J. W.; Briggs, R. J.; Sood, A. K.

1981-01-01

P-side backside reflecting constant, photodiode characterization, and photodiode diffusion and G-R currents were investigated in an effort to develop an 8 m to 12 m infrared quantum detector using mercury cadmium telluride. Anodization, phosphorus implantation, and the graded band gap concept were approaches considered for backside formation. Variable thickness diodes were fabricated with a back surface anodic oxide to investigate the effect of this surface preparation on the diffusion limited zero bias impedance. A modeling technique was refined to thoroughly model diode characteristics. Values for the surface recombination velocity in the depletion region were obtained. These values were improved by implementing better surface damage removal techniques.

The effect of radiometer placement and view on inferred directional and hemispheric radiometric temperatures of an urban canopy

NASA Astrophysics Data System (ADS)

Adderley, C.; Christen, A.; Voogt, J. A.

2015-07-01

Any radiometer at a fixed location has a biased view when observing a convoluted, three-dimensional surface such as an urban canopy. The goal of this contribution is to determine the bias of various sensors views observing a simple urban residential neighbourhood (nadir, oblique, hemispherical) over a 24 hour cycle under clear weather conditions. The error in measuring a longwave radiation flux density (L) and/or inferring surface temperatures (T0) is quantified for different times over a diurnal cycle. Panoramic time-sequential thermography (PTST) data were recorded by a thermal camera on a hydraulic mast above a residential canyon in Vancouver, BC. The data set resolved sub-facet temperature variability of all representative urban facets in a 360° swath repetitively over a 24-hour cycle. This data set is used along with computer graphics and vision techniques to project measured fields of L for a given time and pixel onto texture sheets of a three-dimensional urban surface model at a resolution of centimetres. The resulting data set attributes L of each pixel on the texture sheets to different urban facets and associates facet location, azimuth, slope, material, and sky view factor. The texture sheets of L are used to calculate the complete surface temperature (T0,C) and to simulate the radiation in the field of view (FOV) of narrow and hemispheric radiometers observing the same urban surface (in absence of emissivity and atmospheric effects). The simulated directional (T0,d) and hemispheric (T0,h) radiometric temperatures inferred from various biased views are compared to T0,C. For a range of simulated off-nadir (φ) and azimuth (Ω) angles, T0,d(φ,Ω) and T0,C differ between -2.6 and +2.9 K over the course of the day. The effects of effective anisotropy are highest in the daytime, particularly around sunrise and sunset when different views can lead to differences in T0,d(φ,Ω) that are as high as 3.5 K. For a sensor with a narrow FOV in the nadir of the urban surface, T0,d(φ=0) differs from T0,C by +1.9 K (day) and by -1.6 K (night). Simulations of the FOV of hemispherical, downward-facing pyrgeometers at 270 positions show considerable variations in the measured L and inferred hemispherical radiometeric temperature T0,h as a function of both horizontal placement and height. The root mean squared error (RMSE) between different horizontal positions in retrieving outgoing longwave emittance L↑ decreased exponentially with height, and was 11.2, 6.3 and 2.0 W m-2 at 2, 3, and 5 times the mean building height zb. Generally, above 3.5zb the horizontal positional error is less than the typical accuracy of common pyrgeometers. The average T0,h over 24 h determined from the hemispherical radiometer sufficiently above an urban surface is in close agreement with the average T0,C. However, over the course of the day, the difference between T0,h and T0,C shows an RMSE of 1.7 K (9.4 W m-2) because the relative contributions of facets within the projected FOV of a pyrgeometer do not correspond to their fractions of the complete urban surface.

The effect of radiometer placement and view on inferred directional and hemispheric radiometric temperatures of a urban canopy

NASA Astrophysics Data System (ADS)

Adderley, C.; Christen, A.; Voogt, J. A.

2015-02-01

Any radiometer at a fixed location has a biased view when observing a convoluted, three dimensional surface such as an urban canopy. The goal of this contribution is to determine the bias of various sensors views observing a simple urban residential neighbourhood (nadir, oblique, hemispherical) over a 24 h cycle under clear weather conditions. The error in measuring longwave radiance (L) and/or inferring surface temperatures (T0) is quantified for different times over a diurnal cycle. Panoramic time-sequential thermography (PTST) data was recorded by a thermal camera on a hydraulic mast above a residential canyon in Vancouver, BC. The dataset resolved sub-facet temperature variability of all representative urban facets in a 360° swath repetitively over a 24 h cycle. This dataset is used along with computer graphics and vision techniques to project measured fields of L for a given time and pixel onto texture sheets of a three-dimensional urban surface model at a resolution of centimetres. The resulting dataset attributes L of each pixel on the texture sheets to different urban facets and associates facet location, azimuth, slope, material, and sky view factor. The texture sheets of L are used to calculate the complete surface temperature (T0,C) and to simulate the instantaneous field of view (IFOV) of narrow and hemispheric radiometers observing the same urban surface (in absence of emissivity and atmospheric effects). The simulated directional (T0,d) and hemispheric (T0,h) radiometric temperatures inferred from various biased views are compared to T0,C. For a range of simulated off-nadir (ϕ) and azimuth (Ω) angles, T0,d (ϕ, Ω) and T0,C differ between -2.7 and +2.9 K over the course of the day. The effects of effective anisotropy are highest in the daytime, particularly around sunrise and sunset when different views can lead to differences in T0,d (ϕ, Ω) that are as high as 3.5 K. For a sensor with a narrow IFOV in the nadir of the urban surface, T0,d (ϕ = 0°) differs from T0,C by -2.2 K (day) and by +1.6 K (night). Simulations of the IFOV of hemispherical, downward-facing pyrgeometers at 270 positions show considerable variations in the measured L and inferred hemispherical radiometeric temperature T0,h as a function of both horizontal placement and height. The root mean squared error (RMSE) between different horizontal positions in retrieving outgoing longwave emittance L↑ decreased exponentially with height, and was 11.2, 6.3 and 2.0 W m-2 at 2, 3, and 5 times the mean building height zb. Generally, above 3.5 zb the horizontal positional error is less than the typical accuracy of common pyrgeometers. The average T0,h over 24 h determined from the hemispherical radiometer sufficiently above an urban surface is in close agreement with the average T0,C. However, over the course of the day, the difference between T0,h and T0,C shows an RMSE of 1.8 K (9.9 W m-2) because the relative contributions of facets within the projected IFOV of a pyrgeometer do not correspond to their fractions of the complete urban surface.

Seasonal variations of the backscattering coefficient measured by radar altimeters over the Antarctic Ice Sheet

NASA Astrophysics Data System (ADS)

Ibrahime Adodo, Fifi; Remy, Frédérique; Picard, Ghislain

2018-05-01

Spaceborne radar altimeters are a valuable tool for observing the Antarctic Ice Sheet. The radar wave interaction with the snow provides information on both the surface and the subsurface of the snowpack due to its dependence on the snow properties. However, the penetration of the radar wave within the snowpack also induces a negative bias on the estimated surface elevation. Empirical corrections of this space- and time-varying bias are usually based on the backscattering coefficient variability. We investigate the spatial and seasonal variations of the backscattering coefficient at the S (3.2 GHz ˜ 9.4 cm), Ku (13.6 GHz ˜ 2.3 cm) and Ka (37 GHz ˜ 0.8 cm) bands. We identified that the backscattering coefficient at Ku band reaches a maximum in winter in part of the continent (Region 1) and in the summer in the remaining (Region 2), while the evolution at other frequencies is relatively uniform over the whole continent. To explain this contrasting behavior between frequencies and between regions, we studied the sensitivity of the backscattering coefficient at three frequencies to several parameters (surface snow density, snow temperature and snow grain size) using an electromagnetic model. The results show that the seasonal cycle of the backscattering coefficient at Ka frequency is dominated by the volume echo and is mainly driven by snow temperature evolution everywhere. In contrast, at S band, the cycle is dominated by the surface echo. At Ku band, the seasonal cycle is dominated by the volume echo in Region 1 and by the surface echo in Region 2. This investigation provides new information on the seasonal dynamics of the Antarctic Ice Sheet surface and provides new clues to build more accurate corrections of the radar altimeter surface elevation signal in the future.

High temperature current mirror amplifier

DOEpatents

Patterson, R.B. III.

1984-05-22

Disclosed is a high temperature current mirror amplifier having biasing means in the transdiode connection of the input transistor for producing a voltage to maintain the base-collector junction reversed-biased and a current means for maintaining a current through the biasing means at high temperatures so that the base-collector junction of the input transistor remained reversed-biased. For accuracy, a second current mirror is provided with a biasing means and current means on the input leg. 2 figs.

Mapping Surface Temperatures on a Debris-Covered Glacier with an Unmanned Aerial Vehicle

NASA Astrophysics Data System (ADS)

Kraaijenbrink, Philip D. A.; Shea, Joseph M.; Litt, Maxime; Steiner, Jakob F.; Treichler, Désirée; Koch, Inka; Immerzeel, Walter W.

2018-05-01

A mantel of debris cover often accumulates across the surface of glaciers in active mountain ranges with exceptionally steep terrain, such as the Andes, Himalaya and New Zealand Alps. Such a supraglacial debris layer has a major influence on a glacier's surface energy budget, enhancing radiation absorption and melt when the layer is thin, but insulating the ice when thicker than a few cm. Information on spatially distributed debris surface temperature has the potential to provide insight into the properties of the debris, its effects on the ice below and its influence on the near-surface boundary layer. Here, we deploy an unmanned aerial vehicle (UAV) equipped with a thermal infrared sensor on three separate missions over one day to map changing surface temperatures across the debris-covered Lirung Glacier in the Central Himalaya. We present a methodology to georeference and process the acquired thermal imagery, and correct for emissivity and sensor bias. Derived UAV surface temperatures are compared with distributed simultaneous in situ temperature measurements as well as with Landsat 8 thermal satellite imagery. Results show that the UAV-derived surface temperatures vary greatly both spatially and temporally, with -1.4±1.8, 11.0 ±5.2 and 15.3±4.7 °C for the three flights (mean±sd), respectively. The range in surface temperatures over the glacier during the morning is very large with almost 50 °C. Ground-based measurements are generally in agreement with the UAV imagery, but considerable deviations are present that are likely due to differences in measurement technique and approach, and validation is difficult as a result. The difference in spatial and temporal variability captured by the UAV as compared with much coarser satellite imagery is striking and it shows that satellite derived temperature maps should be interpreted with care. We conclude that UAVs provide a suitable means to acquire surface temperature maps of debris-covered glacier surfaces at high spatial and temporal resolution, but that there are caveats with regard to absolute temperature measurement.

Properties of the surface generation-recombination noise in 1.94 μm GaSb-based laser diodes

NASA Astrophysics Data System (ADS)

Glemža, Justinas; Palenskis, Vilius; Pralgauskaitė, Sandra; Vyšniauskas, Juozas; Matukas, Jonas

2018-06-01

A detail investigation of generation-recombination (g-r) noise in 1.94 μm GaSb-based type-I ridge waveguide laser diodes (LDs) has been performed in a temperature range (230-295) K. Lorentzian-type noise spectra have been observed in the current range below the threshold at the forward and reverse biases of the LDs with the same characteristic time (3.7 μs) and activation energy (≈0.37 eV) of charge carriers transitions associated with the g-r processes. An equivalent electrical circuit possessing the voltage noise source is presented, which allows the description of both the current-voltage characteristic and the voltage fluctuation spectral density of the laser diode. Results indicate that the origin of the g-r noise in the investigated samples is the surface recombination caused by the surface leakage current channel between n+GaSb and p+GaSb contacts, which is practically independent from the applied bias polarity.

weather@home 2: validation of an improved global-regional climate modelling system

NASA Astrophysics Data System (ADS)

Guillod, Benoit P.; Jones, Richard G.; Bowery, Andy; Haustein, Karsten; Massey, Neil R.; Mitchell, Daniel M.; Otto, Friederike E. L.; Sparrow, Sarah N.; Uhe, Peter; Wallom, David C. H.; Wilson, Simon; Allen, Myles R.

2017-05-01

Extreme weather events can have large impacts on society and, in many regions, are expected to change in frequency and intensity with climate change. Owing to the relatively short observational record, climate models are useful tools as they allow for generation of a larger sample of extreme events, to attribute recent events to anthropogenic climate change, and to project changes in such events into the future. The modelling system known as weather@home, consisting of a global climate model (GCM) with a nested regional climate model (RCM) and driven by sea surface temperatures, allows one to generate a very large ensemble with the help of volunteer distributed computing. This is a key tool to understanding many aspects of extreme events. Here, a new version of the weather@home system (weather@home 2) with a higher-resolution RCM over Europe is documented and a broad validation of the climate is performed. The new model includes a more recent land-surface scheme in both GCM and RCM, where subgrid-scale land-surface heterogeneity is newly represented using tiles, and an increase in RCM resolution from 50 to 25 km. The GCM performs similarly to the previous version, with some improvements in the representation of mean climate. The European RCM temperature biases are overall reduced, in particular the warm bias over eastern Europe, but large biases remain. Precipitation is improved over the Alps in summer, with mixed changes in other regions and seasons. The model is shown to represent the main classes of regional extreme events reasonably well and shows a good sensitivity to its drivers. In particular, given the improvements in this version of the weather@home system, it is likely that more reliable statements can be made with regards to impact statements, especially at more localized scales.

Work functions of hafnium nitride thin films as emitter material for field emitter arrays

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

Gotoh, Yasuhito, E-mail: gotoh.yasuhito.5w@kyoto-u.ac.jp; Fujiwara, Sho; Tsuji, Hiroshi

The work functions of hafnium nitride thin films prepared by radio-frequency magnetron sputtering were investigated in vacuum, before and after surface cleaning processes, with a view of improving the properties of as-fabricated field emitter arrays comprising hafnium nitride emitters. The measurement of the work function was first performed for the as-deposited films and then for films subjected to surface cleaning process, either thermal treatment or ion bombardment. Thermal treatment at a maximum temperature of 300 °C reduced the work function by 0.7 eV. Once the film was heated, the work function maintained the reduced value, even after cooling to room temperature. Amore » little change in the work function was observed for the second and third thermal treatments. The ion bombardment was conducted by exposing the sample to a thin plasma for different sample bias conditions and processing times. When the sample was biased at −10 V, the work function decreased by 0.6 eV. The work function reduction became saturated in the early stage of the ion bombardment. When the sample was biased at −50 V, the work function exhibited different behaviors, that is, first it decreased rapidly and then increased in response to the increase in processing time. The lowest attainable work function was found to be 4.00 eV. It should be noted that none of the work function values reported in this paper were obtained using surfaces that were demonstrated to be free from oxygen contamination. The present results suggest that the current–voltage characteristics of a field emitter array can be improved by a factor of 25–50 by the examined postprocesses.« less

Improving model biases in an ESM with an isopycnic ocean component by accounting for wind work on oceanic near-inertial motions.

NASA Astrophysics Data System (ADS)

de Wet, P. D.; Bentsen, M.; Bethke, I.

2016-02-01

It is well-known that, when comparing climatological parameters such as ocean temperature and salinity to the output of an Earth System Model (ESM), the model exhibits biases. In ESMs with an isopycnic ocean component, such as NorESM, insufficient vertical mixing is thought to be one of the causes of such differences between observational and model data. However, enhancing the vertical mixing of the model's ocean component not only requires increasing the energy input, but also sound physical reasoning for doing so. Various authors have shown that the action of atmospheric winds on the ocean's surface is a major source of energy input into the upper ocean. However, due to model and computational constraints, oceanic processes linked to surface winds are incompletely accounted for. Consequently, despite significantly contributing to the energy required to maintain ocean stratification, most ESMs do not directly make provision for this energy. In this study we investigate the implementation of a routine in which the energy from work done on oceanic near-inertial motions is calculated in an offline slab model. The slab model, which has been well-documented in the literature, runs parallel to but independently from the ESM's ocean component. It receives wind fields with a frequency higher than that of the coupling frequency, allowing it to capture the fluctuations in the winds on shorter time scales. The additional energy calculated thus is then passed to the ocean component, avoiding the need for increased coupling between the components of the ESM. Results show localised reduction in, amongst others, the salinity and temperature biases of NorESM, confirming model sensitivity to wind-forcing and points to the need for better representation of surface processes in ESMs.

Effects of the Antenna Aperture on Remote Sensing of Sea Surface Salinity at L-Band

NASA Technical Reports Server (NTRS)

Dinnat, Emmanuel P.; LeVine, David M.

2006-01-01

Remote sensing of sea surface salinity with sufficient accuracy to meet the needs of global oceanography is a challenging task. The global variability of the salinity signal in the open ocean is only a few Kelvin even at L-band and an accuracy on the order of 0.1K is desired to study the influence of salinity on ocean circulation and energy exchange with the atmosphere. On the other hand, resolution is not an issue for understanding the dynamics of the open ocean where scales of hundreds of km are not uncommon. This permits remote sensing with large antenna footprints and spatial averaging to reduce noise. However, antennas with large footprints introduce other problems. For example, the angle of incidence and hence the brightness temperature varies over the footprint. Similarly, the polarization of brightness temperature relative to the antenna ports changes. Studies have been conducted using antenna patterns representative of the antenna that will be flown on the Aquarius mission to examine these effects. Aquarius is a pushbroom style radiometer with three beams looking across track away from the sun. The beams are at incidences angles (at the spacecraft) of about 26.5, 34 and 40 degrees each with a half-power beam width of about 5.8 degrees. It is shown that the measured brightness temperature is biased relative to the value at boresight because of changes across the field of view. The bias can be as much as 4K and positive or negative depending on polarization. Polarization mixing because of the variations of the local plane of incidence across the footprint also occur and can result in biased polarimetric measurements. A bias in the third Stokes parameter of as much as 0.4K is possible. Such effects may affect algorithms that use the third Stokes parameter to correct for Faraday rotation. Another issue associated with the antenna is sun glint. This is an issue determined by surface roughness and antenna sidelobes. Examples will be given for the random component (glint) for the case of the Aquarius antenna beams. Fortunately, the Aquarius beams mostly look to the dark side of the day-night termination, but during some portions of the year they will see sun-lighted ocean. In this case, glint could be an issue for the inner-most beam.

Calculation of surface and top of atmosphere radiative fluxes from physical quantities based on ISCCP data sets. 1: Method and sensitivity to input data uncertainties

NASA Technical Reports Server (NTRS)

Zhang, Y.-C.; Rossow, W. B.; Lacis, A. A.

1995-01-01

The largest uncertainty in upwelling shortwave (SW) fluxes (approximately equal 10-15 W/m(exp 2), regional daily mean) is caused by uncertainties in land surface albedo, whereas the largest uncertainty in downwelling SW at the surface (approximately equal 5-10 W/m(exp 2), regional daily mean) is related to cloud detection errors. The uncertainty of upwelling longwave (LW) fluxes (approximately 10-20 W/m(exp 2), regional daily mean) depends on the accuracy of the surface temperature for the surface LW fluxes and the atmospheric temperature for the top of atmosphere LW fluxes. The dominant source of uncertainty is downwelling LW fluxes at the surface (approximately equal 10-15 W/m(exp 2)) is uncertainty in atmospheric temperature and, secondarily, atmospheric humidity; clouds play little role except in the polar regions. The uncertainties of the individual flux components and the total net fluxes are largest over land (15-20 W/m(exp 2)) because of uncertainties in surface albedo (especially its spectral dependence) and surface temperature and emissivity (including its spectral dependence). Clouds are the most important modulator of the SW fluxes, but over land areas, uncertainties in net SW at the surface depend almost as much on uncertainties in surface albedo. Although atmospheric and surface temperature variations cause larger LW flux variations, the most notable feature of the net LW fluxes is the changing relative importance of clouds and water vapor with latitude. Uncertainty in individual flux values is dominated by sampling effects because of large natrual variations, but uncertainty in monthly mean fluxes is dominated by bias errors in the input quantities.

Robust global ocean cooling trend for the pre-industrial Common Era

NASA Astrophysics Data System (ADS)

McGregor, Helen V.; Evans, Michael N.; Goosse, Hugues; Leduc, Guillaume; Martrat, Belen; Addison, Jason A.; Mortyn, P. Graham; Oppo, Delia W.; Seidenkrantz, Marit-Solveig; Sicre, Marie-Alexandrine; Phipps, Steven J.; Selvaraj, Kandasamy; Thirumalai, Kaustubh; Filipsson, Helena L.; Ersek, Vasile

2015-09-01

The oceans mediate the response of global climate to natural and anthropogenic forcings. Yet for the past 2,000 years -- a key interval for understanding the present and future climate response to these forcings -- global sea surface temperature changes and the underlying driving mechanisms are poorly constrained. Here we present a global synthesis of sea surface temperatures for the Common Era (CE) derived from 57 individual marine reconstructions that meet strict quality control criteria. We observe a cooling trend from 1 to 1800 CE that is robust against explicit tests for potential biases in the reconstructions. Between 801 and 1800 CE, the surface cooling trend is qualitatively consistent with an independent synthesis of terrestrial temperature reconstructions, and with a sea surface temperature composite derived from an ensemble of climate model simulations using best estimates of past external radiative forcings. Climate simulations using single and cumulative forcings suggest that the ocean surface cooling trend from 801 to 1800 CE is not primarily a response to orbital forcing but arises from a high frequency of explosive volcanism. Our results show that repeated clusters of volcanic eruptions can induce a net negative radiative forcing that results in a centennial and global scale cooling trend via a decline in mixed-layer oceanic heat content.

Robust global ocean cooling trend for the pre-industrial Common Era

USGS Publications Warehouse

McGregor, Helen V.; Evans, Michael N.; Goosse, Hugues; Leduc, Guillaume; Martrat, Belen; Addison, Jason A.; Mortyn, P. Graham; Oppo, Delia W.; Seidenkrantz, Marit-Solveig; Sicre, Marie-Alexandrine; Phipps, Steven J.; Selvaraj, Kandasamy; Thirumalai, Kaustubh; Filipsson, Helena L.; Ersek, Vasile

2015-01-01

The oceans mediate the response of global climate to natural and anthropogenic forcings. Yet for the past 2,000 years — a key interval for understanding the present and future climate response to these forcings — global sea surface temperature changes and the underlying driving mechanisms are poorly constrained. Here we present a global synthesis of sea surface temperatures for the Common Era (CE) derived from 57 individual marine reconstructions that meet strict quality control criteria. We observe a cooling trend from 1 to 1800 CEthat is robust against explicit tests for potential biases in the reconstructions. Between 801 and 1800 CE, the surface cooling trend is qualitatively consistent with an independent synthesis of terrestrial temperature reconstructions, and with a sea surface temperature composite derived from an ensemble of climate model simulations using best estimates of past external radiative forcings. Climate simulations using single and cumulative forcings suggest that the ocean surface cooling trend from 801 to 1800 CE is not primarily a response to orbital forcing but arises from a high frequency of explosive volcanism. Our results show that repeated clusters of volcanic eruptions can induce a net negative radiative forcing that results in a centennial and global scale cooling trend via a decline in mixed-layer oceanic heat content.

An Assessment of the SST Simulation Using the Climate Forecast System Coupled to the SSiB Surface Model

NASA Astrophysics Data System (ADS)

Wang, Y.; Xue, Y.; Huang, B.; Lee, J.; De Sales, F.

2016-12-01

A long term simulation has been conducted using the Climate Forecast System (CFSv2) coupled to the SSiB-2 land model, which consists of the Global Forecast System atmospheric model (GFS) and the Modular Ocean model - version 4 (MOM4) as the ocean component. This study evaluates the model's performance in simulating sea surface temperature (SST) mean state, trend, and inter-annual and decadal variabilities. The model is able to produce the reasonable spatial distribution of the SST climatology; however, it has prominent large scale biases. In the middle latitude of the Northern Hemisphere, major cold biases is close to the warm side of the large SST gradients, which may be associated with the weaker Kuroshio and Gulf Stream extensions that diffuse the SST gradient. IN addition, warm biases extend along the west coast of the North America continent to the high latitude, which may be related with excessive Ekman down-welling and solar radiation fluxes reaching to the surface due to the lack of cloud there. Warm biases also exist over the tropical cold tough areas in the Pacific and Atlantic. The global SST trend and interannual variations are well captured except for that in the south Hemisphere after year 2000, which is mainly contributed by the bias from the southern Pacific Ocean. Although the model fails to accurately produce ENSO events in proper years, it does reproduce the ENSO frequency well; they are skewed toward more warm events after 1990. The model also shows ability in SST decadal variation, such as the so-called inter-decadal Pacific oscillation (IPO); however, its phases seem to go reversely compared with the observation.

Effects of modeled tropical sea surface temperature variability on coral reef bleaching predictions

NASA Astrophysics Data System (ADS)

Van Hooidonk, R. J.

2011-12-01

Future widespread coral bleaching and subsequent mortality has been projected with sea surface temperature (SST) data from global, coupled ocean-atmosphere general circulation models (GCMs). While these models possess fidelity in reproducing many aspects of climate, they vary in their ability to correctly capture such parameters as the tropical ocean seasonal cycle and El Niño Southern Oscillation (ENSO) variability. These model weaknesses likely reduce the skill of coral bleaching predictions, but little attention has been paid to the important issue of understanding potential errors and biases, the interaction of these biases with trends and their propagation in predictions. To analyze the relative importance of various types of model errors and biases on coral reef bleaching predictive skill, various intra- and inter-annual frequency bands of observed SSTs were replaced with those frequencies from GCMs 20th century simulations to be included in the Intergovernmental Panel on Climate Change (IPCC) 5th assessment report. Subsequent thermal stress was calculated and predictions of bleaching were made. These predictions were compared with observations of coral bleaching in the period 1982-2007 to calculate skill using an objective measure of forecast quality, the Peirce Skill Score (PSS). This methodology will identify frequency bands that are important to predicting coral bleaching and it will highlight deficiencies in these bands in models. The methodology we describe can be used to improve future climate model derived predictions of coral reef bleaching and it can be used to better characterize the errors and uncertainty in predictions.

North Tropical Atlantic Climate Variability and Model Biases

NASA Astrophysics Data System (ADS)

Yang, Y.

2017-12-01

Remote forcing from El Niño-Southern Oscillation (ENSO) and local ocean-atmosphere feedback are important for climate variability over the North Tropical Atlantic. These two factors are extracted by the ensemble mean and inter-member difference of a 10-member Pacific Ocean-Global Atmosphere (POGA) experiment, in which sea surface temperatures (SSTs) are restored to the observed anomalies over the tropical Pacific but fully coupled to the atmosphere elsewhere. POGA reasonably captures main features of observed North Tropical Atlantic variability. ENSO forced and local North Tropical Atlantic modes (NTAMs) develop with wind-evaporation-SST feedback, explaining one third and two thirds of total variance respectively. Notable biases, however, exist. The seasonality of the simulated NTAM is delayed by one month, due to the late development of the North Atlantic Oscillation (NAO) in the model. A spurious band of enhanced sea surface temperature (SST) variance (SBEV) is identified over the northern equatorial Atlantic in POGA and 14 out of 23 CMIP5 models. The SBEV is especially pronounced in boreal spring and due to the combined effect of both anomalous atmospheric thermal forcing and oceanic vertical upwelling. While the tropical North Atlantic variability is only weakly correlated with the Atlantic Zonal Mode (AZM) in observations, the SBEV in CMIP5 produces conditions that drive and intensify the AZM variability via triggering the Bjerknes feedback. This partially explains why AZM is strong in some CMIP5 models even though the equatorial cold tongue and easterly trades are biased low.

Seasat scatterometer versus scanning multichannel microwave radiometer wind speeds: A comparison on a global scale

NASA Astrophysics Data System (ADS)

Boutin, J.; Etcheto, J.

1990-12-01

The wind speeds obtained from the Seasat A scatterometer system (SASS) and scanning multichannel microwave radiometer (SMMR) using two different algorithms were compared on a global scale. The temperature dependence of the sea surface emissivity was shown to be incorrectly modelled. After correcting this effect, regional differences up to ± 3 m s-1 are still observed between both instruments, even though they balance in global averaging, resulting in no bias between the global data sets. Validation experiments of satellite wind speeds should take into account this possibility of regional biases and insure the validity of the measurements everywhere in the global ocean.

Laser diode absorption spectroscopy for accurate CO(2) line parameters at 2 microm: consequences for space-based DIAL measurements and potential biases.

PubMed

Joly, Lilian; Marnas, Fabien; Gibert, Fabien; Bruneau, Didier; Grouiez, Bruno; Flamant, Pierre H; Durry, Georges; Dumelie, Nicolas; Parvitte, Bertrand; Zéninari, Virginie

2009-10-10

Space-based active sensing of CO(2) concentration is a very promising technique for the derivation of CO(2) surface fluxes. There is a need for accurate spectroscopic parameters to enable accurate space-based measurements to address global climatic issues. New spectroscopic measurements using laser diode absorption spectroscopy are presented for the preselected R30 CO(2) absorption line ((20(0)1)(III)<--(000) band) and four others. The line strength, air-broadening halfwidth, and its temperature dependence have been investigated. The results exhibit significant improvement for the R30 CO(2) absorption line: 0.4% on the line strength, 0.15% on the air-broadening coefficient, and 0.45% on its temperature dependence. Analysis of potential biases of space-based DIAL CO(2) mixing ratio measurements associated to spectroscopic parameter uncertainties are presented.

Impact of automatization in temperature series in Spain and comparison with the POST-AWS dataset

NASA Astrophysics Data System (ADS)

Aguilar, Enric; López-Díaz, José Antonio; Prohom Duran, Marc; Gilabert, Alba; Luna Rico, Yolanda; Venema, Victor; Auchmann, Renate; Stepanek, Petr; Brandsma, Theo

2016-04-01

Climate data records are most of the times affected by inhomogeneities. Especially inhomogeneities introducing network-wide biases are sometimes related to changes happening almost simultaneously in an entire network. Relative homogenization is difficult in these cases, especially at the daily scale. A good example of this is the substitution of manual observations (MAN) by automatic weather stations (AWS). Parallel measurements (i.e. records taken at the same time with the old (MAN) and new (AWS) sensors can provide an idea of the bias introduced and help to evaluate the suitability of different correction approaches. We present here a quality controlled dataset compiled under the DAAMEC Project, comprising 46 stations across Spain and over 85,000 parallel measurements (AWS-MAN) of daily maximum and minimum temperature. We study the differences between both sensors and compare it with the available metadata to account for internal inhomogeneities. The differences between both systems vary much across stations, with patterns more related to their particular settings than to climatic/geographical reasons. The typical median biases (AWS-MAN) by station (comprised between the interquartile range) oscillate between -0.2°C and 0.4 in daily maximum temperature and between -0.4°C and 0.2°C in daily minimum temperature. These and other results are compared with a larger network, the Parallel Observations Scientific Team, a working group of the International Surface Temperatures Initiative (ISTI-POST) dataset, which comprises our stations, as well as others from different countries in America, Asia and Europe.

Analysis of reverse gate leakage mechanism of AlGaN/GaN HEMTs with N2 plasma surface treatment

NASA Astrophysics Data System (ADS)

Liu, Hui; Zhang, Zongjing; Luo, Weijun

2018-06-01

The mechanism of reverse gate leakage current of AlGaN/GaN HEMTs with two different surface treatment methods are studied by using C-V, temperature dependent I-V and theoretical analysis. At the lower reverse bias region (VR >- 3.5 V), the dominant leakage current mechanism of the device with N2 plasma surface treatment is the Poole-Frenkel emission current (PF), and Trap-Assisted Tunneling current (TAT) is the principal leakage current of the device which treated by HCl:H2O solution. At the higher reverse bias region (VR <- 3.5 V), both of the two samples show good agreement with the surface leakage mechanism. The leakage current of the device with N2 plasma surface treatment is one order of magnitude smaller than the device which treated by HCl:H2O solution. This is due to the recovery of Ga-N bond in N2 plasma surface treatment together with the reduction of the shallow traps in post-gate annealing (PGA) process. The measured results agree well with the theoretical calculations and demonstrate N2 plasma surface treatment can reduce the reverse leakage current of the AlGaN/GaN HEMTs.

Validation of Infrared Azimuthal Model as Applied to GOES Data Over the ARM SGP

NASA Technical Reports Server (NTRS)

Gambheer, Arvind V.; Doelling, David R.; Spangenberg, Douglas A.; Minnis, Patrick

2004-01-01

The goal of this research is to identify and reduce the GOES-8 IR temperature biases, induced by a fixed geostationary position, during the course of a day. In this study, the same CERES LW window channel model is applied to GOES-8 IR temperatures during clear days over the Atmospheric Radiation Measurement-Southern Great Plains Central Facility (SCF). The model-adjusted and observed IR temperatures are compared with topof- the-atmosphere (TOA) estimated temperatures derived from a radiative transfer algorithm based on the atmospheric profile and surface radiometer measurements. This algorithm can then be incorporated to derive more accurate Ts from real-time satellite operational products.

Assessment of clear sky radiative fluxes in CMIP5 climate models using surface observations from BSRN

NASA Astrophysics Data System (ADS)

Wild, M.; Hakuba, M. Z.; Folini, D.; Ott, P.; Long, C. N.

2017-12-01

Clear sky fluxes in the latest generation of Global Climate Models (GCM) from CMIP5 still vary largely particularly at the Earth's surface, covering in their global means a range of 16 and 24 Wm-2 in the surface downward clear sky shortwave (SW) and longwave radiation, respectively. We assess these fluxes with monthly clear sky reference climatologies derived from more than 40 Baseline Surface Radiation Network (BSRN) sites based on Long and Ackermann (2000) and Hakuba et al. (2015). The comparison is complicated by the fact that the monthly SW clear sky BSRN reference climatologies are inferred from measurements under true cloud-free conditions, whereas the GCM clear sky fluxes are calculated continuously at every timestep solely by removing the clouds, yet otherwise keeping the prevailing atmospheric composition (e.g. water vapor, temperature, aerosols) during the cloudy conditions. This induces the risk of biases in the GCMs just due to the additional sampling of clear sky fluxes calculated under atmospheric conditions representative for cloudy situations. Thereby, a wet bias may be expected in the GCMs compared to the observational references, which may induce spurious low biases in the downward clear sky SW fluxes. To estimate the magnitude of these spurious biases in the available monthly mean fields from 40 CMIP5 models, we used their respective multi-century control runs, and searched therein for each month and each BSRN station the month with the lowest cloud cover. The deviations of the clear sky fluxes in this month from their long-term means have then be used as indicators of the magnitude of the abovementioned sampling biases and as correction factors for an appropriate comparison with the BSRN climatologies, individually applied for each model and BSRN site. The overall correction is on the order of 2 Wm-2. This revises our best estimate for the global mean surface downward SW clear sky radiation, previously at 249 Wm-2 infered from the GCM clear sky flux fields and their biases compared to the BSRN climatologies, now to 247 Wm-2 including this additional correction. 34 out of 40 CMIP5 GCMs exceed this reference value. With a global mean surface albedo of 13 % and net TOA SW clear sky flux of 287 Wm-2 from CERES-EBAF this results in a global mean clear sky surface and atmospheric SW absorption of 214 and 73 Wm-2, respectively.

Temperature dependence of exchange bias in (NiFe/IrMn)n multilayer films studied through static and dynamic techniques

NASA Astrophysics Data System (ADS)

Adams, Daniel J.; Khanal, Shankar; Khan, Mohammad Asif; Maksymov, Artur; Spinu, Leonard

2018-05-01

The in-plane temperature dependence of exchange bias was studied through both dc magnetometry and ferromagnetic resonance spectroscopy in a series of [NiFe/IrMn]n multilayer films, where n is the number of layer repetitions. Major hysteresis loops were recorded in the temperature range of 300 K to 2 K to reveal the effect of temperature on the exchange bias in the static regime while temperature-dependent continuous-wave ferromagnetic resonance for frequencies from 3 to 16 GHz was used to determine the exchange bias dynamically. Strong divergence between the values of exchange bias determined using the two different types of measurements as well as a peak in temperature dependence of the resonance linewidth were observed. These results are explained in terms of the slow-relaxer mechanism.

Simulation of the present-day climate with the climate model INMCM5

NASA Astrophysics Data System (ADS)

Volodin, E. M.; Mortikov, E. V.; Kostrykin, S. V.; Galin, V. Ya.; Lykossov, V. N.; Gritsun, A. S.; Diansky, N. A.; Gusev, A. V.; Iakovlev, N. G.

2017-12-01

In this paper we present the fifth generation of the INMCM climate model that is being developed at the Institute of Numerical Mathematics of the Russian Academy of Sciences (INMCM5). The most important changes with respect to the previous version (INMCM4) were made in the atmospheric component of the model. Its vertical resolution was increased to resolve the upper stratosphere and the lower mesosphere. A more sophisticated parameterization of condensation and cloudiness formation was introduced as well. An aerosol module was incorporated into the model. The upgraded oceanic component has a modified dynamical core optimized for better implementation on parallel computers and has two times higher resolution in both horizontal directions. Analysis of the present-day climatology of the INMCM5 (based on the data of historical run for 1979-2005) shows moderate improvements in reproduction of basic circulation characteristics with respect to the previous version. Biases in the near-surface temperature and precipitation are slightly reduced compared with INMCM4 as well as biases in oceanic temperature, salinity and sea surface height. The most notable improvement over INMCM4 is the capability of the new model to reproduce the equatorial stratospheric quasi-biannual oscillation and statistics of sudden stratospheric warmings.

Modulation of Soil Initial State on WRF Model Performance Over China

NASA Astrophysics Data System (ADS)

Xue, Haile; Jin, Qinjian; Yi, Bingqi; Mullendore, Gretchen L.; Zheng, Xiaohui; Jin, Hongchun

2017-11-01

The soil state (e.g., temperature and moisture) in a mesoscale numerical prediction model is typically initialized by reanalysis or analysis data that may be subject to large bias. Such bias may lead to unrealistic land-atmosphere interactions. This study shows that the Climate Forecast System Reanalysis (CFSR) dramatically underestimates soil temperature and overestimates soil moisture over most parts of China in the first (0-10 cm) and second (10-25 cm) soil layers compared to in situ observations in July 2013. A correction based on the global optimal dual kriging is employed to correct CFSR bias in soil temperature and moisture using in situ observations. To investigate the impacts of the corrected soil state on model forecasts, two numerical model simulations—a control run with CFSR soil state and a disturbed run with the corrected soil state—were conducted using the Weather Research and Forecasting model. All the simulations are initiated 4 times per day and run 48 h. Model results show that the corrected soil state, for example, warmer and drier surface over the most parts of China, can enhance evaporation over wet regions, which changes the overlying atmospheric temperature and moisture. The changes of the lifting condensation level, level of free convection, and water transport due to corrected soil state favor precipitation over wet regions, while prohibiting precipitation over dry regions. Moreover, diagnoses indicate that the remote moisture flux convergence plays a dominant role in the precipitation changes over the wet regions.

Evaluation of the Community Multiscale Air Quality Model for Simulating Winter Ozone Formation in the Uinta Basin

NASA Astrophysics Data System (ADS)

Matichuk, Rebecca; Tonnesen, Gail; Luecken, Deborah; Gilliam, Rob; Napelenok, Sergey L.; Baker, Kirk R.; Schwede, Donna; Murphy, Ben; Helmig, Detlev; Lyman, Seth N.; Roselle, Shawn

2017-12-01

The Weather Research and Forecasting (WRF) and Community Multiscale Air Quality (CMAQ) models were used to simulate a 10 day high-ozone episode observed during the 2013 Uinta Basin Winter Ozone Study (UBWOS). The baseline model had a large negative bias when compared to ozone (O3) and volatile organic compound (VOC) measurements across the basin. Contrary to other wintertime Uinta Basin studies, predicted nitrogen oxides (NOx) were typically low compared to measurements. Increases to oil and gas VOC emissions resulted in O3 predictions closer to observations, and nighttime O3 improved when reducing the deposition velocity for all chemical species. Vertical structures of these pollutants were similar to observations on multiple days. However, the predicted surface layer VOC mixing ratios were generally found to be underestimated during the day and overestimated at night. While temperature profiles compared well to observations, WRF was found to have a warm temperature bias and too low nighttime mixing heights. Analyses of more realistic snow heat capacity in WRF to account for the warm bias and vertical mixing resulted in improved temperature profiles, although the improved temperature profiles seldom resulted in improved O3 profiles. While additional work is needed to investigate meteorological impacts, results suggest that the uncertainty in the oil and gas emissions contributes more to the underestimation of O3. Further, model adjustments based on a single site may not be suitable across all sites within the basin.

Land-Atmosphere Coupling in the Multi-Scale Modelling Framework

NASA Astrophysics Data System (ADS)

Kraus, P. M.; Denning, S.

2015-12-01

The Multi-Scale Modeling Framework (MMF), in which cloud-resolving models (CRMs) are embedded within general circulation model (GCM) gridcells to serve as the model's cloud parameterization, has offered a number of benefits to GCM simulations. The coupling of these cloud-resolving models directly to land surface model instances, rather than passing averaged atmospheric variables to a single instance of a land surface model, the logical next step in model development, has recently been accomplished. This new configuration offers conspicuous improvements to estimates of precipitation and canopy through-fall, but overall the model exhibits warm surface temperature biases and low productivity.This work presents modifications to a land-surface model that take advantage of the new multi-scale modeling framework, and accommodate the change in spatial scale from a typical GCM range of ~200 km to the CRM grid-scale of 4 km.A parameterization is introduced to apportion modeled surface radiation into direct-beam and diffuse components. The diffuse component is then distributed among the land-surface model instances within each GCM cell domain. This substantially reduces the number excessively low light values provided to the land-surface model when cloudy conditions are modeled in the CRM, associated with its 1-D radiation scheme. The small spatial scale of the CRM, ~4 km, as compared with the typical ~200 km GCM scale, provides much more realistic estimates of precipitation intensity, this permits the elimination of a model parameterization of canopy through-fall. However, runoff at such scales can no longer be considered as an immediate flow to the ocean. Allowing sub-surface water flow between land-surface instances within the GCM domain affords better realism and also reduces temperature and productivity biases.The MMF affords a number of opportunities to land-surface modelers, providing both the advantages of direct simulation at the 4 km scale and a much reduced conceptual gap between model resolution and parameterized processes.

Towards Removing the Southern Ocean Short Wave Bias in HadGEM3: Mixed-phase Cloud Improvements.

NASA Astrophysics Data System (ADS)

Field, P.; Furtado, K.

2014-12-01

Many IPCC models suffer from significant Sea Surface Temperature (SST) biases in the Southern Ocean that adversely affects the representation of the cryosphere and global circulation in these models. Evidence suggests that much of this error is linked to Short Wave (SW) radiation, sensible and latent heat biases. Flaws in the representation of clouds and a deficit of supercooled liquid water in mixed-phase clouds are suspected as a likely source of the SW error. A physically based method that uses subgrid turbulence to control a new liquid production term has been developed. Comparisons between theory, based on a stochastic differential equation used to represent supersaturation fluctuations, and decametre resolution Large Eddy Simulations will be presented. An implementation of this approach in a GCM shows an increased prevalance of supercooled liquid water and a reduction in the magnitude of the Southern Ocean SW bias. To conclude, we will summarize the complete package of changes that have been made to tackle the Southern Ocean SST bias in a physically meaningful way.

Three-dimensional spin mapping of antiferromagnetic nanopyramids having spatially alternating surface anisotropy at room temperature.

PubMed

Wang, Kangkang; Smith, Arthur R

2012-11-14

Antiferromagnets play a key role in modern spintronic devices owing to their ability to modify the switching behavior of adjacent ferromagnets via the exchange bias effect. Consequently, detailed measurements of the spin structure at antiferromagnetic interfaces and surfaces are highly desirable, not only for advancing technologies but also for enabling new insights into the underlying physics. Here using spin-polarized scanning tunneling microscopy at room-temperature, we reveal in three-dimensions an orthogonal spin structure on antiferromagnetic compound nanopyramids. Contrary to expected uniaxial anisotropy based on bulk properties, the atomic terraces are found to have alternating in-plane and out-of-plane magnetic anisotropies. The observed layer-wise alternation in anisotropy could have strong influences on future nanoscale spintronic applications.

Sources of Uncertainty and the Interpretation of Short-Term Fluctuations

NASA Astrophysics Data System (ADS)

Lewandowsky, S.; Risbey, J.; Cowtan, K.; Rahmstorf, S.

2016-12-01

The alleged significant slowdown in global warming during the first decade of the 21st century, and the appearance of a discrepancy between models and observations, has attracted considerable research attention. We trace the history of this research and show how its conclusions were shaped by several sources of uncertainty and ambiguity about models and observations. We show that as those sources of uncertainty were gradually eliminated by further research, insufficient evidence remained to infer any discrepancy between models and observations or a significant slowing of warming. Specifically, we show that early research had to contend with uncertainties about coverage biases in the global temperature record and biases in the sea surface temperature observations which turned out to have exaggerated the extent of slowing. In addition, uncertainties in the observed forcings were found to have exaggerated the mismatch between models and observations. Further sources of uncertainty that were ultimately eliminated involved the use of incommensurate sea surface temperature data between models and observations and a tacit interpretation of model projections as predictions or forecasts. After all those sources of uncertainty were eliminated, the most recent research finds little evidence for an unusual slowdown or a discrepancy between models and observations. We discuss whether these different kinds of uncertainty could have been anticipated or managed differently, and how one can apply those lessons to future short-term fluctuations in warming.

CuInP 2S 6 Room Temperature Layered Ferroelectric

DOE PAGES

Belianinov, Alex; He, Qian; Dziaugys, Andrius; ...

2015-05-01

In this paper, we explore ferroelectric properties of cleaved 2-D flakes of copper indium thiophosphate, CuInP 2S 6 (CITP), and probe size effects along with limits of ferroelectric phase stability, by ambient and ultra high vacuum scanning probe microscopy. CITP belongs to the only material family known to display ferroelectric polarization in a van der Waals, layered crystal at room temperature and above. Our measurements directly reveal stable, ferroelectric polarization as evidenced by domain structures, switchable polarization, and hysteresis loops. We found that at room temperature the domain structure of flakes thicker than 100 nm is similar to the cleavedmore » bulk surfaces, whereas below 50 nm polarization disappears. We ascribe this behavior to a well-known instability of polarization due to depolarization field. Furthermore, polarization switching at high bias is also associated with ionic mobility, as evidenced both by macroscopic measurements and by formation of surface damage under the tip at a bias of 4 V—likely due to copper reduction. Mobile Cu ions may therefore also contribute to internal screening mechanisms. Finally, the existence of stable polarization in a van-der-Waals crystal naturally points toward new strategies for ultimate scaling of polar materials, quasi-2D, and single-layer materials with advanced and nonlinear dielectric properties that are presently not found in any members of the growing “graphene family”.« less

Assessing the quality of humidity measurements from global operational radiosonde sensors

NASA Astrophysics Data System (ADS)

Moradi, Isaac; Soden, Brian; Ferraro, Ralph; Arkin, Phillip; Vömel, Holger

2013-07-01

The quality of humidity measurements from global operational radiosonde sensors in upper, middle, and lower troposphere for the period 2000-2011 were investigated using satellite observations from three microwave water vapor channels operating at 183.31±1, 183.31±3, and 183.31±7 GHz. The radiosonde data were partitioned based on sensor type into 19 classes. The satellite brightness temperatures (Tb) were simulated using radiosonde profiles and a radiative transfer model, then the radiosonde simulated Tb's were compared with the observed Tb's from the satellites. The surface affected Tb's were excluded from the comparison due to the lack of reliable surface emissivity data at the microwave frequencies. Daytime and nighttime data were examined separately to see the possible effect of daytime radiation bias on the sonde data. The error characteristics among different radiosondes vary significantly, which largely reflects the differences in sensor type. These differences are more evident in the mid-upper troposphere than in the lower troposphere, mainly because some of the sensors stop responding to tropospheric humidity somewhere in the upper or even in the middle troposphere. In the upper troposphere, most sensors have a dry bias but Russian sensors and a few other sensors including GZZ2, VZB2, and RS80H have a wet bias. In middle troposphere, Russian sensors still have a wet bias but all other sensors have a dry bias. All sensors, including Russian sensors, have a dry bias in lower troposphere. The systematic and random errors generally decrease from upper to lower troposphere. Sensors from China, India, Russia, and the U.S. have a large random error in upper troposphere, which indicates that these sensors are not suitable for upper tropospheric studies as they fail to respond to humidity changes in the upper and even middle troposphere. Overall, Vaisala sensors perform better than other sensors throughout the troposphere exhibiting the smallest systematic and random errors. Because of the large differences between different radiosonde humidity sensors, it is important for long-term trend studies to only use data measured using a single type of sensor at any given station. If multiple sensor types are used then it is necessary to consider the bias between sensor types and its possible dependence on humidity and temperature.

Variability in Bias of Gridded Sea Surface Temperature Data Products: Implications for Seasonally Resolved Marine Proxy Reconstructions

NASA Astrophysics Data System (ADS)

Ouellette, G., Jr.; DeLong, K. L.

2016-12-01

Seasonally resolved reconstructions of sea surface temperature (SST) are commonly produced using isotopic ratios and trace elemental ratios within the skeletal material of marine organisms such as corals, coralline algae, and mollusks. Using these geochemical proxies to produce paleoclimate reconstructions requires using regression methods to calibrate the proxy to observed SST, ideally with in situ SST records that span many years. Unfortunately, the few locations with in situ SST records rarely coincide with the time span of the marine proxy archive. Therefore, SST data products are often used for calibration and they are based on MOHSST or ICOADS SST observations as their main SST source but use different algorithms to produce globally gridded data products. These products include the Hadley Center's HADSST (5º) and interpolated HADISST (1º), NOAA's extended reconstructed SST (ERSST; 2º), optimum interpolation SST (OISST; 1º), and the Kaplan SST (5º). This study assessed the potential bias in these data products at marine archive sites throughout the tropical Atlantic using in situ SST where it was available, and a high-resolution (4 km) satellite-based SST data product from NOAA Pathfinder that has been shown to closely reflect in situ SST for our locations. Bias was assessed at each site, and then within each data product across the region for spatial homogeneity. Our results reveal seasonal biases in all data products, but not for all locations and not of a uniform magnitude or season among products. We found the largest differences in mean SST on the order of 1-3°C for single sites in the Gulf of Mexico, and differences for regional mean SST bias were 0.5-1°C when sites in the Gulf of Mexico were compared to sites in the Caribbean Sea within the same data product. No one SST data product outperformed the others and no systematic bias was found. This analysis illustrates regional strengths and weaknesses of these data products, and serves as a cautionary note against the wholesale use of a particular gridded data product for marine proxy calibration, whether for a single site or larger regional reconstruction, without considering the inherent heterogeneous bias present in each data product that we show varies among locations. Furthermore, this study has implications for comparing climate models and these SST data products.

The Impact of Sea Ice Concentration Accuracies on Climate Model Simulations with the GISS GCM

NASA Technical Reports Server (NTRS)

Parkinson, Claire L.; Rind, David; Healy, Richard J.; Martinson, Douglas G.; Zukor, Dorothy J. (Technical Monitor)

2000-01-01

The Goddard Institute for Space Studies global climate model (GISS GCM) is used to examine the sensitivity of the simulated climate to sea ice concentration specifications in the type of simulation done in the Atmospheric Modeling Intercomparison Project (AMIP), with specified oceanic boundary conditions. Results show that sea ice concentration uncertainties of +/- 7% can affect simulated regional temperatures by more than 6 C, and biases in sea ice concentrations of +7% and -7% alter simulated annually averaged global surface air temperatures by -0.10 C and +0.17 C, respectively, over those in the control simulation. The resulting 0.27 C difference in simulated annual global surface air temperatures is reduced by a third, to 0.18 C, when considering instead biases of +4% and -4%. More broadly, least-squares fits through the temperature results of 17 simulations with ice concentration input changes ranging from increases of 50% versus the control simulation to decreases of 50% yield a yearly average global impact of 0.0107 C warming for every 1% ice concentration decrease, i.e., 1.07 C warming for the full +50% to -50% range. Regionally and on a monthly average basis, the differences can be far greater, especially in the polar regions, where wintertime contrasts between the +50% and -50% cases can exceed 30 C. However, few statistically significant effects are found outside the polar latitudes, and temperature effects over the non-polar oceans tend to be under 1 C, due in part to the specification of an unvarying annual cycle of sea surface temperatures. The +/- 7% and 14% results provide bounds on the impact (on GISS GCM simulations making use of satellite data) of satellite-derived ice concentration inaccuracies, +/- 7% being the current estimated average accuracy of satellite retrievals and +/- 4% being the anticipated improved average accuracy for upcoming satellite instruments. Results show that the impact on simulated temperatures of imposed ice concentration changes is least in summer, encouragingly the same season in which the satellite accuracies are thought to be worst. Hence the impact of satellite inaccuracies is probably less than the use of an annually averaged satellite inaccuracy would suggest.

Comparison of CERES-MODIS stratus cloud properties with ground-based measurements at the DOE ARM Southern Great Plains site

NASA Astrophysics Data System (ADS)

Dong, Xiquan; Minnis, Patrick; Xi, Baike; Sun-Mack, Sunny; Chen, Yan

2008-02-01

Overcast stratus cloud properties derived for the Clouds and the Earth's Radiant Energy System (CERES) project using Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) data are compared with observations taken at the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Southern Great Plains site from March 2000 through December 2004. Retrievals from ARM surface-based data were averaged over a 1-h interval centered at the time of each satellite overpass, and the CERES-MODIS cloud properties were averaged within a 30 km × 30 km box centered on the ARM SGP site. Two data sets were analyzed: all of the data (ALL), which include multilayered, single-layered, and slightly broken stratus decks and a subset, single-layered unbroken decks (SL). The CERES-MODIS effective cloud heights were determined from effective cloud temperature using a lapse rate method with the surface temperature specified as the 24-h mean surface air temperature. For SL stratus, they are, on average, within the ARM radar-lidar estimated cloud boundaries and are 0.534 ± 0.542 km and 0.108 ± 0.480 km lower than the cloud physical tops and centers, respectively, and are comparable for day and night observations. The mean differences and standard deviations are slightly larger for ALL data, but not statistically different to those of SL data. The MODIS-derived effective cloud temperatures are 2.7 ± 2.4 K less than the surface-observed SL cloud center temperatures with very high correlations (0.86-0.97). Variations in the height differences are mainly caused by uncertainties in the surface air temperatures, lapse rates, and cloud top height variability. The biases are mainly the result of the differences between effective and physical cloud top, which are governed by cloud liquid water content and viewing zenith angle, and the selected lapse rate, -7.1 K km-1. On the basis of a total of 43 samples, the means and standard deviations of the differences between the daytime Terra and surface retrievals of effective radius re, optical depth, and liquid water path for SL stratus are 0.1 ± 1.9 μm (1.2 ± 23.5%), -1.3 ± 9.5 (-3.6 ± 26.2%), and 0.6 ± 49.9 gm-2 (0.3 ± 27%), respectively, while the corresponding correlation coefficients are 0.44, 0.87, and 0.89. For Aqua, they are 0.2 ± 1.9 μm (2.5 ± 23.4%), 2.5 ± 7.8 (7.8 ± 24.3%), and 28.1 ± 52.7 gm-2 (17.2 ± 32.2%), as well as 0.35, 0.96, and 0.93 from a total of 21 cases. The results for ALL cases are comparable. Although a bias in re was expected because the satellite retrieval of effective radius only represents the top of the cloud, the surface-based radar retrievals revealed that the vertical profile of re is highly variable with smaller droplets occurring at cloud top in some cases. The larger bias in optical depth and liquid water path for Aqua is due, at least partially, to differences in the Terra and Aqua MODIS visible channel calibrations. Methods for improving the cloud top height and microphysical property retrievals are suggested.

Comparison of CERES-MODIS Stratus Cloud Properties with Ground-Based Measurements at the DOE ARM Southern Great Plains Site

NASA Technical Reports Server (NTRS)

Dong, Xiquan; Minnis Patrick; Xi, Baike; Sun-Mack, Sunny; Chen, Yan

2008-01-01

Overcast stratus cloud properties derived for the Clouds and the Earth's Radiant Energy system (CERES) Project using Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) data are compared with observations taken at the Atmospheric Radiation Measurement (ARM) Southern Great Plains site from March 2000 through December 2004. Retrievals from ARM surface-based data were averaged over a 1-hour interval centered at the time of each satellite overpass, and the CERES-MODIS cloud properties were averaged within a 30-km x 30 km box centered on the ARM SGP site. Two datasets were analyzed: all of the data (ALL) which include multilayered, single-layered, and slightly broken stratus decks and a subset, single-layered unbroken decks (SL). The CERES-MODIS effective cloud heights were determined from effective cloud temperature using a lapse rate method with the surface temperature specified as the 24-h mean surface air temperature. For SL stratus, they are, on average, within the ARM radar-lidar estimated cloud boundaries and are 0.534 +/- 0.542 km and 0.108 +/- 0.480 km lower than the cloud physical tops and centers, respectively, and are comparable for day and night observations. The mean differences and standard deviations are slightly larger for ALL data, but not statistically different to those of SL data. The MODIS-derived effective cloud temperatures are 2.7 +/- 2.4 K less than the surface-observed SL cloud center temperatures with very high correlations (0.86-0.97). Variations in the height differences are mainly caused by uncertainties in the surface air temperatures, lapse rates, and cloud-top height variability. The biases are mainly the result of the differences between effective and physical cloud top, which are governed by cloud liquid water content and viewing zenith angle, and the selected lapse rate, -7.1 K km(exp -1). Based on a total of 43 samples, the means and standard deviations of the differences between the daytime Terra and surface retrievals of effective radius r(sub e), optical depth, and liquid water path for SL stratu are 0.1 +/- 1.9 micrometers (1.2 +/- 23.5%), -1.3 +/- 9.5 (-3.6 +/-26.2%), and 0.6 +/- 49.9 gm (exp -2) (0.3 +/- 27%), respectively, while the corresponding correlation coefficients are 0.44, 0.87, and 0.89. For Aqua, they are 0.2 +/- 1.9 micrometers (2.5 +/- 23.4%), 2.5 +/- 7.8 (7.8 +/- 24.3%), and 28.1 +/- 52.7 gm (exp -2) (17.2 +/- 32.2%), as well as 0.35, 0.96, and 0.93 from a total of 21 cases. The results for ALL cases are comparable. Although a bias in R(sub e) was expected because the satellite retrieval of effective radius only represents the top of the cloud, the surface-based radar retrievals revealed that the vertical profile of r(sub e) is highly variable with smaller droplets occurring at cloud top in some cases. The larger bias in optical depth and liquid water path for Aqua is due, at least partially, to differences in the Terra and Aqua MODIS visible channel calibrations. methods for improving the cloud-top height and microphysical property retrievals are suggested.

Seasonally Distinct Reconstructions of Northern Alaskan Temperature Variability Since the Last Glacial Maximum

NASA Astrophysics Data System (ADS)

Longo, W. M.; Crowther, J.; Daniels, W.; Russell, J. M.; Giblin, A. E.; Morrill, C.; Zhang, X.; Wang, X.; Huang, Y.

2015-12-01

Paleoclimate reconstructions have provided little consensus on how continental temperatures in Eastern Beringia changed from the Last Glacial Maximum (LGM) to the present. Reconstructions show regional differences in LGM severity, the timing of deglacial warming, and Holocene temperature variability. Currently, arctic temperatures are increasing at the fastest rates on the planet, highlighting the need to identify the sensitivities of arctic systems to various climate forcings. This cannot be done without resolving the complex climate history of Eastern Beringia. Here, we present two new organic geochemical temperature reconstructions from Lake E5, north central Alaska that span the LGM, last glacial termination and Holocene. The proxies (alkenones and brGDGTs) record seasonally distinct temperatures, allowing for the attribution of different forcings to each proxy. The alkenone-based UK37 reconstruction records spring/early summer lake temperatures and indicates a 4 oC abrupt warming at 13.1 ka and a relatively warm late Holocene, which peaks at 2.4 ka and exhibits a cooling trend from 2.4 to 0.1 ka. The brGDGT reconstruction is calibrated to mean annual air temperature and interpreted here as exhibiting a strong warm season bias. BrGDGTs show an abrupt 4.5 oC warming at 14 ka, and show evidence for an early Holocene Thermal Maximum (HTM), which cools by 3 oC after 8.4 ka. Because UK37 temperatures do not exhibit an early HTM, we hypothesize that summer insolation had a minimal effect on spring/early summer lake temperatures. Instead, the UK37 reconstruction agrees with sea ice and sea surface temperature reconstructions from the Beaufort and Chukchi Seas and northeast Pacific Ocean. We hypothesize that forcings associated with sea ice concentration and changes in atmospheric circulation had stronger affects on spring/early summer lake temperatures and we present modern observational data in support of this hypothesis. By contrast, the summer-biased brGDGT reconstruction suggests a strong and relatively direct temperature response to summer insolation forcing. Together, these records suggest that both internal and external forcings significantly affected LGM to present temperature variability in Eastern Beringia, with different seasonal biases.

Drag coefficient Variability and Thermospheric models

NASA Astrophysics Data System (ADS)

Moe, Kenneth

Satellite drag coefficients depend upon a variety of factors: The shape of the satellite, its altitude, the eccentricity of its orbit, the temperature and mean molecular mass of the ambient atmosphere, and the time in the sunspot cycle. At altitudes where the mean free path of the atmospheric molecules is large compared to the dimensions of the satellite, the drag coefficients can be determined from the theory of free-molecule flow. The dependence on altitude is caused by the concentration of atomic oxygen which plays an important role by its ability to adsorb on the satellite surface and thereby affect the energy loss of molecules striking the surface. The eccentricity of the orbit determines the satellite velocity at perigee, and therefore the energy of the incident molecules relative to the energy of adsorption of atomic oxygen atoms on the surface. The temperature of the ambient atmosphere determines the extent to which the random thermal motion of the molecules influences the momentum transfer to the satellite. The time in the sunspot cycle affects the ambient temperature as well as the concentration of atomic oxygen at a particular altitude. Tables and graphs will be used to illustrate the variability of drag coefficients. Before there were any measurements of gas-surface interactions in orbit, Izakov and Cook independently made an excellent estimate that the drag coefficient of satellites of compact shape would be 2.2. That numerical value, independent of altitude, was used by Jacchia to construct his model from the early measurements of satellite drag. Consequently, there is an altitude dependent bias in the model. From the sparce orbital experiments that have been done, we know that the molecules which strike satellite surfaces rebound in a diffuse angular distribution with an energy loss given by the energy accommodation coefficient. As more evidence accumulates on the energy loss, more realistic drag coefficients are being calculated. These improved drag coefficients help evaluate the biases in present models. Moreover, they make possible the derivation of accurate densities from accelerometer measurements.

Global Land Surface Temperature From the Along-Track Scanning Radiometers

NASA Astrophysics Data System (ADS)

Ghent, D. J.; Corlett, G. K.; Göttsche, F.-M.; Remedios, J. J.

2017-11-01

The Leicester Along-Track Scanning Radiometer (ATSR) and Sea and Land Surface Temperature Radiometer (SLSTR) Processor for LAnd Surface Temperature (LASPLAST) provides global land surface temperature (LST) products from thermal infrared radiance data. In this paper, the state-of-the-art version of LASPLAST, as deployed in the GlobTemperature project, is described and applied to data from the Advanced Along-Track Scanning Radiometer (AATSR). The LASPLAST retrieval formulation for LST is a nadir-only, two-channel, split-window algorithm, based on biome classification, fractional vegetation, and across-track water vapor dependences. It incorporates globally robust retrieval coefficients derived using highly sampled atmosphere profiles. LASPLAST benefits from appropriate spatial resolution auxiliary information and a new probabilistic-based cloud flagging algorithm. For the first time for a satellite-derived LST product, pixel-level uncertainties characterized in terms of random, locally correlated, and systematic components are provided. The new GlobTemperature GT_ATS_2P Version 1.0 product has been validated for 1 year of AATSR data (2009) against in situ measurements acquired from "gold standard reference" stations: Gobabeb, Namibia, and Evora, Portugal; seven Surface Radiation Budget stations, and the Atmospheric Radiation Measurement station at Southern Great Plains. These data show average absolute biases for the GT_ATS_2P Version 1.0 product of 1.00 K in the daytime and 1.08 K in the nighttime. The improvements in data provenance including better accuracy, fully traceable retrieval coefficients, quantified uncertainty, and more detailed information in the new harmonized format of the GT_ATS_2P product will allow for more significant exploitation of the historical LST data record from the ATSRs and a valuable near-real-time service from the Sea and Land Surface Temperature Radiometers (SLSTRs).

Leveraging Oceanic and Surface Intensive Field Campaign Data Sets for Validation and Improvement of Recent Hyperspectral IR Satellite Data Products

NASA Astrophysics Data System (ADS)

Joseph, E.; Nalli, N. R.; Oyola, M. I.; Morris, V. R.; Sakai, R.

2014-12-01

An overview is given of research to validate or improve the retrieval of environmental data records (EDRs) from recently deployed hyperspectral IR satellite sensors such as Suomi NPP Cross-track Infrared Microwave Sounder Suite (CrIMSS). The effort centers around several surface field intensive campaigns that are designed or leveraged for EDR validation. These data include ship-based observations of upper air ozone, pressure, temperature and relative humidity soundings; aerosol and cloud properties; and sea surface temperature. Similar intensive data from two land-based sites are also utilized as well. One site, the Howard University Beltsville site, is at a single point location but has a comprehensive array of observations for an extended period of time. The other land site, presently being deployed by the University at Albany, is under development with limited upper air soundings but will have regionally distributed surface based microwave profiling of temperature and relative humidity on the scale of 10 - 50 km and other standard meteorological observations. Combined these observations provide data that are unique in their wide range including, a variety of meteorological conditions and atmospheric compositions over the ocean and urban-suburban environments. With the distributed surface sites the variability of atmospheric conditions are captured concurrently across a regional spatial scale. Some specific examples are given of comparisons of moisture and temperature correlative EDRs from the satellite sensors and surface based observations. An additional example is given of the use of this data to correct sea surface temperature (SST) retrieval biases from the hyperspectral IR satellite observations due to aerosol contamination.

Day-night variation in operationally retrieved TOVS temperature biases

NASA Technical Reports Server (NTRS)

Kidder, Stanley Q.; Achtemeier, Gary L.

1986-01-01

Several authors have reported that operationally retrieved TOVS (TIROS Operational Vertical Sounder) temperatures are biased with respect to rawinsonde temperatures or temperature analyses. This note reports a case study from which it is concluded that, at least for the time period Mar. 26 through Apr. 8, 1979, there was a significant day-night variation in TOVS mean layer virtual temperature biases with respect to objective analyses of rawinsonde data over the U.S.

Potential Nighttime Contamination of CERES Clear-sky Field of View by Optically Thin Cirrus during the CRYSTAL-FACE Campaign

NASA Technical Reports Server (NTRS)

Lee, Yong-Keun; Yang, Ping; Hu, Yongxiang; Baum, Bryan A.; Loeb, Norman G.; Gao, Bo-Cai

2006-01-01

We investigate the outgoing broadband longwave (LW, 5 to approx. 200 microns) and window (WIN, 8 to approx. 12 microns) channel radiances at the top of atmosphere (TOA) under clear-sky conditions, using data acquired by the Cloud and the Earth s Radiant Energy System (CERES) and Moderate-Resolution Imaging Spectroradiometer (MODIS) instruments onboard the NASA Terra satellite platform. In this study, detailed analyses are performed on the CERES Single Scanner Footprint TOA/Surface Fluxes and Clouds product to understand the radiative effect of thin cirrus. The data are acquired over the Florida area during the Cirrus Regional Study of Tropical Anvils and Cirrus Layers Florida Area Cirrus Experiment (CRYSTAL-FACE) field program. Of particular interest is the anisotropy associated with the radiation field. Measured CERES broadband radiances are compared to those obtained from rigorous radiative transfer simulations. Analysis of results from this comparison indicates that the simulated radiances tend to be larger than their measured counterparts, with differences ranging from 2.1% to 8.3% for the LW band and from 1.7% to 10.6% for the WIN band. The averaged difference in radiance is approximately 4% for both the LW and WIN channels. A potential cause for the differences could be the presence of thin cirrus (i.e., optically thin ice clouds with visible optical thicknesses smaller than approximately 0.3). The detection and quantitative analysis of these thin cirrus clouds are challenging even with sophisticated multispectral instruments. While large differences in radiance between the CERES observations and the theoretical calculations are found, the corresponding difference in the anisotropic factors is very small (0.2%). Furthermore, sensitivity studies show that the influence due to a 1 K bias of the surface temperature on the errors of the LW and WIN channel radiances is of the same order as that associated with a 2% bias of the surface emissivity. The LW and WIN errors associated with a 5% bias of water vapor amount in the lower atmosphere in conjunction with a 50% bias of water vapor amount in the upper atmosphere is similar to that of a 1 K bias of the vertical temperature profile. Even with the uncertainties considered for these various factors, the simulated LW and WIN radiances are still larger than the observed radiances if thin cirrus clouds are excluded.

Experimental aspects of buoyancy correction in measuring reliable high-pressure excess adsorption isotherms using the gravimetric method

NASA Astrophysics Data System (ADS)

Nguyen, Huong Giang T.; Horn, Jarod C.; Thommes, Matthias; van Zee, Roger D.; Espinal, Laura

2017-12-01

Addressing reproducibility issues in adsorption measurements is critical to accelerating the path to discovery of new industrial adsorbents and to understanding adsorption processes. A National Institute of Standards and Technology Reference Material, RM 8852 (ammonium ZSM-5 zeolite), and two gravimetric instruments with asymmetric two-beam balances were used to measure high-pressure adsorption isotherms. This work demonstrates how common approaches to buoyancy correction, a key factor in obtaining the mass change due to surface excess gas uptake from the apparent mass change, can impact the adsorption isotherm data. Three different approaches to buoyancy correction were investigated and applied to the subcritical CO2 and supercritical N2 adsorption isotherms at 293 K. It was observed that measuring a collective volume for all balance components for the buoyancy correction (helium method) introduces an inherent bias in temperature partition when there is a temperature gradient (i.e. analysis temperature is not equal to instrument air bath temperature). We demonstrate that a blank subtraction is effective in mitigating the biases associated with temperature partitioning, instrument calibration, and the determined volumes of the balance components. In general, the manual and subtraction methods allow for better treatment of the temperature gradient during buoyancy correction. From the study, best practices specific to asymmetric two-beam balances and more general recommendations for measuring isotherms far from critical temperatures using gravimetric instruments are offered.

Experimental aspects of buoyancy correction in measuring reliable highpressure excess adsorption isotherms using the gravimetric method.

PubMed

Nguyen, Huong Giang T; Horn, Jarod C; Thommes, Matthias; van Zee, Roger D; Espinal, Laura

2017-12-01

Addressing reproducibility issues in adsorption measurements is critical to accelerating the path to discovery of new industrial adsorbents and to understanding adsorption processes. A National Institute of Standards and Technology Reference Material, RM 8852 (ammonium ZSM-5 zeolite), and two gravimetric instruments with asymmetric two-beam balances were used to measure high-pressure adsorption isotherms. This work demonstrates how common approaches to buoyancy correction, a key factor in obtaining the mass change due to surface excess gas uptake from the apparent mass change, can impact the adsorption isotherm data. Three different approaches to buoyancy correction were investigated and applied to the subcritical CO 2 and supercritical N 2 adsorption isotherms at 293 K. It was observed that measuring a collective volume for all balance components for the buoyancy correction (helium method) introduces an inherent bias in temperature partition when there is a temperature gradient (i.e. analysis temperature is not equal to instrument air bath temperature). We demonstrate that a blank subtraction is effective in mitigating the biases associated with temperature partitioning, instrument calibration, and the determined volumes of the balance components. In general, the manual and subtraction methods allow for better treatment of the temperature gradient during buoyancy correction. From the study, best practices specific to asymmetric two-beam balances and more general recommendations for measuring isotherms far from critical temperatures using gravimetric instruments are offered.

Linear servomotor probe drive system with real-time self-adaptive position control for the Alcator C-Mod tokamak

NASA Astrophysics Data System (ADS)

Brunner, D.; Kuang, A. Q.; LaBombard, B.; Burke, W.

2017-07-01

A new servomotor drive system has been developed for the horizontal reciprocating probe on the Alcator C-Mod tokamak. Real-time measurements of plasma temperature and density—through use of a mirror Langmuir probe bias system—combined with a commercial linear servomotor and controller enable self-adaptive position control. Probe surface temperature and its rate of change are computed in real time and used to control probe insertion depth. It is found that a universal trigger threshold can be defined in terms of these two parameters; if the probe is triggered to retract when crossing the trigger threshold, it will reach the same ultimate surface temperature, independent of velocity, acceleration, or scrape-off layer heat flux scale length. In addition to controlling the probe motion, the controller is used to monitor and control all aspects of the integrated probe drive system.

Microplasma Jet Synthesis of Ni-Fe Oxide Films for Magnetic Exchange Bias and Electrocatalytic Studies

NASA Astrophysics Data System (ADS)

Pebley, Andrew Christian

Ni-Fe oxides have received significant interest from the scientific community because they have attractive magnetic and electrochemical properties for use in next generation data storage and energy conversion technologies. For example, the NiFe2O4/NiO nanogranular system exhibits the exchange bias effect, a magnetic phenomenon occurring at the interface of a ferro- or ferrimagnet (FM or FiM) and an antiferromagnet (AFM), where the AFM acts to increase the magnetic hardness of the corresponding FM or FiM. Additionally, doping of NiO with Fe has resulted in remarkably high catalytic activities for water splitting, a potential clean energy alternative to fossil fuels. A key challenge in implementing these Ni-Fe oxides for magnetic and electrocatalytic applications is the ability to control film morphology, crystallinity, composition, chemical phase, and doping during synthesis. Moreover, how these physiochemical properties effect magnetic and electrochemical behavior in the Ni-Fe oxide system is not fully understood. This dissertation focuses on the development and use of a novel synthesis technique, known as microplasma (MP) jet-based deposition, for the fabrication of biphasic NiFe2O4 (FiM)/NiO (AFM) and Fe-doped NiO nanostructured films for fundamental studies of exchange bias and electrocatalysis, respectively. The goal of this work was to understand how MP operation and deposition conditions (e.g., precursor composition, flux, substrate temperature, and post-deposition heat treatment) influence Ni-Fe oxide growth and film microstructure. Specifically, the role of composition, phase fraction, grain size, temperature, and interfacial density on exchange bias phenomena in NiFe 2O4/NiO nanogranular films was investigated. MP jets were also used to realize metastable Fe-doped NiO films with high surface area to assess how doping affects the electrochemical properties of NiO for the oxygen evolution reaction (OER). Biphasic NiFe2O4/NiO films of different composition were synthesized using MP jets and post-deposition annealing. The exchange bias effect (HE) and enhanced coercivity (HC) were seen at 300 K, which was the first time that HE has been reported at room temperature in the NiFe2O4/NiO nanogranular system. These values increased with Ni incorporation, and were rationalized as due to increased NiFe2O4/NiO interfacial density. Moreover, MP jet deposition of NiFe2O4/NiO films on heated substrates was explored to realize higher interfacial densities. HE was observed at low temperatures in these films, but not at room temperature, which was attributed to spin glass coupling arising from structurally disordered interfaces. Through systematic post-deposition heat treatments, it was found that spin glass-like phases disappeared after annealing, and the observed HE was due to direct exchange coupling between the NiO and NiFe2O 4 phases. MP jets were also used to deposit high-surface area, metastable Fe-doped NiO films of different composition (up to 20% Fe on a metals basis) at room temperature on indium tin oxide (ITO) substrates for OER catalysis. It was seen that Fe fully incorporated into the NiO rocksalt lattice, decreasing the overpotential for OER (i.e., 360 to 310 mV at 10 mA/cm2 for NiO and Ni0.95Fe0.05O, respectively). Turnover frequency (TOF) calculations demonstrated an improvement in the catalytic activity of the NiO surface with Fe doping, and chronopotentiometry measurements verified that Fe-doped NiO films were mechanically and chemically robust during extended operation under OER conditions. Overall, this work demonstrates the potential of MP jet deposition as a versatile, one-step approach to realize multi-phase and doped nanostructured oxide films with high interfacial densities and surface areas for a variety of magnetic and energy conversion applications.

Using dry spell dynamics of land surface temperature to evaluate large-scale model representation of soil moisture control on evapotranspiration

NASA Astrophysics Data System (ADS)

Taylor, Christopher M.; Harris, Philip P.; Gallego-Elvira, Belen; Folwell, Sonja S.

2017-04-01

The soil moisture control on the partition of land surface fluxes between sensible and latent heat is a key aspect of land surface models used within numerical weather prediction and climate models. As soils dry out, evapotranspiration (ET) decreases, and the excess energy is used to warm the atmosphere. Poor simulations of this dynamic process can affect predictions of mean, and in particular, extreme air temperatures, and can introduce substantial biases into projections of climate change at regional scales. The lack of reliable observations of fluxes and root zone soil moisture at spatial scales that atmospheric models use (typically from 1 to several hundred kilometres), coupled with spatial variability in vegetation and soil properties, makes it difficult to evaluate the flux partitioning at the model grid box scale. To overcome this problem, we have developed techniques to use Land Surface Temperature (LST) to evaluate models. As soils dry out, LST rises, so it can be used under certain circumstances as a proxy for the partition between sensible and latent heat. Moreover, long time series of reliable LST observations under clear skies are available globally at resolutions of the order of 1km. Models can exhibit large biases in seasonal mean LST for various reasons, including poor description of aerodynamic coupling, uncertainties in vegetation mapping, and errors in down-welling radiation. Rather than compare long-term average LST values with models, we focus on the dynamics of LST during dry spells, when negligible rain falls, and the soil moisture store is drying out. The rate of warming of the land surface, or, more precisely, its warming rate relative to the atmosphere, emphasises the impact of changes in soil moisture control on the surface energy balance. Here we show the application of this approach to model evaluation, with examples at continental and global scales. We can compare the behaviour of both fully-coupled land-atmosphere models, and land surface models forced by observed meteorology. This approach provides insight into a fundamental process that affects predictions on multiple time scales, and which has an important impact for society.

Thermal conductance of and heat generation in tire-pavement interface and effect on aircraft braking

NASA Technical Reports Server (NTRS)

Miller, C. D.

1976-01-01

A finite-difference analysis was performed on temperature records obtained from a free rolling automotive tire and from pavement surface. A high thermal contact conductance between tire and asphalt was found on a statistical basis. Average slip due to squirming between tire and asphalt was about 1.5 mm. Consequent friction heat was estimated as 64 percent of total power absorbed by bias-ply, belted tire. Extrapolation of results to aircraft tire indicates potential braking improvement by even moderate increase of heat absorbing capacity of runway surface.

Evaluation of tropical Pacific observing systems using NCEP and GFDL ocean data assimilation systems

NASA Astrophysics Data System (ADS)

Xue, Yan; Wen, Caihong; Yang, Xiaosong; Behringer, David; Kumar, Arun; Vecchi, Gabriel; Rosati, Anthony; Gudgel, Rich

2017-08-01

The TAO/TRITON array is the cornerstone of the tropical Pacific and ENSO observing system. Motivated by the recent rapid decline of the TAO/TRITON array, the potential utility of TAO/TRITON was assessed for ENSO monitoring and prediction. The analysis focused on the period when observations from Argo floats were also available. We coordinated observing system experiments (OSEs) using the global ocean data assimilation system (GODAS) from the National Centers for Environmental Prediction and the ensemble coupled data assimilation (ECDA) from the Geophysical Fluid Dynamics Laboratory for the period 2004-2011. Four OSE simulations were conducted with inclusion of different subsets of in situ profiles: all profiles (XBT, moorings, Argo), all except the moorings, all except the Argo and no profiles. For evaluation of the OSE simulations, we examined the mean bias, standard deviation difference, root-mean-square difference (RMSD) and anomaly correlation against observations and objective analyses. Without assimilation of in situ observations, both GODAS and ECDA had large mean biases and RMSD in all variables. Assimilation of all in situ data significantly reduced mean biases and RMSD in all variables except zonal current at the equator. For GODAS, the mooring data is critical in constraining temperature in the eastern and northwestern tropical Pacific, while for ECDA both the mooring and Argo data is needed in constraining temperature in the western tropical Pacific. The Argo data is critical in constraining temperature in off-equatorial regions for both GODAS and ECDA. For constraining salinity, sea surface height and surface current analysis, the influence of Argo data was more pronounced. In addition, the salinity data from the TRITON buoys played an important role in constraining salinity in the western Pacific. GODAS was more sensitive to withholding Argo data in off-equatorial regions than ECDA because it relied on local observations to correct model biases and there were few XBT profiles in those regions. The results suggest that multiple ocean data assimilation systems should be used to assess sensitivity of ocean analyses to changes in the distribution of ocean observations to get more robust results that can guide the design of future tropical Pacific observing systems.

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.

The Effect of Sea-Surface Sun Glitter on Microwave Radiometer Measurements

NASA Technical Reports Server (NTRS)

Wentz, F. J.

1981-01-01

A relatively simple model for the microwave brightness temperature of sea surface Sun glitter is presented. The model is an accurate closeform approximation for the fourfold Sun glitter integral. The model computations indicate that Sun glitter contamination of on orbit radiometer measurements is appreciable over a large swath area. For winds near 20 m/s, Sun glitter affects the retrieval of environmental parameters for Sun angles as large as 20 to 25 deg. The model predicted biases in retrieved wind speed and sea surface temperature due to neglecting Sun glitter are consistent with those experimentally observed in SEASAT SMMR retrievals. A least squares retrieval algorithm that uses a combined sea and Sun model function shows the potential of retrieving accurate environmental parameters in the presence of Sun glitter so long as the Sun angles and wind speed are above 5 deg and 2 m/s, respectively.

Three-dimensional scanning force/tunneling spectroscopy at room temperature.

PubMed

Sugimoto, Yoshiaki; Ueda, Keiichi; Abe, Masayuki; Morita, Seizo

2012-02-29

We simultaneously measured the force and tunneling current in three-dimensional (3D) space on the Si(111)-(7 × 7) surface using scanning force/tunneling microscopy at room temperature. The observables, the frequency shift and the time-averaged tunneling current were converted to the physical quantities of interest, i.e. the interaction force and the instantaneous tunneling current. Using the same tip, the local density of states (LDOS) was mapped on the same surface area at constant height by measuring the time-averaged tunneling current as a function of the bias voltage at every lateral position. LDOS images at negative sample voltages indicate that the tip apex is covered with Si atoms, which is consistent with the Si-Si covalent bonding mechanism for AFM imaging. A measurement technique for 3D force/current mapping and LDOS imaging on the equivalent surface area using the same tip was thus demonstrated.

Dynamical and Thermodynamic Elements of Modeled Climate Change at the East African Margin of Convection

NASA Astrophysics Data System (ADS)

Giannini, Alessandra; Lyon, Bradfield; Seager, Richard; Vigaud, Nicolas

2018-01-01

We propose a dynamical interpretation of model projections for an end-of-century wetting in equatorial East Africa. In the current generation of global climate models, increased atmospheric moisture content associated with warming is not the dominant process explaining the increase in rainfall, as the regional circulation is only weakly convergent even during the rainy seasons. Instead, projected wetter future conditions are generally consistent with the El Niño-like trend in tropical Pacific sea surface temperatures in climate models. In addition, a weakening in moisture convergence over the adjacent Congo Basin and Maritime Continent cores of convection results in the weakening of near-surface winds, which increases moisture advection from the Congo Basin core toward the East African margin. Overall confidence in the projections is limited by the significant biases in simulation of the regional climatology and disagreement between observed and modeled tropical Pacific sea surface temperature trends to date.

Enhanced Wang Landau sampling of adsorbed protein conformations.

PubMed

Radhakrishna, Mithun; Sharma, Sumit; Kumar, Sanat K

2012-03-21

Using computer simulations to model the folding of proteins into their native states is computationally expensive due to the extraordinarily low degeneracy of the ground state. In this paper, we develop an efficient way to sample these folded conformations using Wang Landau sampling coupled with the configurational bias method (which uses an unphysical "temperature" that lies between the collapse and folding transition temperatures of the protein). This method speeds up the folding process by roughly an order of magnitude over existing algorithms for the sequences studied. We apply this method to study the adsorption of intrinsically disordered hydrophobic polar protein fragments on a hydrophobic surface. We find that these fragments, which are unstructured in the bulk, acquire secondary structure upon adsorption onto a strong hydrophobic surface. Apparently, the presence of a hydrophobic surface allows these random coil fragments to fold by providing hydrophobic contacts that were lost in protein fragmentation. © 2012 American Institute of Physics

Understanding tropical upper tropospheric warming: The role of SSTs, convective parameterizations, and observational uncertainties

NASA Astrophysics Data System (ADS)

Po-Chedley, S.; Thorsen, T. J.; Fu, Q.

2015-12-01

Recent research has compared CMIP5 general circulation model (GCM) simulations with satellite observations of warming in the tropical upper troposphere relative to the lower-middle troposphere. Although the pattern of SST warming is important, this research demonstrated that models overestimate increases in static stability between the mid- to upper- tropical troposphere, even when they are forced with historical sea surface temperatures. This discrepancy between satellite-borne microwave sounding unit measurements (MSU) and GCMs is important because it has implications for the strength of the lapse rate and water vapor feedback. The apparent model-observational difference for changes in static stability in the tropical upper troposphere represents an important problem, but it is not clear whether the difference is a result of common biases in GCMs, biases in observational datasets, or both. In this work, we will use GCM simulations to examine the importance of the spatial pattern of SST warming and different convective parameterizations in determining the lapse rate changes in tropical troposphere. We will also consider uncertainties in MSU satellite observations, including changes in the diurnal sampling of temperature and instrument calibration biases when comparing GCMs with the observed record.

Tunneling electron induced chemisorption of copper phthalocyanine molecules on the Cu(111) surface

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

Stock, T.; Nogami, J.

2014-02-17

The adsorption of up to one monolayer (ML) of copper phthalocyanine (CuPc) molecules on a room temperature Cu(111) surface has been studied using scanning tunneling microscopy (STM). Below 1 ML the molecules are in a fluid state and are highly mobile on the surface. At 1 ML coverage the molecules coalesce into a highly ordered 2D crystal phase. At sub-ML coverages, chemisorption of individual CuPc molecules can be induced through exposure to tunneling electrons at a tunneling bias voltage exceeding a threshold value. This tunneling electron induced effect has been exploited to perform molecular STM lithography.

Imaging Josephson vortices on the surface superconductor Si(111)-(√7×√3)-In using a scanning tunneling microscope.

PubMed

Yoshizawa, Shunsuke; Kim, Howon; Kawakami, Takuto; Nagai, Yuki; Nakayama, Tomonobu; Hu, Xiao; Hasegawa, Yukio; Uchihashi, Takashi

2014-12-12

We have studied the superconducting Si(111)-(√7×√3)-In surface using a ³He-based low-temperature scanning tunneling microscope. Zero-bias conductance images taken over a large surface area reveal that vortices are trapped at atomic steps after magnetic fields are applied. The crossover behavior from Pearl to Josephson vortices is clearly identified from their elongated shapes along the steps and significant recovery of superconductivity within the cores. Our numerical calculations combined with experiments clarify that these characteristic features are determined by the relative strength of the interterrace Josephson coupling at the atomic step.

Impact of a statistical bias correction on the projected simulated hydrological changes obtained from three GCMs and two hydrology models

NASA Astrophysics Data System (ADS)

Hagemann, Stefan; Chen, Cui; Haerter, Jan O.; Gerten, Dieter; Heinke, Jens; Piani, Claudio

2010-05-01

Future climate model scenarios depend crucially on their adequate representation of the hydrological cycle. Within the European project "Water and Global Change" (WATCH) special care is taken to couple state-of-the-art climate model output to a suite of hydrological models. This coupling is expected to lead to a better assessment of changes in the hydrological cycle. However, due to the systematic model errors of climate models, their output is often not directly applicable as input for hydrological models. Thus, the methodology of a statistical bias correction has been developed, which can be used for correcting climate model output to produce internally consistent fields that have the same statistical intensity distribution as the observations. As observations, global re-analysed daily data of precipitation and temperature are used that are obtained in the WATCH project. We will apply the bias correction to global climate model data of precipitation and temperature from the GCMs ECHAM5/MPIOM, CNRM-CM3 and LMDZ-4, and intercompare the bias corrected data to the original GCM data and the observations. Then, the orginal and the bias corrected GCM data will be used to force two global hydrology models: (1) the hydrological model of the Max Planck Institute for Meteorology (MPI-HM) consisting of the Simplified Land surface (SL) scheme and the Hydrological Discharge (HD) model, and (2) the dynamic vegetation model LPJmL operated by the Potsdam Institute for Climate Impact Research. The impact of the bias correction on the projected simulated hydrological changes will be analysed, and the resulting behaviour of the two hydrology models will be compared.

Radiometric characterization of an LWIR, type-II strained layer superlattice pBiBn photodetector

NASA Astrophysics Data System (ADS)

Treider, L. A.; Morath, C. P.; Cowan, V. M.; Tian, Z. B.; Krishna, S.

2015-05-01

Type-II Strained Layer Superlattice (T2SLS) infrared photodetectors have been in development over the last decade. T2SLS offers a theoretically longer Auger recombination lifetime than traditional mercury cadmium telluride (MCT), which presumably translates to infrared detectors with lower dark-current and higher operating temperatures. However, these improvements did not materialize due to the presence of Shockley-Read-Hall (SRH) defects in T2SLSs, which limits the recombination lifetime well below the Auger-limit. With the recent introduction of the pBiBn, and other similar unipolar barrier detectors, T2SLS material has seen renewed interest since these designs ideally eliminate the SRH-generation and surface currents while retaining the other potential advantages of T2SLS: reduced manufacturing cost, better availability of a durable state-side manufacturing base, ability to tune the cutoff wavelength, and better uniformity. Here, an electrical and optical characterization of a long-wave, pBiBn detector with a T2SLS absorber is presented. Dark-current, spectral response and optical response were measured as functions of temperature and bias. Activation energy was then determined as a function of bias from the dark-current measurements. Quantum efficiency was also determined as a function of bias from the optical response measurements. Additionally, noise spectrum measurements were taken as a function of bias.

Recent advances in the salinity retrieval algorithms for Aquarius and Soil Moisture Active Passive (SMAP)

NASA Astrophysics Data System (ADS)

Meissner, Thomas; Wentz, Frank; Lee, Tong

2017-04-01

Our presentation discusses the latest improvements in the salinity retrievals both for Aquarius and Soil Moisture Active-Passive (SMAP) since the last releases. The Aquarius V4.0 was released in June 2015. The final V5.0 release is planned for late 2017. SMAP V 2.0 has been released in September 2016. We will present validation results for both Aquarius V5.0 pre-release and SMAP V2.0 salinity comparing with near-surface salinity measurements from Argo floats. We show that salty biases at higher northern latitudes in Aquarius V4.0 can be explained by inaccuracy in the model used in correcting for the absorption by atmospheric oxygen. These biases will be mitigated in V5.0 by fine-tuning the parameters in the oxygen absorption model. The full 360-degree look capability of SMAP makes it possible to take observations from the forward and backward looking direction at the same instance of time. This two-look capability aids the salinity retrievals. One of the largest spurious contaminations in the salinity retrievals is caused by the galactic reflection from the ocean surface. Because in most instances the reflected galaxy appears only in either the forward or the backward look, it is possible to determine its contribution by taking the difference of the measured SMAP brightness temperatures between the two looks. Our result suggests that the surface roughness that is used in the galactic correction needs to be increased and also the estimated strength of some of the galactic sources need to be slightly adjusted. The improved galaxy correction has been implemented in SMAP V2.0 retrieval and will be included in Aquarius V5.0 as well. It helps the mitigation of residual zonal and temporal biases that were present in both products. Another major cause of the observed zonal biases in SMAP is the emissive SMAP mesh antenna. In order to correct for it, an accurate knowledge of the emissivity of the antenna and its physical temperature are required. We discuss the improvements in the correction for the emissive SMAP antenna in SMAP V2.0 over V1.0.

Impact of decadal cloud variations on the Earth’s energy budget

DOE PAGES

Zhou, Chen; Zelinka, Mark D.; Klein, Stephen A.

2016-10-31

Feedbacks of clouds on climate change strongly influence the magnitude of global warming. Cloud feedbacks, in turn, depend on the spatial patterns of surface warming, which vary on decadal timescales. Therefore, the magnitude of the decadal cloud feedback could deviate from the long-term cloud feedback. We present climate model simulations to show that the global mean cloud feedback in response to decadal temperature fluctuations varies dramatically due to time variations in the spatial pattern of sea surface temperature. Here, we find that cloud anomalies associated with these patterns significantly modify the Earth’s energy budget. Specifically, the decadal cloud feedback betweenmore » the 1980s and 2000s is substantially more negative than the long-term cloud feedback. This is a result of cooling in tropical regions where air descends, relative to warming in tropical ascent regions, which strengthens low-level atmospheric stability. Under these conditions, low-level cloud cover and its reflection of solar radiation increase, despite an increase in global mean surface temperature. Our results suggest that sea surface temperature pattern-induced low cloud anomalies could have contributed to the period of reduced warming between 1998 and 2013, and o er a physical explanation of why climate sensitivities estimated from recently observed trends are probably biased low.« less

Impact of decadal cloud variations on the Earth’s energy budget

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

Zhou, Chen; Zelinka, Mark D.; Klein, Stephen A.

Feedbacks of clouds on climate change strongly influence the magnitude of global warming. Cloud feedbacks, in turn, depend on the spatial patterns of surface warming, which vary on decadal timescales. Therefore, the magnitude of the decadal cloud feedback could deviate from the long-term cloud feedback. We present climate model simulations to show that the global mean cloud feedback in response to decadal temperature fluctuations varies dramatically due to time variations in the spatial pattern of sea surface temperature. Here, we find that cloud anomalies associated with these patterns significantly modify the Earth’s energy budget. Specifically, the decadal cloud feedback betweenmore » the 1980s and 2000s is substantially more negative than the long-term cloud feedback. This is a result of cooling in tropical regions where air descends, relative to warming in tropical ascent regions, which strengthens low-level atmospheric stability. Under these conditions, low-level cloud cover and its reflection of solar radiation increase, despite an increase in global mean surface temperature. Our results suggest that sea surface temperature pattern-induced low cloud anomalies could have contributed to the period of reduced warming between 1998 and 2013, and o er a physical explanation of why climate sensitivities estimated from recently observed trends are probably biased low.« less

Impact of decadal cloud variations on the Earth's energy budget

NASA Astrophysics Data System (ADS)

Zhou, Chen; Zelinka, Mark D.; Klein, Stephen A.

2016-12-01

Feedbacks of clouds on climate change strongly influence the magnitude of global warming. Cloud feedbacks, in turn, depend on the spatial patterns of surface warming, which vary on decadal timescales. Therefore, the magnitude of the decadal cloud feedback could deviate from the long-term cloud feedback. Here we present climate model simulations to show that the global mean cloud feedback in response to decadal temperature fluctuations varies dramatically due to time variations in the spatial pattern of sea surface temperature. We find that cloud anomalies associated with these patterns significantly modify the Earth's energy budget. Specifically, the decadal cloud feedback between the 1980s and 2000s is substantially more negative than the long-term cloud feedback. This is a result of cooling in tropical regions where air descends, relative to warming in tropical ascent regions, which strengthens low-level atmospheric stability. Under these conditions, low-level cloud cover and its reflection of solar radiation increase, despite an increase in global mean surface temperature. These results suggest that sea surface temperature pattern-induced low cloud anomalies could have contributed to the period of reduced warming between 1998 and 2013, and offer a physical explanation of why climate sensitivities estimated from recently observed trends are probably biased low.

Sea Surface Temperature for Climate Applications: A New Dataset from the European Space Agency Climate Change Initiative

NASA Astrophysics Data System (ADS)

Merchant, C. J.; Hulley, G. C.

2013-12-01

There are many datasets describing the evolution of global sea surface temperature (SST) over recent decades -- so why make another one? Answer: to provide observations of SST that have particular qualities relevant to climate applications: independence, accuracy and stability. This has been done within the European Space Agency (ESA) Climate Change Initative (CCI) project on SST. Independence refers to the fact that the new SST CCI dataset is not derived from or tuned to in situ observations. This matters for climate because the in situ observing network used to assess marine climate change (1) was not designed to monitor small changes over decadal timescales, and (2) has evolved significantly in its technology and mix of types of observation, even during the past 40 years. The potential for significant artefacts in our picture of global ocean surface warming is clear. Only by having an independent record can we confirm (or refute) that the work done to remove biases/trend artefacts in in-situ datasets has been successful. Accuracy is the degree to which SSTs are unbiased. For climate applications, a common accuracy target is 0.1 K for all regions of the ocean. Stability is the degree to which the bias, if any, in a dataset is constant over time. Long-term instability introduces trend artefacts. To observe trends of the magnitude of 'global warming', SST datasets need to be stable to <5 mK/year. The SST CCI project has produced a satellite-based dataset that addresses these characteristics relevant to climate applications. Satellite radiances (brightness temperatures) have been harmonised exploiting periods of overlapping observations between sensors. Less well-characterised sensors have had their calibration tuned to that of better characterised sensors (at radiance level). Non-conventional retrieval methods (optimal estimation) have been employed to reduce regional biases to the 0.1 K level, a target violated in most satellite SST datasets. Models for quantifying uncertainty have been developed to attach uncertainty to SST across a range of space-time scales. The stability of the data has been validated.

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

NASA Astrophysics Data System (ADS)

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

2015-05-01

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

Deriving a sea surface temperature record suitable for climate change research from the along-track scanning radiometers

NASA Astrophysics Data System (ADS)

Merchant, C. J.; Llewellyn-Jones, D.; Saunders, R. W.; Rayner, N. A.; Kent, E. C.; Old, C. P.; Berry, D.; Birks, A. R.; Blackmore, T.; Corlett, G. K.; Embury, O.; Jay, V. L.; Kennedy, J.; Mutlow, C. T.; Nightingale, T. J.; O'Carroll, A. G.; Pritchard, M. J.; Remedios, J. J.; Tett, S.

We describe the approach to be adopted for a major new initiative to derive a homogeneous record of sea surface temperature for 1991 2007 from the observations of the series of three along-track scanning radiometers (ATSRs). This initiative is called (A)RC: (Advanced) ATSR Re-analysis for Climate. The main objectives are to reduce regional biases in retrieved sea surface temperature (SST) to less than 0.1 K for all global oceans, while creating a very homogenous record that is stable in time to within 0.05 K decade-1, with maximum independence of the record from existing analyses of SST used in climate change research. If these stringent targets are achieved, this record will enable significantly improved estimates of surface temperature trends and variability of sufficient quality to advance questions of climate change attribution, climate sensitivity and historical reconstruction of surface temperature changes. The approach includes development of new, consistent estimators for SST for each of the ATSRs, and detailed analysis of overlap periods. Novel aspects of the approach include generation of multiple versions of the record using alternative channel sets and cloud detection techniques, to assess for the first time the effect of such choices. There will be extensive effort in quality control, validation and analysis of the impact on climate SST data sets. Evidence for the plausibility of the 0.1 K target for systematic error is reviewed, as is the need for alternative cloud screening methods in this context.

Temperature dependence of current-voltage characteristics in highly doped Ag/p-GaN/In Schottky diodes

NASA Astrophysics Data System (ADS)

Ćınar, K.; Yıldırım, N.; Coşkun, C.; Turut, A.

2009-10-01

To obtain detailed information about the conduction process of the Ag/p-GaN Schottky diodes (SDs) fabricated by us, we measured the I-V characteristics over the temperature range of 80-360 K by the steps of 20 K. The slope of the linear portion of the forward bias I-V plot and nkT =E0 of the device remained almost unchanged as independent of temperature with an average of 25.71±0.90 V-1 and 41.44±1.38 meV, respectively. Therefore, it can be said that the experimental I-V data quite well obey the field emission model rather than the thermionic emission or thermionic field emission model. The study is a very good experimental example for the FE model. Furthermore, the reverse bias saturation current ranges from 8.34×10-8 A at 80 K to 2.10×10-7 A at 360 K, indicating that the charge transport mechanism in the Ag/p-GaN SD is tunneling due to the weak temperature dependence of the saturation current. The possible origin of high experimental characteristic tunneling energy of E00=39 meV, which is ten times larger than possible theoretical value of 3.89 meV, is attributed to the accumulation of a large amount of defect states near the GaN surface or to the deep level defect band induced by high doping or to any mechanism which enhances the electric field and the state density at the semiconductor surface.

Simulation of climate characteristics and extremes of the Volta Basin using CCLM and RCA regional climate models

NASA Astrophysics Data System (ADS)

Darko, Deborah; Adjei, Kwaku A.; Appiah-Adjei, Emmanuel K.; Odai, Samuel N.; Obuobie, Emmanuel; Asmah, Ruby

2018-06-01

The extent to which statistical bias-adjusted outputs of two regional climate models alter the projected change signals for the mean (and extreme) rainfall and temperature over the Volta Basin is evaluated. The outputs from two regional climate models in the Coordinated Regional Climate Downscaling Experiment for Africa (CORDEX-Africa) are bias adjusted using the quantile mapping technique. Annual maxima rainfall and temperature with their 10- and 20-year return values for the present (1981-2010) and future (2051-2080) climates are estimated using extreme value analyses. Moderate extremes are evaluated using extreme indices (viz. percentile-based, duration-based, and intensity-based). Bias adjustment of the original (bias-unadjusted) models improves the reproduction of mean rainfall and temperature for the present climate. However, the bias-adjusted models poorly reproduce the 10- and 20-year return values for rainfall and maximum temperature whereas the extreme indices are reproduced satisfactorily for the present climate. Consequently, projected changes in rainfall and temperature extremes were weak. The bias adjustment results in the reduction of the change signals for the mean rainfall while the mean temperature signals are rather magnified. The projected changes for the original mean climate and extremes are not conserved after bias adjustment with the exception of duration-based extreme indices.

Evaluation of urban surface parameterizations in the WRF model using measurements during the Texas Air Quality Study 2006 field campaign

NASA Astrophysics Data System (ADS)

Lee, S.-H.; Kim, S.-W.; Angevine, W. M.; Bianco, L.; McKeen, S. A.; Senff, C. J.; Trainer, M.; Tucker, S. C.; Zamora, R. J.

2011-03-01

The performance of different urban surface parameterizations in the WRF (Weather Research and Forecasting) in simulating urban boundary layer (UBL) was investigated using extensive measurements during the Texas Air Quality Study 2006 field campaign. The extensive field measurements collected on surface (meteorological, wind profiler, energy balance flux) sites, a research aircraft, and a research vessel characterized 3-dimensional atmospheric boundary layer structures over the Houston-Galveston Bay area, providing a unique opportunity for the evaluation of the physical parameterizations. The model simulations were performed over the Houston metropolitan area for a summertime period (12-17 August) using a bulk urban parameterization in the Noah land surface model (original LSM), a modified LSM, and a single-layer urban canopy model (UCM). The UCM simulation compared quite well with the observations over the Houston urban areas, reducing the systematic model biases in the original LSM simulation by 1-2 °C in near-surface air temperature and by 200-400 m in UBL height, on average. A more realistic turbulent (sensible and latent heat) energy partitioning contributed to the improvements in the UCM simulation. The original LSM significantly overestimated the sensible heat flux (~200 W m-2) over the urban areas, resulting in warmer and higher UBL. The modified LSM slightly reduced warm and high biases in near-surface air temperature (0.5-1 °C) and UBL height (~100 m) as a result of the effects of urban vegetation. The relatively strong thermal contrast between the Houston area and the water bodies (Galveston Bay and the Gulf of Mexico) in the LSM simulations enhanced the sea/bay breezes, but the model performance in predicting local wind fields was similar among the simulations in terms of statistical evaluations. These results suggest that a proper surface representation (e.g. urban vegetation, surface morphology) and explicit parameterizations of urban physical processes are required for accurate urban atmospheric numerical modeling.

Method and apparatus for electron-only radiation detectors from semiconductor materials

DOEpatents

Lund, James C.

2000-01-01

A system for obtaining improved resolution in room temperature semiconductor radiation detectors such as CdZnTe and Hgl.sub.2, which exhibit significant hole-trapping. A electrical reference plane is established about the perimeter of a semiconductor crystal and disposed intermediately between two oppositely biased end electrodes. The intermediate reference plane comprises a narrow strip of wire in electrical contact with the surface of the crystal, biased at a potential between the end electrode potentials and serving as an auxiliary electrical reference for a chosen electrode--typically the collector electrode for the more mobile charge carrier. This arrangement eliminates the interfering effects of the less mobile carriers as these are gathered by their electrode collector.

Climatologies at high resolution for the earth’s land surface areas

PubMed Central

Karger, Dirk Nikolaus; Conrad, Olaf; Böhner, Jürgen; Kawohl, Tobias; Kreft, Holger; Soria-Auza, Rodrigo Wilber; Zimmermann, Niklaus E.; Linder, H. Peter; Kessler, Michael

2017-01-01

High-resolution information on climatic conditions is essential to many applications in environmental and ecological sciences. Here we present the CHELSA (Climatologies at high resolution for the earth’s land surface areas) data of downscaled model output temperature and precipitation estimates of the ERA-Interim climatic reanalysis to a high resolution of 30 arc sec. The temperature algorithm is based on statistical downscaling of atmospheric temperatures. The precipitation algorithm incorporates orographic predictors including wind fields, valley exposition, and boundary layer height, with a subsequent bias correction. The resulting data consist of a monthly temperature and precipitation climatology for the years 1979–2013. We compare the data derived from the CHELSA algorithm with other standard gridded products and station data from the Global Historical Climate Network. We compare the performance of the new climatologies in species distribution modelling and show that we can increase the accuracy of species range predictions. We further show that CHELSA climatological data has a similar accuracy as other products for temperature, but that its predictions of precipitation patterns are better. PMID:28872642

Climatologies at high resolution for the earth's land surface areas

NASA Astrophysics Data System (ADS)

Karger, Dirk Nikolaus; Conrad, Olaf; Böhner, Jürgen; Kawohl, Tobias; Kreft, Holger; Soria-Auza, Rodrigo Wilber; Zimmermann, Niklaus E.; Linder, H. Peter; Kessler, Michael

2017-09-01

High-resolution information on climatic conditions is essential to many applications in environmental and ecological sciences. Here we present the CHELSA (Climatologies at high resolution for the earth's land surface areas) data of downscaled model output temperature and precipitation estimates of the ERA-Interim climatic reanalysis to a high resolution of 30 arc sec. The temperature algorithm is based on statistical downscaling of atmospheric temperatures. The precipitation algorithm incorporates orographic predictors including wind fields, valley exposition, and boundary layer height, with a subsequent bias correction. The resulting data consist of a monthly temperature and precipitation climatology for the years 1979-2013. We compare the data derived from the CHELSA algorithm with other standard gridded products and station data from the Global Historical Climate Network. We compare the performance of the new climatologies in species distribution modelling and show that we can increase the accuracy of species range predictions. We further show that CHELSA climatological data has a similar accuracy as other products for temperature, but that its predictions of precipitation patterns are better.

Adaptively biased molecular dynamics for free energy calculations

NASA Astrophysics Data System (ADS)

Babin, Volodymyr; Roland, Christopher; Sagui, Celeste

2008-04-01

We present an adaptively biased molecular dynamics (ABMD) method for the computation of the free energy surface of a reaction coordinate using nonequilibrium dynamics. The ABMD method belongs to the general category of umbrella sampling methods with an evolving biasing potential and is inspired by the metadynamics method. The ABMD method has several useful features, including a small number of control parameters and an O(t ) numerical cost with molecular dynamics time t. The ABMD method naturally allows for extensions based on multiple walkers and replica exchange, where different replicas can have different temperatures and/or collective variables. This is beneficial not only in terms of the speed and accuracy of a calculation, but also in terms of the amount of useful information that may be obtained from a given simulation. The workings of the ABMD method are illustrated via a study of the folding of the Ace-GGPGGG-Nme peptide in a gaseous and solvated environment.

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.

Local electronic and optical behavior of ELO a-plane GaN

NASA Astrophysics Data System (ADS)

Baski, A. A.; Moore, J. C.; Ozgur, U.; Kasliwal, V.; Ni, X.; Morkoc, H.

2007-03-01

Conductive atomic force microscopy (CAFM) and near-field optical microscopy (NSOM) were used to study a-plane GaN films grown via epitaxial lateral overgrowth (ELO). The ELO films were prepared by metal organic chemical vapor deposition on a patterned SiO2 layer with 4-μm wide windows, which was deposited on a GaN template grown on r-plane sapphire. The window regions of the coalesced ELO films appear as depressions with a high density of surface pits. At reverse bias below 12 V, very low uniform conduction (2 pA) is seen in the window regions. Above 20 V, a lower-quality sample shows localized sites inside the window regions with significant leakage, indicating a correlation between the presence of surface pits and leakage sites. Room temperature NSOM studies also suggest a greater density of surface terminated dislocations in the window regions, while wing regions explicitly show enhanced optical quality of the overgrown GaN. The combination of CAFM and NSOM data therefore indicates a correlation between the presence of surface pits, localized reverse-bias current leakage, and low PL intensity in the window regions.

CAUSES: Clouds Above the United States and Errors at the Surface

NASA Astrophysics Data System (ADS)

Ma, H. Y.; Klein, S. A.; Xie, S.; Morcrette, C. J.; Van Weverberg, K.; Zhang, Y.; Lo, M. H.

2015-12-01

The Clouds Above the United States and Errors at the Surface (CAUSES) is a new joint Global Atmospheric System Studies/Regional and Global Climate model/Atmospheric System Research (GASS/RGCM/ASR) intercomparison project to evaluate the central U.S. summertime surface warm biases seen in many weather and climate models. The main focus is to identify the role of cloud, radiation, and precipitation processes in contributing to surface air temperature biases. In this project, we use short-term hindcast approach and examine the growth of the error as a function of hindcast lead time. The study period covers from April 1 to August 31, 2011, which also covers the entire Midlatitude Continental Convective Clouds Experiment (MC3E) campaign. Preliminary results from several models will be presented. (http://portal.nersc.gov/project/capt/CAUSES/) (This study is funded by the RGCM and ASR programs of the U.S. Department of Energy as part of the Cloud-Associated Parameterizations Testbed. This work is performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. LLNL-ABS-658017)

CAUSES: Clouds Above the United States and Errors at the Surface

NASA Astrophysics Data System (ADS)

Ma, H. Y.; Klein, S. A.; Xie, S.; Zhang, Y.; Morcrette, C. J.; Van Weverberg, K.; Petch, J.; Lo, M. H.

2014-12-01

The Clouds Above the United States and Errors at the Surface (CAUSES) is a new joint Global Atmospheric System Studies/Regional and Global Climate model/Atmospheric System Research (GASS/RGCM/ASR) intercomparison project to evaluate the central U.S. summertime surface warm biases seen in many weather and climate models. The main focus is to identify the role of cloud, radiation, and precipitation processes in contributing to surface air temperature biases. In this project, we use short-term hindcast approach and examine the growth of the error as a function of hindcast lead time. The study period covers from April 1 to August 31, 2011, which also covers the entire Midlatitude Continental Convective Clouds Experiment (MC3E) campaign. Preliminary results from several models will be presented. (http://portal.nersc.gov/project/capt/CAUSES/) (This study is funded by the RGCM and ASR programs of the U.S. Department of Energy as part of the Cloud-Associated Parameterizations Testbed. This work is performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. LLNL-ABS-658017)

Effects of modeled tropical sea surface temperature variability on coral reef bleaching predictions

NASA Astrophysics Data System (ADS)

van Hooidonk, R.; Huber, M.

2012-03-01

Future widespread coral bleaching and subsequent mortality has been projected using sea surface temperature (SST) data derived from global, coupled ocean-atmosphere general circulation models (GCMs). While these models possess fidelity in reproducing many aspects of climate, they vary in their ability to correctly capture such parameters as the tropical ocean seasonal cycle and El Niño Southern Oscillation (ENSO) variability. Such weaknesses most likely reduce the accuracy of predicting coral bleaching, but little attention has been paid to the important issue of understanding potential errors and biases, the interaction of these biases with trends, and their propagation in predictions. To analyze the relative importance of various types of model errors and biases in predicting coral bleaching, various intra- and inter-annual frequency bands of observed SSTs were replaced with those frequencies from 24 GCMs 20th century simulations included in the Intergovernmental Panel on Climate Change (IPCC) 4th assessment report. Subsequent thermal stress was calculated and predictions of bleaching were made. These predictions were compared with observations of coral bleaching in the period 1982-2007 to calculate accuracy using an objective measure of forecast quality, the Peirce skill score (PSS). Major findings are that: (1) predictions are most sensitive to the seasonal cycle and inter-annual variability in the ENSO 24-60 months frequency band and (2) because models tend to understate the seasonal cycle at reef locations, they systematically underestimate future bleaching. The methodology we describe can be used to improve the accuracy of bleaching predictions by characterizing the errors and uncertainties involved in the predictions.

The Roles of Convection Parameterization in the Formation of Double ITCZ Syndrome in the NCAR CESM: I. Atmospheric Processes

NASA Astrophysics Data System (ADS)

Song, Xiaoliang; Zhang, Guang J.

2018-03-01

Several improvements are implemented in the Zhang-McFarlane (ZM) convection scheme to investigate the roles of convection parameterization in the formation of double intertropical convergence zone (ITCZ) bias in the NCAR CESM1.2.1. It is shown that the prominent double ITCZ biases of precipitation, sea surface temperature (SST), and wind stress in the standard CESM1.2.1 are largely eliminated in all seasons with the use of these improvements in convection scheme. This study for the first time demonstrates that the modifications of convection scheme can eliminate the double ITCZ biases in all seasons, including boreal winter and spring. Further analysis shows that the elimination of the double ITCZ bias is achieved not by improving other possible contributors, such as stratus cloud bias off the west coast of South America and cloud/radiation biases over the Southern Ocean, but by modifying the convection scheme itself. This study demonstrates that convection scheme is the primary contributor to the double ITCZ bias in the CESM1.2.1, and provides a possible solution to the long-standing double ITCZ problem. The atmospheric model simulations forced by observed SST show that the original ZM convection scheme tends to produce double ITCZ bias in high SST scenario, while the modified convection scheme does not. The impact of changes in each core component of convection scheme on the double ITCZ bias in atmospheric model is identified and further investigated.

Future snowfall in the Alps: projections based on the EURO-CORDEX regional climate models

NASA Astrophysics Data System (ADS)

Frei, Prisco; Kotlarski, Sven; Liniger, Mark A.; Schär, Christoph

2018-01-01

Twenty-first century snowfall changes over the European Alps are assessed based on high-resolution regional climate model (RCM) data made available through the EURO-CORDEX initiative. Fourteen different combinations of global and regional climate models with a target resolution of 12 km and two different emission scenarios are considered. As raw snowfall amounts are not provided by all RCMs, a newly developed method to separate snowfall from total precipitation based on near-surface temperature conditions and accounting for subgrid-scale topographic variability is employed. The evaluation of the simulated snowfall amounts against an observation-based reference indicates the ability of RCMs to capture the main characteristics of the snowfall seasonal cycle and its elevation dependency but also reveals considerable positive biases especially at high elevations. These biases can partly be removed by the application of a dedicated RCM bias adjustment that separately considers temperature and precipitation biases.

Snowfall projections reveal a robust signal of decreasing snowfall amounts over most parts of the Alps for both emission scenarios. Domain and multi-model mean decreases in mean September-May snowfall by the end of the century amount to -25 and -45 % for representative concentration pathway (RCP) scenarios RCP4.5 and RCP8.5, respectively. Snowfall in low-lying areas in the Alpine forelands could be reduced by more than -80 %. These decreases are driven by the projected warming and are strongly connected to an important decrease in snowfall frequency and snowfall fraction and are also apparent for heavy snowfall events. In contrast, high-elevation regions could experience slight snowfall increases in midwinter for both emission scenarios despite the general decrease in the snowfall fraction. These increases in mean and heavy snowfall can be explained by a general increase in winter precipitation and by the fact that, with increasing temperatures, climatologically cold areas are shifted into a temperature interval which favours higher snowfall intensities. In general, percentage changes in snowfall indices are robust with respect to the RCM postprocessing strategy employed: similar results are obtained for raw, separated, and separated-bias-adjusted snowfall amounts. Absolute changes, however, can differ among these three methods.

Observational Constraints on the Water Vapor Feedback Using GPS Radio Occultations

NASA Astrophysics Data System (ADS)

Vergados, P.; Mannucci, A. J.; Ao, C. O.; Fetzer, E. J.

2016-12-01

The air refractive index at L-band frequencies depends on the air's density and water vapor content. Exploiting these relationships, we derive a theoretical model to infer the specific humidity response to surface temperature variations, dq/dTs, given knowledge of how the air refractive index and temperature vary with surface temperature. We validate this model using 1.2-1.6 GHz Global Positioning System Radio Occultation (GPS RO) observations from 2007 to 2010 at 250 hPa, where the water vapor feedback on surface warming is strongest. Current research indicates that GPS RO data sets can capture the amount of water vapor in very dry and very moist air more efficiently than other observing platforms, possibly suggesting larger water vapor feedback than previously known. Inter-comparing the dq/dTs among different data sets will provide us with additional constraints on the water vapor feedback. The dq/dTs estimation from GPS RO observations shows excellent agreement with previously published results and the responses estimated using Atmospheric Infrared Sounder (AIRS) and NASA's Modern-Era Retrospective Analysis for Research and Applications (MERRA) data sets. In particular, the GPS RO-derived dq/dTs is larger by 6% than that estimated using the AIRS data set. This agrees with past evidence that AIRS may be dry-biased in the upper troposphere. Compared to the MERRA estimations, the GPS RO-derived dq/dTs is 10% smaller, also agreeing with previous results that show that MERRA may have a wet bias in the upper troposphere. Because of their high sensitivity to fractional changes in water vapor, and their inherent long-term accuracy, current and future GPS RO observations show great promise in monitoring climate feedbacks and their trends.

Land surface temperature over global deserts: Means, variability, and trends

NASA Astrophysics Data System (ADS)

Zhou, Chunlüe; Wang, Kaicun

2016-12-01

Land surface air temperature (LSAT) has been a widely used metric to study climate change. Weather observations of LSAT are the fundamental data for climate change studies and provide key evidence of global warming. However, there are very few meteorological observations over deserts due to their uninhabitable environment. This study fills this gap and provides independent evidence using satellite-derived land surface temperatures (LSTs), benefiting from their global coverage. The frequency of clear sky from MODerate Resolution Imaging Spectroradiometer (MODIS) LST data over global deserts was found to be greater than 94% for the 2002-2015 period. Our results show that MODIS LST has a bias of 1.36°C compared to ground-based observations collected at 31 U.S. Climate Reference Network (USCRN) stations, with a standard deviation of 1.83°C. After bias correction, MODIS LST was used to evaluate existing reanalyses, including ERA-Interim, Japanese 55-year Reanalysis (JRA-55), Modern-Era Retrospective Analysis for Research and Applications (MERRA), MERRA-land, National Centers for Environmental Prediction (NCEP)-R1, and NCEP-R2. The reanalyses accurately reproduce the seasonal cycle and interannual variability of the LSTs, but their multiyear means and trends of LSTs exhibit large uncertainties. The multiyear averaged LST over global deserts is 23.5°C from MODIS and varies from 20.8°C to 24.5°C in different reanalyses. The MODIS LST over global deserts increased by 0.25°C/decade from 2002 to 2015, whereas the reanalyses estimated a trend varying from -0.14 to 0.10°C/decade. The underestimation of the LST trend by the reanalyses occurs for approximately 70% of the global deserts, likely due to the imperfect performance of the reanalyses in reproducing natural climate variability.

Optimisation of sea surface current retrieval using a maximum cross correlation technique on modelled sea surface temperature

NASA Astrophysics Data System (ADS)

Heuzé, Céline; Eriksson, Leif; Carvajal, Gisela

2017-04-01

Using sea surface temperature from satellite images to retrieve sea surface currents is not a new idea, but so far its operational near-real time implementation has not been possible. Validation studies are too region-specific or uncertain, due to the errors induced by the images themselves. Moreover, the sensitivity of the most common retrieval method, the maximum cross correlation, to the three parameters that have to be set is unknown. Using model outputs instead of satellite images, biases induced by this method are assessed here, for four different seas of Western Europe, and the best of nine settings and eight temporal resolutions are determined. For all regions, tracking a small 5 km pattern from the first image over a large 30 km region around its original location on a second image, separated from the first image by 6 to 9 hours returned the most accurate results. Moreover, for all regions, the problem is not inaccurate results but missing results, where the velocity is too low to be picked by the retrieval. The results are consistent both with limitations caused by ocean surface current dynamics and with the available satellite technology, indicating that automated sea surface current retrieval from sea surface temperature images is feasible now, for search and rescue operations, pollution confinement or even for more energy efficient and comfortable ship navigation.

Surface wave effects on water temperature in the Baltic Sea: simulations with the coupled NEMO-WAM model

NASA Astrophysics Data System (ADS)

Alari, Victor; Staneva, Joanna; Breivik, Øyvind; Bidlot, Jean-Raymond; Mogensen, Kristian; Janssen, Peter

2016-08-01

Coupled circulation (NEMO) and wave model (WAM) system was used to study the effects of surface ocean waves on water temperature distribution and heat exchange at regional scale (the Baltic Sea). Four scenarios—including Stokes-Coriolis force, sea-state dependent energy flux (additional turbulent kinetic energy due to breaking waves), sea-state dependent momentum flux and the combination these forcings—were simulated to test the impact of different terms on simulated temperature distribution. The scenario simulations were compared to a control simulation, which included a constant wave-breaking coefficient, but otherwise was without any wave effects. The results indicate a pronounced effect of waves on surface temperature, on the distribution of vertical temperature and on upwelling's. Overall, when all three wave effects were accounted for, did the estimates of temperature improve compared to control simulation. During the summer, the wave-induced water temperature changes were up to 1 °C. In northern parts of the Baltic Sea, a warming of the surface layer occurs in the wave included simulations in summer months. This in turn reduces the cold bias between simulated and measured data, e.g. the control simulation was too cold compared to measurements. The warming is related to sea-state dependent energy flux. This implies that a spatio-temporally varying wave-breaking coefficient is necessary, because it depends on actual sea state. Wave-induced cooling is mostly observed in near-coastal areas and is the result of intensified upwelling in the scenario, when Stokes-Coriolis forcing is accounted for. Accounting for sea-state dependent momentum flux results in modified heat exchange at the water-air boundary which consequently leads to warming of surface water compared to control simulation.

Role of the Atlantic Multidecadal Variability on extreme climate conditions over North America

NASA Astrophysics Data System (ADS)

Ruprich-Robert, Yohan; Delworth, Thomas; Msadek, Rym; Castruccio, Frederic; Yeager, Stephen; Danabasoglu, Gokhan

2017-04-01

The Atlantic Multidecadal Variability (AMV) is associated with marked modulations of climate anomalies observed over many areas of the globe like droughts, decline in sea ice or changes in the atmospheric circulation. However, the shortness of the historical observations compared to the AMV period ( 60-80yr) makes it difficult to show that the AMV is a direct driver of these variations. To isolate the AMV climate response, we use a suite of global coupled models from GFDL and NCAR, in which the North Atlantic sea surface temperatures are restored to the observed AMV pattern, while the other ocean basins are left fully coupled. In order to explore and robustly isolate the AMV impacts on extreme events, we use large ensemble simulations (between 30 and 100 members depending on the model) that are integrated for 10 years. We investigate the importance of model resolution by analyzing GFDL models that vary in their atmospheric resolution and we assess the robustness of the results by comparing them to similar experiments performed with the NCAR coupled model. Further, we investigate the influence of model surface temperature biases on the simulated AMV teleconnections using a flux-adjusted experiment based on a model configuration that corrects for momentum, enthalpy and freshwater fluxes. We focus in this presentation on the impact of the AMV on the occurrence of the North American heat waves. We find that the AMV modulates by about 30% the occurrence of heat waves over North Mexico and the South-West of USA, with more heat waves during a warm phase of the AMV. The main reason for such an increase is that, during a warm AMV phase, the anomalously warm sea surface temperature leads to an increase of the atmospheric convection over the tropical Atlantic, as well as to a an anomalous downward motion over North America. This atmospheric response to AMV inhibits the precipitation over there and drives a deficit of soil moisture. In the summer, the latent heat of evaporation usually cools the surface precluding strong surface temperature warming. But the lack of soil moisture allows less evaporation, which leads to positive surface temperature anomalies and an increase of the occurrence of heat waves. By comparing the results from all the model configurations, we highlight the importance of the representation of the soil moisture by the model on the modulation of heat waves by the AMV. We also stress the influence of model's mean state biases on the simulated AMV impacts.

A Coastal Seawater Temperature Dataset for Biogeographical Studies: Large Biases between In Situ and Remotely-Sensed Data Sets around the Coast of South Africa

PubMed Central

Smit, Albertus J.; Roberts, Michael; Anderson, Robert J.; Dufois, Francois; Dudley, Sheldon F. J.; Bornman, Thomas G.; Olbers, Jennifer; Bolton, John J.

2013-01-01

Gridded SST products developed particularly for offshore regions are increasingly being applied close to the coast for biogeographical applications. The purpose of this paper is to demonstrate the dangers of doing so through a comparison of reprocessed MODIS Terra and Pathfinder v5.2 SSTs, both at 4 km resolution, with instrumental in situ temperatures taken within 400 m from the coast. We report large biases of up to +6°C in places between satellite-derived and in situ climatological temperatures for 87 sites spanning the entire ca. 2 700 km of the South African coastline. Although biases are predominantly warm (i.e. the satellite SSTs being higher), smaller or even cold biases also appear in places, especially along the southern and western coasts of the country. We also demonstrate the presence of gradients in temperature biases along shore-normal transects — generally SSTs extracted close to the shore demonstrate a smaller bias with respect to the in situ temperatures. Contributing towards the magnitude of the biases are factors such as SST data source, proximity to the shore, the presence/absence of upwelling cells or coastal embayments. Despite the generally large biases, from a biogeographical perspective, species distribution retains a correlative relationship with underlying spatial patterns in SST, but in order to arrive at a causal understanding of the determinants of biogeographical patterns we suggest that in shallow, inshore marine habitats, temperature is best measured directly. PMID:24312609

Multiple-Point Temperature Gradient Algorithm for Ring Laser Gyroscope Bias Compensation

PubMed Central

Li, Geng; Zhang, Pengfei; Wei, Guo; Xie, Yuanping; Yu, Xudong; Long, Xingwu

2015-01-01

To further improve ring laser gyroscope (RLG) bias stability, a multiple-point temperature gradient algorithm is proposed for RLG bias compensation in this paper. Based on the multiple-point temperature measurement system, a complete thermo-image of the RLG block is developed. Combined with the multiple-point temperature gradients between different points of the RLG block, the particle swarm optimization algorithm is used to tune the support vector machine (SVM) parameters, and an optimized design for selecting the thermometer locations is also discussed. The experimental results validate the superiority of the introduced method and enhance the precision and generalizability in the RLG bias compensation model. PMID:26633401

Synthesis and magnetic properties of single-crystalline Na2-xMn8O16 nanorods

PubMed Central

2011-01-01

The synthesis of single-crystalline hollandite-type manganese oxides Na2-xMn8O16 nanorods by a simple molten salt method is reported for the first time. The nanorods were characterized by powder X-ray diffraction, scanning electron microscopy, transmission electron microscopy, and a superconducting quantum interference device magnetometer. The magnetic measurements indicated that the nanorods showed spin glass behavior and exchange bias effect at low temperatures. The low-temperature magnetic behaviors can be explained by the uncompensated spins on the surface of the nanorods. PMID:21711626

Scanning tunneling microscopy and spectroscopy studies of the heavy-electron superconductor TlNi2Se2

NASA Astrophysics Data System (ADS)

Wilfert, Stefan; Schmitt, Martin; Schmidt, Henrik; Mauerer, Tobias; Sessi, Paolo; Wang, Hangdong; Mao, Qianhui; Fang, Minghu; Bode, Matthias

2018-01-01

We report on the structural and superconducting electronic properties of the heavy-electron superconductor TlNi2Se2 . By using a variable-temperature scanning tunneling microscopy (VT-STM) the coexistence of (√{2 }×√{2 }) R 45∘ and (2 ×1 ) surface reconstructions is observed. Similar to earlier observations on the "122" family of Fe-based superconductors, we find that their respective surface fraction strongly depends on the temperature during cleavage, the measurement temperature, and the sample's history. Cleaving at low temperature predominantly results in the (√{2 }×√{2 }) R 45∘ -reconstructed surface. A detailed analysis of the (√{2 }×√{2 }) R 45∘ -reconstructed domains identifies (2 ×1 ) -ordered dimers, tertramers, and higher order even multimers as domain walls. Higher cleaving temperatures and the warming of low-temperature-cleaved samples increases the relative weight of the (2 ×1 ) surface reconstruction. By slowly increasing the sample temperature Ts inside the VT-STM we find that the (√{2 }×√{2 }) R 45∘ surface reconstructions transforms into the (2 ×1 ) structure at Ts=123 K. We identify the polar nature of the TlNi2Se2 (001) surface as the most probable driving mechanism of the two reconstructions, as both lead to a charge density ρ =0.5 e- , thereby avoiding divergent electrostatic potentials and the resulting "polar catastrophe." Low-temperature scanning tunneling spectroscopy (STS) performed with normal metal and superconducting probe tips shows a superconducting gap which is best fit with an isotropic s wave. We could not detect any correlation between the local surface reconstruction, suggesting that the superconductivity is predominantly governed by TlNi2Se2 bulk properties. Correspondingly, temperature- and field-dependent data reveal that both the critical temperature and critical magnetic field are in good agreement with bulk values obtained earlier from transport measurements. In the superconducting state the formation of an Abrikosov lattice is observed without any zero bias anomaly at the vortex core.

FROM FOLDING THEORIES TO FOLDING PROTEINS: A Review and Assessment of Simulation Studies of Protein Folding and Unfolding

NASA Astrophysics Data System (ADS)

Shea, Joan-Emma; Brooks, Charles L., III

2001-10-01

Beginning with simplified lattice and continuum "minimalist" models and progressing to detailed atomic models, simulation studies have augmented and directed development of the modern landscape perspective of protein folding. In this review we discuss aspects of detailed atomic simulation methods applied to studies of protein folding free energy surfaces, using biased-sampling free energy methods and temperature-induced protein unfolding. We review studies from each on systems of particular experimental interest and assess the strengths and weaknesses of each approach in the context of "exact" results for both free energies and kinetics of a minimalist model for a beta-barrel protein. We illustrate in detail how each approach is implemented and discuss analysis methods that have been developed as components of these studies. We describe key insights into the relationship between protein topology and the folding mechanism emerging from folding free energy surface calculations. We further describe the determination of detailed "pathways" and models of folding transition states that have resulted from unfolding studies. Our assessment of the two methods suggests that both can provide, often complementary, details of folding mechanism and thermodynamics, but this success relies on (a) adequate sampling of diverse conformational regions for the biased-sampling free energy approach and (b) many trajectories at multiple temperatures for unfolding studies. Furthermore, we find that temperature-induced unfolding provides representatives of folding trajectories only when the topology and sequence (energy) provide a relatively funneled landscape and "off-pathway" intermediates do not exist.

The contrasting climate response to tropical and extratropical energy perturbations

NASA Astrophysics Data System (ADS)

Hawcroft, Matt; Haywood, Jim M.; Collins, Mat; Jones, Andy

2018-01-01

The link between cross-equatorial energy transport, the double-intertropical convergence zone (DI) problem and biases in tropical and extratropical albedo and energy budgets in climate models have been investigated in multiple studies, though DI biases persist in many models. Here, a coupled climate model, HadGEM2-ES, is used to investigate the response to idealised energy perturbations in the tropics and extratropics, in both the northern and southern hemispheres, through the imposition of stratospheric aerosols that reflect incoming radiation. The impact on the tropical climate of high and low latitude forcing strongly contrasts, with large changes in tropical precipitation and modulation of the DI bias when the tropics are cooled as precipitation moves away from the cooled hemisphere. These responses are muted when the extratropics are cooled, as the meridional energy transport anomalies that are excited by these energy budget anomalies are partitioned between the atmosphere and ocean. The results here highlight the persistence of the DI bias in HadGEM2-ES, indicating why little progress has been made in rectifying these problems through many generations of climate models. A highly linear relationship between cross-equatorial atmospheric energy transport, tropical precipitation asymmetry and tropical sea surface temperature biases is also demonstrated, giving some suggestion as to where improvements in these large scale, persistent biases may be achieved.

Unexpected Nonlinear Effects in Superconducting Transition-Edge Sensors

NASA Technical Reports Server (NTRS)

Sadleir, John

2016-01-01

When a normal metal transitions into the superconducting state the DC resistance drops from a finite value to zero over some finite transition width in temperature, current, and magnetic field. Superconducting transition-edge sensors (TESs) operate within this transition region and uses resistive changes to measure deposited thermal energy. This resistive transition is not perfectly smooth and a wide range of TES designs and materials show sub-structure in the resistive transition (as seen in smooth nonmonotonic behavior, jump discontinuities, and hysteresis in the devices current-voltage relation and derivatives of the resistance with respect to temperature, bias current, and magnetic field). TES technology has advanced to the point where for many applications this structure is the limiting factor in performance and optimization consists of finding operating points away from these structures. For example, operating at or near this structure can lead to nonlinearity in the detectors response and gain scale, limit the spectral range of the detector by limiting the usable resistive range, and degrade energy resolution. The origin of much of this substructure is unknown. This presentation investigates a number of possible sources in turn. First we model the TES as a superconducting weak-link and solve for the characteristic differential equations current and voltage time dependence. We find:(1) measured DC biased current-voltage relationship is the time-average of a much higher frequency limit cycle solution.(2) We calculate the fundamental frequency and estimate the power radiated from the TES treating the bias leads as an antennae.(3) The solution for a set of circuit parameters becomes multivalued leading to current transitions between levels.(4)The circuit parameters can change the measure resistance and mask the true critical current. As a consequence the TES resistance surface is not just a function of temperature, current, and magnetic field but is also a function of the circuit elements (such as shunt resistor, SQUID inductance, and capacitor values). In other words, same device measured in different electrical circuits will have a different resistive surface in temperature, current, and magnetic field. Next we consider that at the transition temperature of a superconductor both the magnetic penetration depth and coherence length are divergent. As a consequence these important characteristic length scales are changing with operating point. We present measurements on devices showing commensurate behavior between these characteristic lengths and the length scale of added normal metal structures. Reordering of proximity vortices leads to discontinuities and irreversibility of the current-voltage curves. Last we consider a weak-link TES including both thermal activated resistance effects and the effect of the magnetic penetration depth being a function of temperature and magnetic field. We derive its impact on the resistive transition surface and the important device parameters a and b.

Infrared and Passive Microwave Radiometric Sea Surface Temperatures and Their Relationships to Atmospheric Forcing

NASA Technical Reports Server (NTRS)

Castro, Sandra L.

2004-01-01

The current generation of infrared (IR) and passive microwave (MW) satellite sensors provides highly complementary information for monitoring sea surface temperature (SST). On the one hand, infrared sensors provide high resolution and high accuracy but are obscured by clouds. Microwave sensors on the other hand, provide coverage through non-precipitating clouds but have coarser resolution and generally poorer accuracy. Assuming that the satellite SST measurements do not have spatially variable biases, they can be blended combining the merits of both SST products. These factors have motivated recent work in blending the MW and IR data in an attempt to produce high-accuracy SST products with improved coverage in regions with persistent clouds. The primary sources of retrieval uncertainty are, however, different for the two sensors. The main uncertainty in the MW retrievals lies in the effects of wind-induced surface roughness and foam on emissivity, whereas the IR retrievals are more sensitive to the atmospheric water vapor and aerosol content. Average nighttime differences between the products for the month periods of January 1999 and June 2000 are shown. These maps show complex spatial and temporal differences as indicated by the strong spatially coherent features in the product differences and the changes between seasons. Clearly such differences need to be understood and accounted for if the products are to be combined. The overall goals of this project are threefold: (1) To understand the sources of uncertainty in the IR and MW SST retrievals and to characterize the errors affecting the two types of retrieval as a fiction of atmospheric forcing; (2) To demonstrate how representative the temperature difference between the two satellite products is of Delta T; (3) To apply bias adjustments and to device a comprehensive treatment of the behavior of the temperature difference across the oceanic skin layer to determine the best method for blending thermal infrared and passive microwave measurements of SSTs.

Comparison of Nimbus-7 SMMR and GOES-1 VISSR Atmospheric Liquid Water Content.

NASA Astrophysics Data System (ADS)

Lojou, Jean-Yves; Frouin, Robert; Bernard, René

1991-02-01

Vertically integrated atmospheric liquid water content derived from Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR) brightness temperatures and from GOES-1 Visible and Infrared Spin-Scan Radiometer (VISSR) radiances in the visible are compared over the Indian Ocean during MONEX (monsoon experiment). In the retrieval procedure, Wilheit and Chang' algorithm and Stephens' parameterization schemes are applied to the SMMR and VISSR data, respectively. The results indicate that in the 0-100 mg cm2 range of liquid water content considered, the correlation coefficient between the two types of estimates is 0.83 (0.81- 0.85 at the 99 percent confidence level). The Wilheit and Chang algorithm, however, yields values lower than those obtained with Stephens's schemes by 24.5 mg cm2 on the average, and occasionally the SMMR-based values are negative. Alternative algorithms are proposed for use with SMMR data, which eliminate the bias, augment the correlation coefficient, and reduce the rms difference. These algorithms include using the Witheit and Chang formula with modified coefficients (multilinear regression), the Wilheit and Chang formula with the same coefficients but different equivalent atmospheric temperatures for each channel (temperature bias adjustment), and a second-order polynomial in brightness temperatures at 18, 21, and 37 GHz (polynomial development). When applied to a dataset excluded from the regressionn dataset, the multilinear regression algorithm provides the best results, namely a 0.91 correlation coefficient, a 5.2 mg cm2 (residual) difference, and a 2.9 mg cm2 bias. Simply shifting the liquid water content predicted by the Wilheit and Chang algorithm does not yield as good comparison statistics, indicating that the occasional negative values are not due only to a bias. The more accurate SMMR-derived liquid water content allows one to better evaluate cloud transmittance in the solar spectrum, at least in the area and during the period analyzed. Combining this cloud transmittance with a clear sky model would provide ocean surface insulation estimates from SMMR data alone.

First principles investigation of heterogeneous catalysis on metal oxide surfaces

NASA Astrophysics Data System (ADS)

Ghoussoub, Mireille

Metal oxides possess unique electronic and structural properties that render them highly favourable for applications in heterogeneous catalysis. In this study, computational atomistic modelling based on Density Functional Theory was used to investigate the reduction of carbon dioxide over hydroxylated indium oxide nanoparticles, as well at the activation of methane over oxygen-covered bimetallic surfaces. The first study employed metadynamics-biased ab initio molecular dynamics to obtain the free energy surface of the various reaction steps at finite temperature. In the second study, the nudged elastic band method was used to probe the C-H activation mechanisms for different surface configurations. In both cases, activation energies, reaction energies, transition state structures, and charge analysis results are used to explain the underlying mechanistic pathways.

RF plasma MOCVD of Y2O3 thin films: Effect of RF self-bias on the substrates during deposition

NASA Astrophysics Data System (ADS)

Chopade, S. S.; Barve, S. A.; Thulasi Raman, K. H.; Chand, N.; Deo, M. N.; Biswas, A.; Rai, Sanjay; Lodha, G. S.; Rao, G. M.; Patil, D. S.

2013-11-01

Yttrium oxide (Y2O3) thin films have been deposited by radio frequency plasma assisted metal organic chemical vapor deposition (MOCVD) process using (2,2,6,6-tetramethyl-3,5-heptanedionate) yttrium (commonly known as Y(thd)3) precursor in a plasma of argon and oxygen gases at a substrate temperature of 350 °C. The films have been deposited under influence of varying RF self-bias (-50 V to -175 V) on silicon, quartz, stainless steel and tantalum substrates. The deposited coatings are characterized by glancing angle X-ray diffraction (GIXRD), Fourier transform infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS), spectroscopic ellipsometry and scanning electron microscopy (SEM). GIXRD and FTIR results indicate deposition of Y2O3 (BCC structure) in all cases. However, XPS results indicate nonstoichiometric cubic phase deposition on the surface of deposited films. The degree of nonstoichiometry varies with bias during deposition. Ellipsometry results indicate that the refractive index for the deposited films is varying from 1.70 to 1.83 that is typical for Y2O3. All films are transparent in the investigated wavelength range 300-1200 nm. SEM results indicate that the microstructure of the films is changing with applied bias. Results indicate that it is possible to deposit single phase cubic Y2O3 thin films at low substrate temperature by RF plasma MOCVD process. RF self-bias that decides about the energy of impinging ions on the substrates plays an important role in controlling the texture of deposited Y2O3 films on the substrates. Results indicate that to control the structure of films and its texture, it is important to control the bias on the substrate during deposition. The films deposited at high bias level show degradation in the crystallinity and reduction of thickness.

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.

Daily mean temperature estimate at the US SUFRAD stations as an average of the maximum and minimum temperatures

DOE PAGES

Chylek, Petr; Augustine, John A.; Klett, James D.; ...

2017-09-30

At thousands of stations worldwide, the mean daily surface air temperature is estimated as a mean of the daily maximum (T max) and minimum (T min) temperatures. In this paper, we use the NOAA Surface Radiation Budget Network (SURFRAD) of seven US stations with surface air temperature recorded each minute to assess the accuracy of the mean daily temperature estimate as an average of the daily maximum and minimum temperatures and to investigate how the accuracy of the estimate increases with an increasing number of daily temperature observations. We find the average difference between the estimate based on an averagemore » of the maximum and minimum temperatures and the average of 1440 1-min daily observations to be - 0.05 ± 1.56 °C, based on analyses of a sample of 238 days of temperature observations. Considering determination of the daily mean temperature based on 3, 4, 6, 12, or 24 daily temperature observations, we find that 2, 4, or 6 daily observations do not reduce significantly the uncertainty of the daily mean temperature. The bias reduction in a statistically significant manner (95% confidence level) occurs only with 12 or 24 daily observations. The daily mean temperature determination based on 24 hourly observations reduces the sample daily temperature uncertainty to - 0.01 ± 0.20 °C. Finally, estimating the parameters of population of all SURFRAD observations, the 95% confidence intervals based on 24 hourly measurements is from - 0.025 to 0.004 °C, compared to a confidence interval from - 0.15 to 0.05 °C based on the mean of T max and T min.« less

Daily mean temperature estimate at the US SUFRAD stations as an average of the maximum and minimum temperatures

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

Chylek, Petr; Augustine, John A.; Klett, James D.

At thousands of stations worldwide, the mean daily surface air temperature is estimated as a mean of the daily maximum (T max) and minimum (T min) temperatures. In this paper, we use the NOAA Surface Radiation Budget Network (SURFRAD) of seven US stations with surface air temperature recorded each minute to assess the accuracy of the mean daily temperature estimate as an average of the daily maximum and minimum temperatures and to investigate how the accuracy of the estimate increases with an increasing number of daily temperature observations. We find the average difference between the estimate based on an averagemore » of the maximum and minimum temperatures and the average of 1440 1-min daily observations to be - 0.05 ± 1.56 °C, based on analyses of a sample of 238 days of temperature observations. Considering determination of the daily mean temperature based on 3, 4, 6, 12, or 24 daily temperature observations, we find that 2, 4, or 6 daily observations do not reduce significantly the uncertainty of the daily mean temperature. The bias reduction in a statistically significant manner (95% confidence level) occurs only with 12 or 24 daily observations. The daily mean temperature determination based on 24 hourly observations reduces the sample daily temperature uncertainty to - 0.01 ± 0.20 °C. Finally, estimating the parameters of population of all SURFRAD observations, the 95% confidence intervals based on 24 hourly measurements is from - 0.025 to 0.004 °C, compared to a confidence interval from - 0.15 to 0.05 °C based on the mean of T max and T min.« less

Comparing regional precipitation and temperature extremes in climate model and reanalysis products

DOE PAGES

Angélil, Oliver; Perkins-Kirkpatrick, Sarah; Alexander, Lisa V.; ...

2016-07-12

A growing field of research aims to characterise the contribution of anthropogenic emissions to the likelihood of extreme weather and climate events. These analyses can be sensitive to the shapes of the tails of simulated distributions. If tails are found to be unrealistically short or long, the anthropogenic signal emerges more or less clearly, respectively, from the noise of possible weather. Here we compare the chance of daily land-surface precipitation and near-surface temperature extremes generated by three Atmospheric Global Climate Models typically used for event attribution, with distributions from six reanalysis products. The likelihoods of extremes are compared for area-averagesmore » over grid cell and regional sized spatial domains. Results suggest a bias favouring overly strong attribution estimates for hot and cold events over many regions of Africa and Australia, and a bias favouring overly weak attribution estimates over regions of North America and Asia. For rainfall, results are more sensitive to geographic location. Although the three models show similar results over many regions, they do disagree over others. Equally, results highlight the discrepancy amongst reanalyses products. This emphasises the importance of using multiple reanalysis and/or observation products, as well as multiple models in event attribution studies.« less

Downscaling GISS ModelE Boreal Summer Climate over Africa

NASA Technical Reports Server (NTRS)

Druyan, Leonard M.; Fulakeza, Matthew

2015-01-01

The study examines the perceived added value of downscaling atmosphere-ocean global climate model simulations over Africa and adjacent oceans by a nested regional climate model. NASA/Goddard Institute for Space Studies (GISS) coupled ModelE simulations for June- September 1998-2002 are used to form lateral boundary conditions for synchronous simulations by the GISS RM3 regional climate model. The ModelE computational grid spacing is 2deg latitude by 2.5deg longitude and the RM3 grid spacing is 0.44deg. ModelE precipitation climatology for June-September 1998-2002 is shown to be a good proxy for 30-year means so results based on the 5-year sample are presumed to be generally representative. Comparison with observational evidence shows several discrepancies in ModelE configuration of the boreal summer inter-tropical convergence zone (ITCZ). One glaring shortcoming is that ModelE simulations do not advance the West African rain band northward during the summer to represent monsoon precipitation onset over the Sahel. Results for 1998-2002 show that onset simulation is an important added value produced by downscaling with RM3. ModelE Eastern South Atlantic Ocean computed sea-surface temperatures (SST) are some 4 K warmer than reanalysis, contributing to large positive biases in overlying surface air temperatures (Tsfc). ModelE Tsfc are also too warm over most of Africa. RM3 downscaling somewhat mitigates the magnitude of Tsfc biases over the African continent, it eliminates the ModelE double ITCZ over the Atlantic and it produces more realistic orographic precipitation maxima. Parallel ModelE and RM3 simulations with observed SST forcing (in place of the predicted ocean) lower Tsfc errors but have mixed impacts on circulation and precipitation biases. Downscaling improvements of the meridional movement of the rain band over West Africa and the configuration of orographic precipitation maxima are realized irrespective of the SST biases.

Dynamical downscaling with the fifth-generation Canadian regional climate model (CRCM5) over the CORDEX Arctic domain: effect of large-scale spectral nudging and of empirical correction of sea-surface temperature

NASA Astrophysics Data System (ADS)

Takhsha, Maryam; Nikiéma, Oumarou; Lucas-Picher, Philippe; Laprise, René; Hernández-Díaz, Leticia; Winger, Katja

2017-10-01

As part of the CORDEX project, the fifth-generation Canadian Regional Climate Model (CRCM5) is used over the Arctic for climate simulations driven by reanalyses and by the MPI-ESM-MR coupled global climate model (CGCM) under the RCP8.5 scenario. The CRCM5 shows adequate skills capturing general features of mean sea level pressure (MSLP) for all seasons. Evaluating 2-m temperature (T2m) and precipitation is more problematic, because of inconsistencies between observational reference datasets over the Arctic that suffer of a sparse distribution of weather stations. In our study, we additionally investigated the effect of large-scale spectral nudging (SN) on the hindcast simulation driven by reanalyses. The analysis shows that SN is effective in reducing the spring MSLP bias, but otherwise it has little impact. We have also conducted another experiment in which the CGCM-simulated sea-surface temperature (SST) is empirically corrected and used as lower boundary conditions over the ocean for an atmosphere-only global simulation (AGCM), which in turn provides the atmospheric lateral boundary conditions to drive the CRCM5 simulation. This approach, so-called 3-step approach of dynamical downscaling (CGCM-AGCM-RCM), which had considerably improved the CRCM5 historical simulations over Africa, exhibits reduced impact over the Arctic domain. The most notable positive effect over the Arctic is a reduction of the T2m bias over the North Pacific Ocean and the North Atlantic Ocean in all seasons. Future projections using this method are compared with the results obtained with the traditional 2-step dynamical downscaling (CGCM-RCM) to assess the impact of correcting systematic biases of SST upon future-climate projections. The future projections are mostly similar for the two methods, except for precipitation.

Four dimensional data assimilation (FDDA) impacts on WRF performance in simulating inversion layer structure and distributions of CMAQ-simulated winter ozone concentrations in Uintah Basin

NASA Astrophysics Data System (ADS)

Tran, Trang; Tran, Huy; Mansfield, Marc; Lyman, Seth; Crosman, Erik

2018-03-01

Four-dimensional data assimilation (FDDA) was applied in WRF-CMAQ model sensitivity tests to study the impact of observational and analysis nudging on model performance in simulating inversion layers and O3 concentration distributions within the Uintah Basin, Utah, U.S.A. in winter 2013. Observational nudging substantially improved WRF model performance in simulating surface wind fields, correcting a 10 °C warm surface temperature bias, correcting overestimation of the planetary boundary layer height (PBLH) and correcting underestimation of inversion strengths produced by regular WRF model physics without nudging. However, the combined effects of poor performance of WRF meteorological model physical parameterization schemes in simulating low clouds, and warm and moist biases in the temperature and moisture initialization and subsequent simulation fields, likely amplified the overestimation of warm clouds during inversion days when observational nudging was applied, impacting the resulting O3 photochemical formation in the chemistry model. To reduce the impact of a moist bias in the simulations on warm cloud formation, nudging with the analysis water mixing ratio above the planetary boundary layer (PBL) was applied. However, due to poor analysis vertical temperature profiles, applying analysis nudging also increased the errors in the modeled inversion layer vertical structure compared to observational nudging. Combining both observational and analysis nudging methods resulted in unrealistically extreme stratified stability that trapped pollutants at the lowest elevations at the center of the Uintah Basin and yielded the worst WRF performance in simulating inversion layer structure among the four sensitivity tests. The results of this study illustrate the importance of carefully considering the representativeness and quality of the observational and model analysis data sets when applying nudging techniques within stable PBLs, and the need to evaluate model results on a basin-wide scale.

Community Radiative Transfer Model for Inter-Satellites Calibration and Verification

NASA Astrophysics Data System (ADS)

Liu, Q.; Nalli, N. R.; Ignatov, A.; Garrett, K.; Chen, Y.; Weng, F.; Boukabara, S. A.; van Delst, P. F.; Groff, D. N.; Collard, A.; Joseph, E.; Morris, V. R.; Minnett, P. J.

2014-12-01

Developed at the Joint Center for Satellite Data Assimilation, the Community Radiative Transfer Model (CRTM) [1], operationally supports satellite radiance assimilation for weather forecasting. The CRTM also supports JPSS/NPP and GOES-R missions [2] for instrument calibration, validation, monitoring long-term trending, and satellite retrieved products [3]. The CRTM is used daily at the NOAA NCEP to quantify the biases and standard deviations between radiance simulations and satellite radiance measurements in a time series and angular dependency. The purposes of monitoring the data assimilation system are to ensure the proper performance of the assimilation system and to diagnose problems with the system for future improvements. The CRTM is a very useful tool for cross-sensor verifications. Using the double difference method, it can remove the biases caused by slight differences in spectral response and geometric angles between measurements of the two instruments. The CRTM is particularly useful to reduce the difference between instruments for climate studies [4]. In this study, we will carry out the assessment of the Suomi National Polar-orbiting Partnership (SNPP) [5] Cross-track Infrared Sounder (CrIS) data [6], Advanced Technology Microwave Sounder (ATMS) data, and data for Visible Infrared Imaging Radiometer Suite (VIIRS) [7][8] thermal emissive bands. We use dedicated radiosondes and surface data acquired from NOAA Aerosols and Ocean Science Expeditions (AEROSE) [9]. The high quality radiosondes were launched when Suomi NPP flew over NOAA Ship Ronald H. Brown situated in the tropical Atlantic Ocean. The atmospheric data include profiles of temperature, water vapor, and ozone, as well as total aerosol optical depths. The surface data includes air temperature and humidity at 2 meters, skin temperature (Marine Atmospheric Emitted Radiance Interferometer, M-AERI [10]), surface temperature, and surface wind vector. [1] Liu, Q., and F. Weng, 2006: JAS [2] Liu, Q., and S. Boukabara, 2013: RSE [3] Boukabara et al., 2011: TGARS [4] Wang, LK, Zou C-Z. 2013: JGR [5] Weng et al, 2012: JGR [6] Han, Y., et al., 2013: JGR [7] Caoet al, 2013: GR [8] Liang, X, A. Ignatov, 2013: JGR [9] Nalliet al 2011: BAMS [10] Minnett et al, 2001: JAOT

Laser-Assisted Field Evaporation and Three-Dimensional Atom-by-Atom Mapping of Diamond Isotopic Homojunctions.

PubMed

Mukherjee, Samik; Watanabe, Hideyuki; Isheim, Dieter; Seidman, David N; Moutanabbir, Oussama

2016-02-10

It addition to its high evaporation field, diamond is also known for its limited photoabsorption, strong covalent bonding, and wide bandgap. These characteristics have been thought for long to also complicate the field evaporation of diamond and make its control hardly achievable on the atomistic-level. Herein, we demonstrate that the unique behavior of nanoscale diamond and its interaction with pulsed laser lead to a controlled field evaporation thus enabling three-dimensional atom-by-atom mapping of diamond (12)C/(13)C homojunctions. We also show that one key element in this process is to operate the pulsed laser at high energy without letting the dc bias increase out of bounds for diamond nanotip to withstand. Herein, the role of the dc bias in evaporation of diamond is essentially to generate free charge carriers within the nanotip via impact ionization. The mobile free charges screen the internal electric field, eventually creating a hole rich surface where the pulsed laser is effectively absorbed leading to an increase in the nanotip surface temperature. The effect of this temperature on the uncertainty in the time-of-flight of an ion, the diffusion of atoms on the surface of the nanotip, is also discussed. In addition to paving the way toward a precise manipulation of isotopes in diamond-based nanoscale and quantum structures, this result also elucidates some of the basic properties of dielectric nanostructures under high electric field.

The Systematic Bias of Ingestible Core Temperature Sensors Requires a Correction by Linear Regression.

PubMed

Hunt, Andrew P; Bach, Aaron J E; Borg, David N; Costello, Joseph T; Stewart, Ian B

2017-01-01

An accurate measure of core body temperature is critical for monitoring individuals, groups and teams undertaking physical activity in situations of high heat stress or prolonged cold exposure. This study examined the range in systematic bias of ingestible temperature sensors compared to a certified and traceable reference thermometer. A total of 119 ingestible temperature sensors were immersed in a circulated water bath at five water temperatures (TEMP A: 35.12 ± 0.60°C, TEMP B: 37.33 ± 0.56°C, TEMP C: 39.48 ± 0.73°C, TEMP D: 41.58 ± 0.97°C, and TEMP E: 43.47 ± 1.07°C) along with a certified traceable reference thermometer. Thirteen sensors (10.9%) demonstrated a systematic bias > ±0.1°C, of which 4 (3.3%) were > ± 0.5°C. Limits of agreement (95%) indicated that systematic bias would likely fall in the range of -0.14 to 0.26°C, highlighting that it is possible for temperatures measured between sensors to differ by more than 0.4°C. The proportion of sensors with systematic bias > ±0.1°C (10.9%) confirms that ingestible temperature sensors require correction to ensure their accuracy. An individualized linear correction achieved a mean systematic bias of 0.00°C, and limits of agreement (95%) to 0.00-0.00°C, with 100% of sensors achieving ±0.1°C accuracy. Alternatively, a generalized linear function (Corrected Temperature (°C) = 1.00375 × Sensor Temperature (°C) - 0.205549), produced as the average slope and intercept of a sub-set of 51 sensors and excluding sensors with accuracy outside ±0.5°C, reduced the systematic bias to < ±0.1°C in 98.4% of the remaining sensors ( n = 64). In conclusion, these data show that using an uncalibrated ingestible temperature sensor may provide inaccurate data that still appears to be statistically, physiologically, and clinically meaningful. Correction of sensor temperature to a reference thermometer by linear function eliminates this systematic bias (individualized functions) or ensures systematic bias is within ±0.1°C in 98% of the sensors (generalized function).

Free energy surface of an intrinsically disordered protein: comparison between temperature replica exchange molecular dynamics and bias-exchange metadynamics.

PubMed

Zerze, Gül H; Miller, Cayla M; Granata, Daniele; Mittal, Jeetain

2015-06-09

Intrinsically disordered proteins (IDPs), which are expected to be largely unstructured under physiological conditions, make up a large fraction of eukaryotic proteins. Molecular dynamics simulations have been utilized to probe structural characteristics of these proteins, which are not always easily accessible to experiments. However, exploration of the conformational space by brute force molecular dynamics simulations is often limited by short time scales. Present literature provides a number of enhanced sampling methods to explore protein conformational space in molecular simulations more efficiently. In this work, we present a comparison of two enhanced sampling methods: temperature replica exchange molecular dynamics and bias exchange metadynamics. By investigating both the free energy landscape as a function of pertinent order parameters and the per-residue secondary structures of an IDP, namely, human islet amyloid polypeptide, we found that the two methods yield similar results as expected. We also highlight the practical difference between the two methods by describing the path that we followed to obtain both sets of data.

Importance of understanding landscape biases in USGS gage locations: Implications and solutions for managers

USGS Publications Warehouse

Wagner, Tyler; DeWeber, Jefferson Tyrell; Tsang, Yin-Phan; Krueger, Damon; Whittier, Joanna B.; Infante, Dana M.; Whelan, Gary

2014-01-01

Flow and water temperature are fundamental properties of stream ecosystems upon which many freshwater resource management decisions are based. U.S. Geological Survey (USGS) gages are the most important source of streamflow and water temperature data available nationwide, but the degree to which gages represent landscape attributes of the larger population of streams has not been thoroughly evaluated. We identified substantial biases for seven landscape attributes in one or more regions across the conterminous United States. Streams with small watersheds (<10 km2) and at high elevations were often underrepresented, and biases were greater for water temperature gages and in arid regions. Biases can fundamentally alter management decisions and at a minimum this potential for error must be acknowledged accurately and transparently. We highlight three strategies that seek to reduce bias or limit errors arising from bias and illustrate how one strategy, supplementing USGS data, can greatly reduce bias.

Evaluation and analysis of Seasat-A Scanning multichannel Microwave radiometer (SMMR) Antenna Pattern Correction (APC) algorithm. Sub-task 2: T sub B measured vs. T sub B calculated comparison results

NASA Technical Reports Server (NTRS)

Kitzis, J. L.; Kitzis, S. N.

1979-01-01

Interim Antenna Pattern Correction (APC) brightness temperature measurements for all ten SMMR channels are compared with calculated values generated from surface truth data. Plots and associated statistics are presented for the available points of coincidence between SMMR and surface truth measurements acquired for the Gulf of Alaska SEASAT Experiment. The most important conclusions of the study deal with the apparent existence of different instrument biases for each SMMR channel, and their variation across the scan.

Good News for Borehole Climatology

NASA Astrophysics Data System (ADS)

Rath, Volker; Fidel Gonzalez-Rouco, J.; Goosse, Hugues

2010-05-01

Though the investigation of observed borehole temperatures has proved to be a valuable tool for the reconstruction of ground surface temperature histories, there are many open questions concerning the significance and accuracy of the reconstructions from these data. In particular, the temperature signal of the warming after the Last glacial Maximum (LGM) is still present in borehole temperature profiles. It influences the relatively shallow boreholes used in current paleoclimate inversions to estimate temperature changes in the last centuries. This is shown using Monte Carlo experiments on past surface temperature change, using plausible distributions for the most important parameters, i.e.,amplitude and timing of the glacial-interglacial transition, the prior average temperature, and petrophysical properties. It has been argued that the signature of the last glacial-interglacial transition could be responsible for the high amplitudes of millennial temperature reconstructions. However, in shallow boreholes the additional effect of past climate can reasonably approximated by a linear variation of temperature with depth, and thus be accommodated by a "biased" background heat flow. This is good news for borehole climate, but implies that the geological heat flow values have to be interpreted accordingly. Borehole climate reconstructions from these shallow are most probably underestimating past variability due to the diffusive character of the heat conduction process, and the smoothness constraints necessary for obtaining stable solutions of this ill-posed inverse problem. A simple correction based on subtracting an appropriate prior surface temperature history shows promising results reducing these errors considerably, also with deeper boreholes, where the heat flow signal can not be approximated linearly, and improves the comparisons with AOGCM modeling results.

On improving cold region hydrological processes in the Canadian Land Surface Scheme

NASA Astrophysics Data System (ADS)

Ganji, Arman; Sushama, Laxmi; Verseghy, Diana; Harvey, Richard

2017-01-01

Regional and global climate model simulated streamflows for high-latitude regions show systematic biases, particularly in the timing and magnitude of spring peak flows. Though these biases could be related to the snow water equivalent and spring temperature biases in models, a good part of these biases is due to the unaccounted effects of non-uniform infiltration capacity of the frozen ground and other related processes. In this paper, the treatment of frozen water in the Canadian Land Surface Scheme (CLASS), which is used in the Canadian regional and global climate models, is modified to include fractional permeable area, supercooled liquid water and a new formulation for hydraulic conductivity. The impact of these modifications on the regional hydrology, particularly streamflow, is assessed by comparing three simulations performed with the original and two modified versions of CLASS, driven by atmospheric forcing data from the European Centre for Medium-Range Weather Forecast (ECMWF) reanalysis (ERA-Interim) for the 1990-2001 period over a northeast Canadian domain. The two modified versions of CLASS differ in the soil hydraulic conductivity and matric potential formulations, with one version being based on formulations from a previous study and the other one is newly proposed. Results suggest statistically significant decreases in infiltration and therefore soil moisture during the snowmelt season for the simulation with the new hydraulic conductivity and matric potential formulations and fractional permeable area concept compared to the original version of CLASS, which is also reflected in the increased spring surface runoff and streamflows in this simulation with modified CLASS over most of the study domain. The simulated spring peaks and their timing in this simulation are also in better agreement to those observed. This study thus demonstrates the importance of treatment of frozen water for realistic simulation of streamflows.

System and circuitry to provide stable transconductance for biasing

NASA Technical Reports Server (NTRS)

Garverick, Steven L. (Inventor); Yu, Xinyu (Inventor)

2012-01-01

An amplifier system can include an input amplifier configured to receive an analog input signal and provide an amplified signal corresponding to the analog input signal. A tracking loop is configured to employ delta modulation for tracking the amplified signal, the tracking loop providing a corresponding output signal. A biasing circuit is configured to adjust a bias current to maintain stable transconductance over temperature variations, the biasing circuit providing at least one bias signal for biasing at least one of the input amplifier and the tracking loop, whereby the circuitry receiving the at least one bias signal exhibits stable performance over the temperature variations. In another embodiment the biasing circuit can be utilized in other applications.

Design and Testing of an Automated System using Thermochromatic Liquid Crystals to Determine Local Heat Transfer Coefficients for an Impinging Jet

NASA Technical Reports Server (NTRS)

Tan, Benjamin

1995-01-01

Using thermochromatic liquid crystal to measure surface temperature, an automated transient method with time-varying free-stream temperature is developed to determine local heat transfer coefficients. By allowing the free-stream temperature to vary with time, the need for complicated mechanical components to achieve a step temperature change is eliminated, and by using the thermochromatic liquid crystals as temperature indicators, the labor intensive task of installing many thermocouples is omitted. Bias associated with human perception of the transition of the thermochromatic liquid crystal is eliminated by using a high speed digital camera and a computer. The method is validated by comparisons with results obtained by the steady-state method for a circular Jet impinging on a flat plate. Several factors affecting the accuracy of the method are evaluated.

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

Steigies, C. T.; Barjatya, A.

Langmuir probes are standard instruments for plasma density measurements on many sounding rockets. These probes can be operated in swept-bias as well as in fixed-bias modes. In swept-bias Langmuir probes, contamination effects are frequently visible as a hysteresis between consecutive up and down voltage ramps. This hysteresis, if not corrected, leads to poorly determined plasma densities and temperatures. With a properly chosen sweep function, the contamination parameters can be determined from the measurements and correct plasma parameters can then be determined. In this paper, we study the contamination effects on fixed-bias Langmuir probes, where no hysteresis type effect is seenmore » in the data. Even though the contamination is not evident from the measurements, it does affect the plasma density fluctuation spectrum as measured by the fixed-bias Langmuir probe. We model the contamination as a simple resistor-capacitor circuit between the probe surface and the plasma. We find that measurements of small scale plasma fluctuations (meter to sub-meter scale) along a rocket trajectory are not affected, but the measured amplitude of large scale plasma density variation (tens of meters or larger) is attenuated. From the model calculations, we determine amplitude and cross-over frequency of the contamination effect on fixed-bias probes for different contamination parameters. The model results also show that a fixed bias probe operating in the ion-saturation region is affected less by contamination as compared to a fixed bias probe operating in the electron saturation region.« less

Low leakage current Ni/CdZnTe/In diodes for X/ γ-ray detectors

NASA Astrophysics Data System (ADS)

Sklyarchuk, V. M.; Gnatyuk, V. A.; Pecharapa, W.

2018-01-01

The electrical characteristics of the Ni/Cd1-xZnxTe/In structures with a metal-semiconductor rectifying contact are investigated. The diodes, fabricated on the base of In-doped n-type Cd1-xZnxTe (CZT) crystals with resistivity of ∼1010 Ω ṡ cm, have low leakage current and can be used as X/ γ-ray detectors. The rectifying contact was obtained by vacuum deposition of Ni on the semiconductor surface pretreated with argon plasma. The high barrier rectifying contact allowed us to increase applied reverse bias voltage up to 2500 V at the CZT crystal thickness of 1 mm. Dark (leakage) currents of the diodes with the rectifying contact area of 4 mm2 did not exceed 3-5 nA at bias voltage of 2000 V and room temperature. The charge transport mechanisms in the Ni/CZT/In structures have been interpreted as generation-recombination in the space charge region within the range of reverse bias of 5-100 V and as currents limited by space charge at both forward and reverse bias at V >100 V.

Fluoride Thin Films: from Exchange Bias to Multferroicity

NASA Astrophysics Data System (ADS)

Johnson, Trent A.

This dissertation concerns research into the growth and characterization fluoride thin films by molecular beam epitaxy. After a discussion of relevant background material and experimental procedures in the first two chapters, we study exchange bias in magnetic multilayers incorporating the uniaxial antiferromagnet FeF2, grown to varying thicknesses, sandwiched between ferromagnetic Co layers with fixed thicknesses of 5 and 20 nm. Several bilayers with only the 20 nm thick Co layer were grown for comparative study. The samples were grown on Al2O3 (112¯0) substrates at room temperature. In-situ RHEED and x-ray diffraction indicated the films were polycrystalline. The films were determined to have low surface and interlayer roughness, as determined by AFM and x-ray reflectivity. After field-cooling to below the Neel temperature of FeF2 in a magnetic field of 1 kOe, magnetic hysteresis loops were measured as a function of temperature. We found that both layers had a negative exchange bias, with the exchange bias of the thinner layer larger than that of the thicker layer. In addition, the coercivity below the blocking temperature TB of the thinner layer was significantly larger than that of the thick layer, even though the coercivity of the two layers was the same for T > TB. The exchange bias effect, manifested by a shift in these hysteresis loops, showed a strong dependence on the thickness of the antiferromagnet. Anisotropic magnetoresistance measurements provided additional insight into the magnetization reversal mechanism within the ferromagnets. The thickness dependent exchange anisotropy of trilayer and bilayer samples is explained by adapting a random field model to the antiferromagnet/ferromagnet interface. Finally, We investigate the temperature dependent growth, as well as the magnetic and ferroelectric properties of thin films of the multiferroic compounds BaMF4, where M = Fe, Co, Ni. The films were grown to thicknesses of 50 or 100 nm on single crystal Al2O3 (0001) substrates. X-ray diffraction showed that this family of films grew epitaxially in the (010) orientation, but were twinned in the plane, with three domain orientations rotated by 120 degrees relative to one another. Measurements of the remanent hysteresis via interdigitated electrodes showed that the compounds M = Co, and Ni were ferroelectric, but no switching behavior was observed in the Fe system at electric fields up to 400 kV/cm. Measurements of the field-cooled and zero-field-cooled magnetic moment confirmed low temperature antiferromagnetic behavior, and found new weak ferromagnetic phases induced by strain.

Influence of surface nudging on climatological mean and ENSO feedbacks in a coupled model

NASA Astrophysics Data System (ADS)

Zhu, Jieshun; Kumar, Arun

2018-01-01

Studies have suggested that surface nudging could be an efficient way to reconstruct the subsurface ocean variability, and thus a useful method for initializing climate predictions (e.g., seasonal and decadal predictions). Surface nudging is also the basis for climate models with flux adjustments. In this study, however, some negative aspects of surface nudging on climate simulations in a coupled model are identified. Specifically, a low-resolution version of the NCEP Climate Forecast System, version 2 (CFSv2L) is used to examine the influence of nudging on simulations of climatological mean and on the coupled feedbacks during ENSO. The effect on ENSO feedbacks is diagnosed following a heat budget analysis of mixed layer temperature anomalies. Diagnostics of the climatological mean state indicates that, even though SST biases in all ocean basins, as expected, are eliminated, the fidelity of climatological precipitation, surface winds and subsurface temperature (or the thermocline depth) could be highly ocean basin dependent. This is exemplified by improvements in the climatology of these variables in the tropical Atlantic, but degradations in the tropical Pacific. Furthermore, surface nudging also distorts the dynamical feedbacks during ENSO. For example, while the thermocline feedback played a critical role during the evolution of ENSO in a free simulation, it only played a minor role in the nudged simulation. These results imply that, even though the simulation of surface temperature could be improved in a climate model with surface nudging, the physics behind might be unrealistic.

The use of NOAA AVHRR data for assessment of the urban heat sland effect

USGS Publications Warehouse

Gallo, K.P.; McNab, A. L.; Karl, Thomas R.; Brown, Jesslyn F.; Hood, J. J.; Tarpley, J.D.

1993-01-01

A vegetation index and a radiative surface temperature were derived from satellite data acquired at approximately 1330 LST for each of 37 cities and for their respective nearby rural regions from 28 June through 8 August 1991. Urban–rural differences for the vegetation index and the surface temperatures were computed and then compared to observed urban–rural differences in minimum air temperatures. The purpose of these comparisons was to evaluate the use of satellite data to assess the influence of the urban environment on observed minimum air temperatures (the urban heat island effect). The temporal consistency of the data, from daily data to weekly, biweekly, and monthly intervals, was also evaluated. The satellite-derived normalized difference (ND) vegetation-index data, sampled over urban and rural regions composed of a variety of land surface environments, were linearly related to the difference in observed urban and rural minimum temperatures. The relationship between the ND index and observed differences in minimum temperature was improved when analyses were restricted by elevation differences between the sample locations and when biweekly or monthly intervals were utilized. The difference in the ND index between urban and rural regions appears to be an indicator of the difference in surface properties (evaporation and heat storage capacity) between the two environments that are responsible for differences in urban and rural minimum temperatures. The urban and rural differences in the ND index explain a greater amount of the variation observed in minimum temperature differences than past analyses that utilized urban population data. The use of satellite data may contribute to a globally consistent method for analysis of urban heat island bias.

Effect of negative bias on TiAlSiN coating deposited on nitrided Zircaloy-4

NASA Astrophysics Data System (ADS)

Jun, Zhou; Zhendong, Feng; Xiangfang, Fan; Yanhong, Liu; Huanlin, Li

2018-01-01

TiAlSiN coatings were deposited on the nitrided Zircaloy-4 by multi-arc ion plating at -100 V, -200 V and -300 V. In this study, the high temperature oxidation behavior of coatings was tested by a box-type resistance furnace in air for 3 h at 800 °C; the macro-morphology of coatings was observed and analyzed by a zoom-stereo microscope; the micro-morphology of coatings was analyzed by a scanning electron microscopy (SEM), and the chemical elements of samples were analyzed by an energy dispersive spectroscopy(EDS); the adhesion strength of the coating to the substrate was measured by an automatic scratch tester; and the phases of coatings were analyzed by an X-ray diffractometer(XRD). Results show that the coating deposited at -100 V shows better high temperature oxidation resistance behavior, at the same time, Al elements contained in the coating is of the highest amount, meanwhile, the adhesion strength of the coating to the substrate is the highest, which is 33N. As the bias increases, high temperature oxidation resistance behavior of the coating weakens first and then increases, the amount of large particles on the surface of the coating increases first and then decreases whereas the density of the coating decreases first and then increases, and adhesion strength of the coating to the substrate increases first and then weakens. The coating's quality is relatively poor when the bias is -200 V.

Antisite disorder induced spin glass and exchange bias effect in Nd2NiMnO6 epitaxial thin film

NASA Astrophysics Data System (ADS)

Singh, Amit Kumar; Chauhan, Samta; Chandra, Ramesh

2017-03-01

We report the observation of the exchange bias effect and spin glass behaviour at low temperature in a ferromagnetic Nd2NiMnO6 epitaxial thin film. Along with the ferromagnetic transition at ˜194 K, an additional transition is observed at lower temperature (˜55 K) as seen from M-T curves of the sample. A shift in the ac susceptibility peak with frequency has been observed at low temperature, which is a signature of a glassy phase within the sample. The detailed investigation of the memory effect and time dependent magnetic relaxation measurements reveals the presence of a spin glass phase in the Nd2NiMnO6 thin film. The exchange bias effect observed at low temperature in the sample has been associated with an antisite disorder induced spin glass phase, which results in a ferromagnetic/spin glass interface at low temperature. The exchange bias behaviour has been further confirmed by performing cooling field and temperature dependence of exchange bias along with training effect measurements.

Bias Stress and Temperature Impact on InGaZnO TFTs and Circuits

PubMed Central

Martins, Jorge; Bahubalindruni, Pydi; Rovisco, Ana; Kiazadeh, Asal; Martins, Rodrigo; Fortunato, Elvira; Barquinha, Pedro

2017-01-01

This paper focuses on the analysis of InGaZnO thin-film transistors (TFTs) and circuits under the influence of different temperatures and bias stress, shedding light into their robustness when used in real-world applications. For temperature-dependent measurements, a temperature range of 15 to 85 °C was considered. In case of bias stress, both gate and drain bias were applied for 60 min. Though isolated transistors show a variation of drain current as high as 56% and 172% during bias voltage and temperature stress, the employed circuits were able to counteract it. Inverters and two-TFT current mirrors following simple circuit topologies showed a gain variation below 8%, while the improved robustness of a cascode current mirror design is proven by showing a gain variation less than 5%. The demonstration that the proper selection of TFT materials and circuit topologies results in robust operation of oxide electronics under different stress conditions and over a reasonable range of temperatures proves that the technology is suitable for applications such as smart food packaging and wearables. PMID:28773037

Bias Stress and Temperature Impact on InGaZnO TFTs and Circuits.

PubMed

Martins, Jorge; Bahubalindruni, Pydi; Rovisco, Ana; Kiazadeh, Asal; Martins, Rodrigo; Fortunato, Elvira; Barquinha, Pedro

2017-06-21

This paper focuses on the analysis of InGaZnO thin-film transistors (TFTs) and circuits under the influence of different temperatures and bias stress, shedding light into their robustness when used in real-world applications. For temperature-dependent measurements, a temperature range of 15 to 85 °C was considered. In case of bias stress, both gate and drain bias were applied for 60 min. Though isolated transistors show a variation of drain current as high as 56% and 172% during bias voltage and temperature stress, the employed circuits were able to counteract it. Inverters and two-TFT current mirrors following simple circuit topologies showed a gain variation below 8%, while the improved robustness of a cascode current mirror design is proven by showing a gain variation less than 5%. The demonstration that the proper selection of TFT materials and circuit topologies results in robust operation of oxide electronics under different stress conditions and over a reasonable range of temperatures proves that the technology is suitable for applications such as smart food packaging and wearables.

Van der Waals heterojunction diode composed of WS2 flake placed on p-type Si substrate

NASA Astrophysics Data System (ADS)

Aftab, Sikandar; Farooq Khan, M.; Min, Kyung-Ah; Nazir, Ghazanfar; Afzal, Amir Muhammad; Dastgeer, Ghulam; Akhtar, Imtisal; Seo, Yongho; Hong, Suklyun; Eom, Jonghwa

2018-01-01

P-N junctions represent the fundamental building blocks of most semiconductors for optoelectronic functions. This work demonstrates a technique for forming a WS2/Si van der Waals junction based on mechanical exfoliation. Multilayered WS2 nanoflakes were exfoliated on the surface of bulk p-type Si substrates using a polydimethylsiloxane stamp. We found that the fabricated WS2/Si p-n junctions exhibited rectifying characteristics. We studied the effect of annealing processes on the performance of the WS2/Si van der Waals p-n junction and demonstrated that annealing improved its electrical characteristics. However, devices with vacuum annealing have an enhanced forward-bias current compared to those annealed in a gaseous environment. We also studied the top-gate-tunable rectification characteristics across the p-n junction interface in experiments as well as density functional theory calculations. Under various temperatures, Zener breakdown occurred at low reverse-bias voltages, and its breakdown voltage exhibited a negative coefficient of temperature. Another breakdown voltage was observed, which increased with temperature, suggesting a positive coefficient of temperature. Therefore, such a breakdown can be assigned to avalanche breakdown. This work demonstrates a promising application of two-dimensional materials placed directly on conventional bulk Si substrates.

What causes the facing-the-viewer bias in biological motion?

PubMed

Weech, Séamas; McAdam, Matthew; Kenny, Sophie; Troje, Nikolaus F

2014-10-13

Orthographically projected biological motion point-light displays are generally ambiguous with respect to their orientation in depth, yet observers consistently prefer the facing-the-viewer interpretation. There has been discussion as to whether this bias can be attributed to the social relevance of biological motion stimuli or relates to local, low-level stimulus properties. In the present study we address this question. In Experiment 1, we compared the facing-the-viewer bias produced by a series of four stick figures and three human silhouettes that differed in posture, gender, and the presence versus absence of walking motion. Using a paradigm in which we asked observers to indicate the spinning direction of these figures, we found no bias when participants observed silhouettes, whereas a pronounced degree of bias was elicited by most stick figures. We hypothesized that the ambiguous surface normals on the lines and dots that comprise stick figures are prone to a visual bias that assumes surfaces to be convex. The local surface orientations of the occluding contours of silhouettes are unambiguous, and as such the convexity bias does not apply. In Experiment 2, we tested the role of local features in ambiguous surface perception by adding dots to the elbows and knees of silhouettes. We found biases consistent with the facing directions implied by a convex body surface. The results unify a number of findings regarding the facing-the-viewer bias. We conclude that the facing-the-viewer bias is established at the level of surface reconstruction from local image features rather than on a semantic level. © 2014 ARVO.

Modeling canopy-induced turbulence in the Earth system: a unified parameterization of turbulent exchange within plant canopies and the roughness sublayer (CLM-ml v0)

NASA Astrophysics Data System (ADS)

Bonan, Gordon B.; Patton, Edward G.; Harman, Ian N.; Oleson, Keith W.; Finnigan, John J.; Lu, Yaqiong; Burakowski, Elizabeth A.

2018-04-01

Land surface models used in climate models neglect the roughness sublayer and parameterize within-canopy turbulence in an ad hoc manner. We implemented a roughness sublayer turbulence parameterization in a multilayer canopy model (CLM-ml v0) to test if this theory provides a tractable parameterization extending from the ground through the canopy and the roughness sublayer. We compared the canopy model with the Community Land Model (CLM4.5) at seven forest, two grassland, and three cropland AmeriFlux sites over a range of canopy heights, leaf area indexes, and climates. CLM4.5 has pronounced biases during summer months at forest sites in midday latent heat flux, sensible heat flux, gross primary production, nighttime friction velocity, and the radiative temperature diurnal range. The new canopy model reduces these biases by introducing new physics. Advances in modeling stomatal conductance and canopy physiology beyond what is in CLM4.5 substantially improve model performance at the forest sites. The signature of the roughness sublayer is most evident in nighttime friction velocity and the diurnal cycle of radiative temperature, but is also seen in sensible heat flux. Within-canopy temperature profiles are markedly different compared with profiles obtained using Monin-Obukhov similarity theory, and the roughness sublayer produces cooler daytime and warmer nighttime temperatures. The herbaceous sites also show model improvements, but the improvements are related less systematically to the roughness sublayer parameterization in these canopies. The multilayer canopy with the roughness sublayer turbulence improves simulations compared with CLM4.5 while also advancing the theoretical basis for surface flux parameterizations.

Biases in the instrumental temperature record: the policy and communications context

NASA Astrophysics Data System (ADS)

Cowtan, K.; Way, R. G.

2014-12-01

Global surface temperature plays a significant role in the public perception of climate change. However, observations are not uniformly distributed over the surface of the planet. The lack of data for the rapidly warming Arctic in the Met Office HadCRUT4 dataset has led to a systematic underestimation of the rate of warming over the past decade and a half. Smaller biases have also been detected in other versions of the temperature record. This underestimation of recent temperature trends is one contributory factor (of several) to the apparent 'hiatus' in global warming. The use of the putative hiatus as an argument against action on global warming has created a social context in which what should have been a minor technical paper appeared to take on a much greater significance. From a scientific perspective, the apparent hiatus is irrelevant to our understanding of long term greenhouse warming, and should therefore have no bearing on policy. However the misinformation context into which science is communicated means that any scientific work can take on a policy significance which is determined not by the work itself, but by the societal context. This raises challenging ethical questions for scientists. In an information environment in which interested parties have already attached policy implications to many aspects of climate science, it becomes impossible to publish or communicate a scientific work without implicitly taking a position. Different segments of the public have different and often contradictory perceptions of the scientific context, and as a result the words of the scientist may convey completely different messages to different hearers. Communicating science in a way which does not mislead is difficult, however abandoning the effort at communication can lead to the public being more misled.

Evaluating Arctic warming mechanisms in CMIP5 models

NASA Astrophysics Data System (ADS)

Franzke, Christian L. E.; Lee, Sukyoung; Feldstein, Steven B.

2017-05-01

Arctic warming is one of the most striking signals of global warming. The Arctic is one of the fastest warming regions on Earth and constitutes, thus, a good test bed to evaluate the ability of climate models to reproduce the physics and dynamics involved in Arctic warming. Different physical and dynamical mechanisms have been proposed to explain Arctic amplification. These mechanisms include the surface albedo feedback and poleward sensible and latent heat transport processes. During the winter season when Arctic amplification is most pronounced, the first mechanism relies on an enhancement in upward surface heat flux, while the second mechanism does not. In these mechanisms, it has been proposed that downward infrared radiation (IR) plays a role to a varying degree. Here, we show that the current generation of CMIP5 climate models all reproduce Arctic warming and there are high pattern correlations—typically greater than 0.9—between the surface air temperature (SAT) trend and the downward IR trend. However, we find that there are two groups of CMIP5 models: one with small pattern correlations between the Arctic SAT trend and the surface vertical heat flux trend (Group 1), and the other with large correlations (Group 2) between the same two variables. The Group 1 models exhibit higher pattern correlations between Arctic SAT and 500 hPa geopotential height trends, than do the Group 2 models. These findings suggest that Arctic warming in Group 1 models is more closely related to changes in the large-scale atmospheric circulation, whereas in Group 2, the albedo feedback effect plays a more important role. Interestingly, while Group 1 models have a warm or weak bias in their Arctic SAT, Group 2 models show large cold biases. This stark difference in model bias leads us to hypothesize that for a given model, the dominant Arctic warming mechanism and trend may be dependent on the bias of the model mean state.

Epithermal Neutron Evidence for a Diurnal Surface Hydration Process in the Moon's High Latitudes

NASA Technical Reports Server (NTRS)

McClanahan, T. P.; Mitrofanov, I. G.; Boynton, W. V.; Chin, G.; Parsons, A.; Starr, R. D.; Evans, L. G.; Sanin, A.; Litvak, M.; Livengood, T.

2015-01-01

We report evidence from epithermal neutron flux observations that show that the Moon's high latitude surfaces are being actively hydrated, dehydrated and rehydrated in a diurnal cycle. The near-surface hydration is indicated by an enhanced suppression of the lunar epithermal neutron leakage flux on the dayside of the dawn terminator on poleward-facing slopes (PFS). At 0600 to 0800 local-time, hydrogen concentrations within the upper 1 meter of PFS are observed to be maximized relative to equivalent equator-facing slopes (EFS). During the lunar day surface hydrogen concentrations diminish towards dusk and then rebuild overnight. Surface hydration is determined by differential comparison of the averaged EFS to PFS epithermal neutron count rates above +/- 75 deg latitude. At dawn the contrast bias towards PFS is consistent with at least 15 to 25 parts-per-million (ppm) hydrogen that dissipates by dusk. We review several lines of evidence derived from temperature and epithermal neutron data by a correlated analysis of observations from the Lunar Reconnaissance Orbiter's (LRO) Lunar Exploration Neutron Detector (LEND) that were mapped as a function of lunar local-time, Lunar Observing Laser Altimeter (LOLA) topography and Diviner (DLRE) surface temperature.

GDGT distribution in a stratified lake and implications for the application of TEX86 in paleoenvironmental reconstructions

NASA Astrophysics Data System (ADS)

Zhang, Zhaohui; Smittenberg, Rienk H.; Bradley, Raymond S.

2016-10-01

We investigated the relationship between distributions of GDGTs, GDGT-based proxies and environmental factors in a stratified lake in northwestern Norway. More than 90% of isoGDGTs were produced at the bottom of the oxycline, indicating a predominance of ammonia-oxidizing Group I.1a of Thaumarchaeota, supported by high crenarchaeol/caldarchaeol ratios. Dissolved oxygen content, rather than temperature, exercised a primary control on TEX86 values. In spite of low BIT value in surface sediment, the reconstructed lake surface temperature was “cold” biased. MBT values in streams and lake surface water were significantly smaller than those in the catchment soil, suggesting in situ production of brGDGTs in streams. A rapid transition of MBT vs. temperature/pH relationships occurring at the bottom of oxycline indicated the differential production of various brGDGTs with D.O. and depths. Only within the oxycline were CBT-based pH values close to in situ pH. Our results confirm earlier studies calling for caution in applying TEX86 as a surface temperature proxy, or MBT and/or CBT for reconstructing pH, in anoxic or euxinic lakes, estuaries and ocean basins. We propose that caldarchaeol/crenarchaeol ratio, an indicator of contributions from methanogenic archaea, together with the BIT and TEX86 proxies, can help reconstruct past levels of stratification.

Evaluation of the HadGEM3-A simulations in view of detection and attribution of human influence on extreme events in Europe

NASA Astrophysics Data System (ADS)

Vautard, Robert; Christidis, Nikolaos; Ciavarella, Andrew; Alvarez-Castro, Carmen; Bellprat, Omar; Christiansen, Bo; Colfescu, Ioana; Cowan, Tim; Doblas-Reyes, Francisco; Eden, Jonathan; Hauser, Mathias; Hegerl, Gabriele; Hempelmann, Nils; Klehmet, Katharina; Lott, Fraser; Nangini, Cathy; Orth, René; Radanovics, Sabine; Seneviratne, Sonia I.; van Oldenborgh, Geert Jan; Stott, Peter; Tett, Simon; Wilcox, Laura; Yiou, Pascal

2018-04-01

A detailed analysis is carried out to assess the HadGEM3-A global atmospheric model skill in simulating extreme temperatures, precipitation and storm surges in Europe in the view of their attribution to human influence. The analysis is performed based on an ensemble of 15 atmospheric simulations forced with observed sea surface temperature of the 54 year period 1960-2013. These simulations, together with dual simulations without human influence in the forcing, are intended to be used in weather and climate event attribution. The analysis investigates the main processes leading to extreme events, including atmospheric circulation patterns, their links with temperature extremes, land-atmosphere and troposphere-stratosphere interactions. It also compares observed and simulated variability, trends and generalized extreme value theory parameters for temperature and precipitation. One of the most striking findings is the ability of the model to capture North-Atlantic atmospheric weather regimes as obtained from a cluster analysis of sea level pressure fields. The model also reproduces the main observed weather patterns responsible for temperature and precipitation extreme events. However, biases are found in many physical processes. Slightly excessive drying may be the cause of an overestimated summer interannual variability and too intense heat waves, especially in central/northern Europe. However, this does not seem to hinder proper simulation of summer temperature trends. Cold extremes appear well simulated, as well as the underlying blocking frequency and stratosphere-troposphere interactions. Extreme precipitation amounts are overestimated and too variable. The atmospheric conditions leading to storm surges were also examined in the Baltics region. There, simulated weather conditions appear not to be leading to strong enough storm surges, but winds were found in very good agreement with reanalyses. The performance in reproducing atmospheric weather patterns indicates that biases mainly originate from local and regional physical processes. This makes local bias adjustment meaningful for climate change attribution.

A Climate-Data Record of the "Clear-Sky" Surface Temperature of the Greenland Ice Sheet

NASA Technical Reports Server (NTRS)

Hall, D. K.; Comiso, J. C.; Digirolamo, N. E.; Stock, L. V.; Riggs, G. A.; Shuman, C. A.

2009-01-01

We are developing a climate-data record (CDR of daily "clear-sky" ice-surface temperature (IST) of the Greenland Ice Sheet, from 1982 to the present using Advanced Very High Resolution Radiometer (AVHRR) (1982 - present) and Moderate-Resolution Imaging Spectroradiometer (MODIS) data (2000 - present) at a resolution of approximately 5 km. The CDR will be continued in the National Polar-orbiting Operational Environmental Satellite System Visible/Infrared Imager Radiometer Suite era. Two algorithms remain under consideration. One algorithm under consideration is based on the split-window technique used in the Polar Pathfinder dataset (Fowler et al., 2000 & 21007). Another algorithm under consideration, developed by Comiso (2006), uses a single channel of AVHRR data (channel 4) in conjunction with meteorological-station data to account for atmospheric effects and drift between AVHRR instruments. Known issues being addressed in the production of the CDR are: tune-series bias caused by cloud cover (surface temperatures can be different under clouds vs. clear areas) and cross-calibration in the overlap period between AVHRR instruments, and between AVHRR and MODIS instruments. Because of uncertainties, mainly due to clouds (Stroeve & Steffen, 1998; Wang and Key, 2005; Hall et al., 2008 and Koenig and Hall, submitted), time-series of satellite 1S'1" do not necessarily correspond to actual surface temperatures. The CDR will be validated by comparing results with automatic-,",eather station (AWS) data and with satellite-derived surface-temperature products. Regional "clear-sky" surface temperature increases in the Arctic, measured from AVHRR infrared data, range from 0.57+/-0.02 deg C (Wang and Key, 2005) to 0.72+/-0.10 deg C (Comiso, 2006) per decade since the early 1980s. Arctic warming has important implications for ice-sheet mass balance because much of the periphery of the Greenland Ice Sheet is already near 0 deg C during the melt season, and is thus vulnerable to rapid melting if temperatures continue to increase. References

Climate impacts of parameterized Nordic Sea overflows

NASA Astrophysics Data System (ADS)

Danabasoglu, Gokhan; Large, William G.; Briegleb, Bruce P.

2010-11-01

A new overflow parameterization (OFP) of density-driven flows through ocean ridges via narrow, unresolved channels has been developed and implemented in the ocean component of the Community Climate System Model version 4. It represents exchanges from the Nordic Seas and the Antarctic shelves, associated entrainment, and subsequent injection of overflow product waters into the abyssal basins. We investigate the effects of the parameterized Denmark Strait (DS) and Faroe Bank Channel (FBC) overflows on the ocean circulation, showing their impacts on the Atlantic Meridional Overturning Circulation and the North Atlantic climate. The OFP is based on the Marginal Sea Boundary Condition scheme of Price and Yang (1998), but there are significant differences that are described in detail. Two uncoupled (ocean-only) and two fully coupled simulations are analyzed. Each pair consists of one case with the OFP and a control case without this parameterization. In both uncoupled and coupled experiments, the parameterized DS and FBC source volume transports are within the range of observed estimates. The entrainment volume transports remain lower than observational estimates, leading to lower than observed product volume transports. Due to low entrainment, the product and source water properties are too similar. The DS and FBC overflow temperature and salinity properties are in better agreement with observations in the uncoupled case than in the coupled simulation, likely reflecting surface flux differences. The most significant impact of the OFP is the improved North Atlantic Deep Water penetration depth, leading to a much better comparison with the observational data and significantly reducing the chronic, shallow penetration depth bias in level coordinate models. This improvement is due to the deeper penetration of the southward flowing Deep Western Boundary Current. In comparison with control experiments without the OFP, the abyssal ventilation rates increase in the North Atlantic. In the uncoupled simulation with the OFP, the warm bias of the control simulation in the deep North Atlantic is substantially reduced along with salinity bias reductions in the northern North Atlantic. There are similar but more modest bias reductions in the deep temperature and salinity distributions especially in the northern North Atlantic in the coupled OFP case. In coupled simulations, there are noticeable impacts of the OFP on climate. The sea surface temperatures (SSTs) are warmer by more than 5°C off the North American coast and by more than 1°C in the Nordic Sea with the OFP. The surface heat fluxes mostly act to diminish these SST changes. There are related changes in the sea level pressure, leading to about 15% weaker westerly wind stress in the northern North Atlantic. In response to the warmer Nordic Sea SSTs, there are reductions in the sea ice extent, improving comparisons with observations. Although the OFP cases improve many aspects of the simulations compared to observations, some significant biases remain, more in coupled than in uncoupled simulations.

Bias correction of temperature produced by the Community Climate System Model using Artificial Neural Networks

NASA Astrophysics Data System (ADS)

Moghim, S.; Hsu, K.; Bras, R. L.

2013-12-01

General Circulation Models (GCMs) are used to predict circulation and energy transfers between the atmosphere and the land. It is known that these models produce biased results that will have impact on their uses. This work proposes a new method for bias correction: the equidistant cumulative distribution function-artificial neural network (EDCDFANN) procedure. The method uses artificial neural networks (ANNs) as a surrogate model to estimate bias-corrected temperature, given an identification of the system derived from GCM models output variables. A two-layer feed forward neural network is trained with observations during a historical period and then the adjusted network can be used to predict bias-corrected temperature for future periods. To capture the extreme values this method is combined with the equidistant CDF matching method (EDCDF, Li et al. 2010). The proposed method is tested with the Community Climate System Model (CCSM3) outputs using air and skin temperature, specific humidity, shortwave and longwave radiation as inputs to the ANN. This method decreases the mean square error and increases the spatial correlation between the modeled temperature and the observed one. The results indicate the EDCDFANN has potential to remove the biases of the model outputs.

Effect of shell thickness on the exchange bias blocking temperature and coercivity in Co-CoO core-shell nanoparticles

NASA Astrophysics Data System (ADS)

Thomas, S.; Reethu, K.; Thanveer, T.; Myint, M. T. Z.; Al-Harthi, S. H.

2017-08-01

The exchange bias blocking temperature distribution of naturally oxidized Co-CoO core-shell nanoparticles exhibits two distinct signatures. These are associated with the existence of two magnetic entities which are responsible for the temperature dependence of an exchange bias field. One is from the CoO grains which undergo thermally activated magnetization reversal. The other is from the disordered spins at the Co-CoO interface which exhibits spin-glass-like behavior. We investigated the oxide shell thickness dependence of the exchange bias effect. For particles with a 3 nm thick CoO shell, the predominant contribution to the temperature dependence of exchange bias is the interfacial spin-glass layer. On increasing the shell thickness to 4 nm, the contribution from the spin-glass layer decreases, while upholding the antiferromagnetic grain contribution. For samples with a 4 nm CoO shell, the exchange bias training was minimal. On the other hand, 3 nm samples exhibited both the training effect and a peak in coercivity at an intermediate set temperature Ta. This is explained using a magnetic core-shell model including disordered spins at the interface.

Temperature dependence of DC transport characteristics for a two-dimensional electron gas in an undoped Si/SiGe heterostructure

NASA Astrophysics Data System (ADS)

Chou, Kuan-Yu; Hsu, Nai-Wen; Su, Yi-Hsin; Chou, Chung-Tao; Chiu, Po-Yuan; Chuang, Yen; Li, Jiun-Yun

2018-02-01

We investigate DC characteristics of a two-dimensional electron gas (2DEG) in an undoped Si/SiGe heterostructure and its temperature dependence. An insulated-gate field-effect transistor was fabricated, and transfer characteristics were measured at 4 K-300 K. At low temperatures (T < 45 K), source electrons are injected into the buried 2DEG channel first and drain current increases with the gate voltage. By increasing the gate voltage further, the current saturates followed by a negative transconductance observed, which can be attributed to electron tunneling from the buried channel to the surface channel. Finally, the drain current is saturated again at large gate biases due to parallel conduction of buried and surface channels. By increasing the temperature, an abrupt increase in threshold voltage is observed at T ˜ 45 K and it is speculated that negatively charged impurities at the Al2O3/Si interface are responsible for the threshold voltage shift. At T > 45 K, the current saturation and negative transconductance disappear and the device acts as a normal transistor.

An intercomparison of GCM and RCM dynamical downscaling for characterizing the hydroclimatology of California and Nevada

NASA Astrophysics Data System (ADS)

Xu, Z.; Rhoades, A.; Johansen, H.; Ullrich, P. A.; Collins, W. D.

2017-12-01

Dynamical downscaling is widely used to properly characterize regional surface heterogeneities that shape the local hydroclimatology. However, the factors in dynamical downscaling, including the refinement of model horizontal resolution, large-scale forcing datasets and dynamical cores, have not been fully evaluated. Two cutting-edge global-to-regional downscaling methods are used to assess these, specifically the variable-resolution Community Earth System Model (VR-CESM) and the Weather Research & Forecasting (WRF) regional climate model, under different horizontal resolutions (28, 14, and 7 km). Two groups of WRF simulations are driven by either the NCEP reanalysis dataset (WRF_NCEP) or VR-CESM outputs (WRF_VRCESM) to evaluate the effects of the large-scale forcing datasets. The impacts of dynamical core are assessed by comparing the VR-CESM simulations to the coupled WRF_VRCESM simulations with the same physical parameterizations and similar grid domains. The simulated hydroclimatology (i.e., total precipitation, snow cover, snow water equivalent and surface temperature) are compared with the reference datasets. The large-scale forcing datasets are critical to the WRF simulations in more accurately simulating total precipitation, SWE and snow cover, but not surface temperature. Both the WRF and VR-CESM results highlight that no significant benefit is found in the simulated hydroclimatology by just increasing horizontal resolution refinement from 28 to 7 km. Simulated surface temperature is sensitive to the choice of dynamical core. WRF generally simulates higher temperatures than VR-CESM, alleviates the systematic cold bias of DJF temperatures over the California mountain region, but overestimates the JJA temperature in California's Central Valley.

Spatial inhomogeneous barrier heights at graphene/semiconductor Schottky junctions

NASA Astrophysics Data System (ADS)

Tomer, Dushyant

Graphene, a semimetal with linear energy dispersion, forms Schottky junction when interfaced with a semiconductor. This dissertation presents temperature dependent current-voltage and scanning tunneling microscopy/spectroscopy (STM/S) measurements performed on graphene Schottky junctions formed with both three and two dimensional semiconductors. To fabricate Schottky junctions, we transfer chemical vapor deposited monolayer graphene onto Si- and C-face SiC, Si, GaAs and MoS2 semiconducting substrates using polymer assisted chemical method. We observe three main type of intrinsic spatial inhomogeneities, graphene ripples, ridges and semiconductor steps in STM imaging that can exist at graphene/semiconductor junctions. Tunneling spectroscopy measurements reveal fluctuations in graphene Dirac point position, which is directly related to the Schottky barrier height. We find a direct correlation of Dirac point variation with the topographic undulations of graphene ripples at the graphene/SiC junction. However, no such correlation is established at graphene/Si and Graphene/GaAs junctions and Dirac point variations are attributed to surface states and trapped charges at the interface. In addition to graphene ripples and ridges, we also observe atomic scale moire patterns at graphene/MoS2 junction due to van der Waals interaction at the interface. Periodic topographic modulations due to moire pattern do not lead to local variation in graphene Dirac point, indicating that moire pattern does not contribute to fluctuations in electronic properties of the heterojunction. We perform temperature dependent current-voltage measurements to investigate the impact of topographic inhomogeneities on electrical properties of the Schottky junctions. We observe temperature dependence in junction parameters, such as Schottky barrier height and ideality factor, for all types of Schottky junctions in forward bias measurements. Standard thermionic emission theory which assumes a perfect smooth interface fails to explain such behavior, hence, we apply a modified emission theory with Gaussian distribution of Schottky barrier heights. The modified theory, applicable to inhomogeneous interfaces, explains the temperature dependent behavior of our Schottky junctions and gives a temperature independent mean barrier height. We attribute the inhomogeneous barrier height to the presence of graphene ripples and ridges in case of SiC and MoS2 while surface states and trapped charges at the interface is dominating in Si and GaAs. Additionally, we observe bias dependent current and barrier height in reverse bias regime also for all Schottky junctions. To explain such behavior, we consider two types of reverse bias conduction mechanisms; Poole-Frenkel and Schottky emission. We find that Poole-Frenkel emission explains the characteristics of graphene/SiC junctions very well. However, both the mechanism fails to interpret the behavior of graphene/Si and graphene/GaAs Schottky junctions. These findings provide insight into the fundamental physics at the interface of graphene/semiconductor junctions.

Tribological synthesis method for producing low-friction surface film coating

DOEpatents

Ajayi, Oyelayo O.; Lorenzo-Martin, Maria De La; Fenske, George R.

2016-10-25

An article of method of manufacture of a low friction tribological film on a substrate. The article includes a substrate of a steel or ceramic which has been tribologically processed with a lubricant containing selected additives and the additives, temperature, load and time of processing can be selectively controlled to bias formation of a film on the substrate where the film is an amorphous structure exhibiting highly advantageous low friction properties.

Model under-representation of decadal Pacific trade wind trends and its link to tropical Atlantic bias

NASA Astrophysics Data System (ADS)

Kajtar, Jules B.; Santoso, Agus; McGregor, Shayne; England, Matthew H.; Baillie, Zak

2018-02-01

The strengthening of the Pacific trade winds in recent decades has been unmatched in the observational record stretching back to the early twentieth century. This wind strengthening has been connected with numerous climate-related phenomena, including accelerated sea-level rise in the western Pacific, alterations to Indo-Pacific ocean currents, increased ocean heat uptake, and a slow-down in the rate of global-mean surface warming. Here we show that models in the Coupled Model Intercomparison Project phase 5 underestimate the observed range of decadal trends in the Pacific trade winds, despite capturing the range in decadal sea surface temperature (SST) variability. Analysis of observational data suggests that tropical Atlantic SST contributes considerably to the Pacific trade wind trends, whereas the Atlantic feedback in coupled models is muted. Atmosphere-only simulations forced by observed SST are capable of recovering the time-variation and the magnitude of the trade wind trends. Hence, we explore whether it is the biases in the mean or in the anomalous SST patterns that are responsible for the under-representation in fully coupled models. Over interannual time-scales, we find that model biases in the patterns of Atlantic SST anomalies are the strongest source of error in the precipitation and atmospheric circulation response. In contrast, on decadal time-scales, the magnitude of the model biases in Atlantic mean SST are directly linked with the trade wind variability response.

Coercivity and Exchange Bias Study of Polycrystalline Hollow Nanoparticles

NASA Astrophysics Data System (ADS)

Bah, Mohamed Alpha

Magnetic nanoparticles (NPs) have the potential to be useful in a variety of applications such as biomedical instruments, catalysis, sensing, recording information, etc. These nanoparticles exhibit remarkably different properties compared to their bulk counter parts. Synthesis of magnetic NPs with the right morphology, phase, size and surface functionality, as well as their usage for specific applications are challenging in terms of efficiency and safety. Morphology wise, there have been numerous reports on magnetic nanoparticles where morphologies such as core/shell, hollow, solid, etc., have been explored. It has been shown that morphology affects the magnetic response. Achieving the right crystal structure with required morphology and the magnetic behavior of the nanoparticle phases determines the magnetic response of the structure. For example, in the case of core/shell NPs various ferromagnetic (FM), ferrimagnetic (FiM), and antiferromagnetic (AFM) core and shell combinations have been reported. In these cases, interesting and strikingly different features, such as unusually high spin glass transition temperature, large exchange bias, finite size effects, magnetic proximity effects, unusual trend of blocking temperature as function of average crystal size, etc., have been reported. More specifically, the morphology of core/shell nanoparticles provides added degrees of freedom compared to conventional solid magnetic nanoparticles, including variations in the size, phase and material of the core and shell of the particle, etc. which helps enhance their magnetic properties. Similar to traditional core/shell nanoparticles, inverted core/shell having a FiM or FM order above the Curie temperature (TC) of the shell has been reported where the Neel temperature (TN) is comparable with the bulk value and there is nonmonotonic dependence of the coercive field (HC) and exchange bias (HEB) on the core diameter. In addition to the core/shell morphology, nanoparticles with hollow morphology are also of interest to the scientific community. For such cases, surface spin glass transition enhancements have been reported due to the presence of the additional inner surface. CoFe2O4, NiFe 2O4 and gamma-Fe2O3 hollow nanoparticles exhibit strikingly contrasting magnetic behavior compared to bulk and conventional solid particles; similar behavior was also observed in core/shell nanoparticles. Structurally, hollow polycrystalline nanoparticles are composed of multiple crystallographic domains. This random orientation of the crystallographic domains also causes randomization of the local anisotropy axes. Hence the overall effect of this morphology on the magnetic properties is exhibited through the high coercivity, relatively high temperature magnetic irreversibility, lack of magnetic saturation, high blocking temperature, etc. Over the years, extensive work on core/shell nanoparticles have been carried out to understand their exchange bias phenomenon and the effect on coercivity. Recently, focus has been given to hollow polycrystalline nanoparticles for the reason mentioned above. This thesis investigates the root cause for the above-mentioned effects on the coercivity and exchange bias. Since hollow nanoparticles with polycrystalline structure have shown to exhibit different and improved magnetic behavior compared to bulk and other conventional solid particles, they will be the focus of our investigation. First, extensive field and temperature dependent magnetic study on polycrystalline hollow nickel ferrite (NiFe2O4) have revealed the effect of the presence of inner surface in a single oxide nanoparticle. Second, the effect of having multiple oxides with different magnetic properties (i.e. FM and AFM) in a single nanoparticle, while maintaining a hollow morphology was investigated by studying polycrystalline hollow gamma-Mn2O3 and MnO nanoparticles. Studies on various conventional solid manganese oxide nanoparticles have already been reported. Therefore, focus was only made on the fabrication and magnetic study of hollow polycrystalline manganese oxide, with a comparison of the results to those from solid nanoparticles already available in literature. A conclusion was drawn to the importance of the coupling of different magnetic phases (i.e. FM and AFM, FiM and AFM, or SG and AFM), in contrast to just having one single oxide in the hollow nanoparticles. Finally, the importance of this coupling as compared to the increase of surface-to-volume ratio was evaluated in CoO/Co3O4/CoFe2O4 polycrystalline hollow nanoparticles by varying the AFM phase (CoO/Co 3O4) in the nanoparticles and observing how the magnetic properties varied. This system helped address the effect of the coupling between different magnetic phases, super-exchange interaction, and proximity effect.

Exploring high dimensional free energy landscapes: Temperature accelerated sliced sampling

NASA Astrophysics Data System (ADS)

Awasthi, Shalini; Nair, Nisanth N.

2017-03-01

Biased sampling of collective variables is widely used to accelerate rare events in molecular simulations and to explore free energy surfaces. However, computational efficiency of these methods decreases with increasing number of collective variables, which severely limits the predictive power of the enhanced sampling approaches. Here we propose a method called Temperature Accelerated Sliced Sampling (TASS) that combines temperature accelerated molecular dynamics with umbrella sampling and metadynamics to sample the collective variable space in an efficient manner. The presented method can sample a large number of collective variables and is advantageous for controlled exploration of broad and unbound free energy basins. TASS is also shown to achieve quick free energy convergence and is practically usable with ab initio molecular dynamics techniques.

Lake surface water temperatures of European Alpine lakes (1989-2013) based on the Advanced Very High Resolution Radiometer (AVHRR) 1 km data set

NASA Astrophysics Data System (ADS)

Riffler, M.; Lieberherr, G.; Wunderle, S.

2015-02-01

Lake water temperature (LWT) is an important driver of lake ecosystems and it has been identified as an indicator of climate change. Consequently, the Global Climate Observing System (GCOS) lists LWT as an essential climate variable. Although for some European lakes long in situ time series of LWT do exist, many lakes are not observed or only on a non-regular basis making these observations insufficient for climate monitoring. Satellite data can provide the information needed. However, only few satellite sensors offer the possibility to analyse time series which cover 25 years or more. The Advanced Very High Resolution Radiometer (AVHRR) is among these and has been flown as a heritage instrument for almost 35 years. It will be carried on for at least ten more years, offering a unique opportunity for satellite-based climate studies. Herein we present a satellite-based lake surface water temperature (LSWT) data set for European water bodies in or near the Alps based on the extensive AVHRR 1 km data record (1989-2013) of the Remote Sensing Research Group at the University of Bern. It has been compiled out of AVHRR/2 (NOAA-07, -09, -11, -14) and AVHRR/3 (NOAA-16, -17, -18, -19 and MetOp-A) data. The high accuracy needed for climate related studies requires careful pre-processing and consideration of the atmospheric state. The LSWT retrieval is based on a simulation-based scheme making use of the Radiative Transfer for TOVS (RTTOV) Version 10 together with ERA-interim reanalysis data from the European Centre for Medium-range Weather Forecasts. The resulting LSWTs were extensively compared with in situ measurements from lakes with various sizes between 14 and 580 km2 and the resulting biases and RMSEs were found to be within the range of -0.5 to 0.6 K and 1.0 to 1.6 K, respectively. The upper limits of the reported errors could be rather attributed to uncertainties in the data comparison between in situ and satellite observations than inaccuracies of the satellite retrieval. An inter-comparison with the standard Moderate-resolution Imaging Spectroradiometer (MODIS) Land Surface Temperature product exhibits RMSEs and biases in the range of 0.6 to 0.9 and -0.5 to 0.2 K, respectively. The cross-platform consistency of the retrieval was found to be within ~ 0.3 K. For one lake, the satellite-derived trend was compared with the trend of in situ measurements and both were found to be similar. Thus, orbital drift is not causing artificial temperature trends in the data set. A comparison with LSWT derived through global sea surface temperature (SST) algorithms shows lower RMSEs and biases for the simulation-based approach. A running project will apply the developed method to retrieve LSWT for all of Europe to derive the climate signal of the last 30 years. The data are available at doi:10.1594/PANGAEA.831007.

Structure and dynamics of the Benguela low-level coastal jet

NASA Astrophysics Data System (ADS)

Patricola, Christina M.; Chang, Ping

2017-10-01

Generations of coupled atmosphere-ocean general circulation models have been plagued by persistent warm sea surface temperature (SST) biases in the southeastern tropical Atlantic. The SST biases are most severe in the eastern boundary coastal upwelling region and are sensitive to surface wind stress and wind stress curl associated with the Benguela low-level coastal jet (BLLCJ), a southerly jet parallel to the Angola-Namibia coast. However, little has been documented about this atmospheric source of oceanic bias. Here we investigate the characteristics and dynamics of the BLLCJ using observations, reanalyses, and atmospheric model simulations. Satellite wind products and high-resolution reanalyses and models represent the BLLCJ with two near-shore maxima, one near the Angola-Benguela front (ABF) at 17.5°S, and the other near 25-27.5°S, whereas coarse resolution reanalyses and models represent the BLLCJ poorly with a single, broad, more offshore maximum. Model experiments indicate that convex coastal geometry near the ABF supports the preferred location of the BLLCJ northern maximum by supporting conditions for a hydraulic expansion fan. Intraseasonal variability of the BLLCJ is associated with large-scale variability in intensity and location of the South Atlantic subtropical high through modulation of the low-level zonal pressure gradient.

Reconstructing spatial-temporal continuous MODIS land surface temperature using the DINEOF method

NASA Astrophysics Data System (ADS)

Zhou, Wang; Peng, Bin; Shi, Jiancheng

2017-10-01

Land surface temperature (LST) is one of the key states of the Earth surface system. Remote sensing has the capability to obtain high-frequency LST observations with global coverage. However, mainly due to cloud cover, there are always gaps in the remotely sensed LST product, which hampers the application of satellite-based LST in data-driven modeling of surface energy and water exchange processes. We explored the suitability of the data interpolating empirical orthogonal functions (DINEOF) method in moderate resolution imaging spectroradiometer LST reconstruction around Ali on the Tibetan Plateau. To validate the reconstruction accuracy, synthetic clouds during both daytime and nighttime are created. With DINEOF reconstruction, the root mean square error and bias under synthetic clouds in daytime are 4.57 and -0.0472 K, respectively, and during the nighttime are 2.30 and 0.0045 K, respectively. The DINEOF method can well recover the spatial pattern of LST. Time-series analysis of LST before and after DINEOF reconstruction from 2002 to 2016 shows that the annual and interannual variabilities of LST can be well reconstructed by the DINEOF method.

Does temperature nudging overwhelm aerosol radiative ...

EPA Pesticide Factsheets

For over two decades, data assimilation (popularly known as nudging) methods have been used for improving regional weather and climate simulations by reducing model biases in meteorological parameters and processes. Similar practice is also popular in many regional integrated meteorology-air quality models that include aerosol direct and indirect effects. However in such multi-modeling systems, temperature changes due to nudging can compete with temperature changes induced by radiatively active & hygroscopic short-lived tracers leading to interesting dilemmas: From weather and climate prediction’s (retrospective or future) point of view when nudging is continuously applied, is there any real added benefit of using such complex and computationally expensive regional integrated modeling systems? What are the relative sizes of these two competing forces? To address these intriguing questions, we convert temperature changes due to nudging into radiative fluxes (referred to as the pseudo radiative forcing, PRF) at the surface and troposphere, and compare the net PRF with the reported aerosol radiative forcing. Results indicate that the PRF at surface dominates PRF at top of the atmosphere (i.e., the net). Also, the net PRF is about 2-4 times larger than estimated aerosol radiative forcing at regional scales while it is significantly larger at local scales. These results also show large surface forcing errors at many polluted urban sites. Thus, operational c

Role of the Soil Thermal Inertia in the short term variability of the surface temperature and consequences for the soil-moisture temperature feedback

NASA Astrophysics Data System (ADS)

Cheruy, Frederique; Dufresne, Jean-Louis; Ait Mesbah, Sonia; Grandpeix, Jean-Yves; Wang, Fuxing

2017-04-01

A simple model based on the surface energy budget at equilibrium is developed to compute the sensitivity of the climatological mean daily temperature and diurnal amplitude to the soil thermal inertia. It gives a conceptual framework to quantity the role of the atmospheric and land surface processes in the surface temperature variability and relies on the diurnal amplitude of the net surface radiation, the sensitivity of the turbulent fluxes to the surface temperature and the thermal inertia. The performances of the model are first evaluated with 3D numerical simulations performed with the atmospheric (LMDZ) and land surface (ORCHIDEE) modules of the Institut Pierre Simon Laplace (IPSL) climate model. A nudging approach is adopted, it prevents from using time-consuming long-term simulations required to account for the natural variability of the climate and allow to draw conclusion based on short-term (several years) simulations. In the moist regions the diurnal amplitude and the mean surface temperature are controlled by the latent heat flux. In the dry areas, the relevant role of the stability of the boundary layer and of the soil thermal inertia is demonstrated. In these regions, the sensitivity of the surface temperature to the thermal inertia is high, due to the high contribution of the thermal flux to the energy budget. At high latitudes, when the sensitivity of turbulent fluxes is dominated by the day-time sensitivity of the sensible heat flux to the surface temperature and when this later is comparable to the thermal inertia term of the sensitivity equation, the surface temperature is also partially controlled by the thermal inertia which can rely on the snow properties; In the regions where the latent heat flux exhibits a high day-to-day variability, such as transition regions, the thermal inertia has also significant impact on the surface temperature variability . In these not too wet (energy limited) and not too dry (moisture-limited) soil moisture (SM) ''hot spots'', it is generally admitted that the variability of the surface temperature is explained by the soil moisture trough its control on the evaporation. This work suggests that the impact of the soil moisture on the temperature through its impact on the thermal inertia can be as important as its direct impact on the evaporation. Contrarily to the evaporation related soil-moisture temperature negative feedback, the thermal inertia soil-moisture related feedback newly identified by this work is a positive feedback which limits the cooling when the soil moisture increases. These results suggest that uncertainties in the representation of the soil and snow thermal properties can be responsible of significant biases in numerical simulations and emphasize the need to carefully document and evaluate these quantities in the Land Surface Modules implemented in the climate models.

Development, implementation, and validation of a modeling system for the San Francisco Bay and Estuary

NASA Astrophysics Data System (ADS)

Chao, Yi; Farrara, John D.; Zhang, Hongchun; Zhang, Yinglong J.; Ateljevich, Eli; Chai, Fei; Davis, Curtiss O.; Dugdale, Richard; Wilkerson, Frances

2017-07-01

A three-dimensional numerical modeling system for the San Francisco Bay is presented. The system is based on an unstructured grid numerical model known as Semi-implicit Cross-scale Hydroscience Integrated System Model (SCHISM). The lateral boundary condition is provided by a regional coastal ocean model. The surface forcing is provided by a regional atmospheric model. The SCHISM results from a decadal hindcast run are compared with available tide gauge data, as well as a collection of temperature and salinity profiles. An examination of the observed climatological annual mean salinities at the United States Geological Survey (USGS) stations shows the highest salinities to be in the open ocean and the lowest well north (upstream) of the Central Bay, a pattern that does not change substantially with season. The corresponding mean SCHISM salinities reproduced the observed variations with location quite well, though with a fresh bias. The lowest values within the Bay occur during spring and the highest values during autumn, mirroring the seasonal variations in river discharge. The corresponding observed mean temperatures within the Bay were 2 to 3° C cooler in the Central Bay than to either the north or south. This observed pattern of a cooler Central Bay was not particularly well reproduced in the SCHISM results, which also showed a cold bias. Examination of the seasonal means revealed that the cool Central Bay pattern is found only during summer in the SCHISM results. The persistent cold and fresh biases in the model control run were nearly eliminated in a sensitivity run with modifications to the surface heat flux and river discharge. The surface atmospheric forcing and the heat flux at the western boundary are found to be the two major terms in a SCHISM-based heat budget analysis of the mean seasonal temperature cycle for the Central Bay. In the Central Bay salt budget, freshwater discharged by rivers into upstream portions of the Bay to the north balanced by the influx of salt from the west are the primary drivers of the mean seasonal salinity cycle. Concerning the interannual variability in temperatures, the warm anomalies during the period 2014-16 were the strongest and most persistent departures from normal during the period analyzed and were realistically reproduced by SCHISM. The most prominent salinity anomalies in both the observations and SCHISM results were the salty anomalies that persisted for most of the four-year California drought of 2012-2015.

Zero bias STS Kondo anomalies of Co impurities on Cu surfaces: do ab initio calculations work?

NASA Astrophysics Data System (ADS)

Baruselli, Pier Paolo; Smogunov, Alexander; Fabrizio, Michele; Requist, Ryan; Tosatti, Erio

2012-02-01

Transition metal atoms such as Co on Cu (111), (100), and (110) surfaces produce STS I-V spectra showing different zero bias Kondo anomalies [1] but these differences have been neither quantitatively predicted nor fully explained theoretically. We apply to this problem the DFT+NRG scheme of Lucignano et al [2], where one solves by NRG an Anderson model built from ab initio phase shifts provided by DFT. For Co/Cu(100) and Co/Cu(110) our calculations describe correctly the experimental trend of Kondo temperatures, and fairly the lineshapes too. By contrast, they fail to describe Co/Cu(111) where in particular the anti-lorentzian lineshape found in experiment remains unexplained. This failure underscores the role of surface states, probably relevant for Co/Cu(111) [3] but not correctly described by our thin slab calculations. Future efforts to quantitatively include Kondo screening by surface states are therefore called for. 1. N. Knorr et al PRL 88, 096804 (2002); M. Ternes et al 2009 J. Phys.: Cond. Matt. 21, 053001 (2009); A. Gumbsch et al PRB81, 165420 (2010). 2. P. Lucignano et al Nature Mat. 8, 563 (2009); P.P. Baruselli et al, Physica E, doi:10.1016/j.physe.2011.05.005. 3. C. Lin et al. PRB 71, 035417 (2005).

Alleviating tropical Atlantic sector biases in the Kiel climate model by enhancing horizontal and vertical atmosphere model resolution: climatology and interannual variability

NASA Astrophysics Data System (ADS)

Harlaß, Jan; Latif, Mojib; Park, Wonsun

2018-04-01

We investigate the quality of simulating tropical Atlantic (TA) sector climatology and interannual variability in integrations of the Kiel climate model (KCM) with varying atmosphere model resolution. The ocean model resolution is kept fixed. A reasonable simulation of TA sector annual-mean climate, seasonal cycle and interannual variability can only be achieved at sufficiently high horizontal and vertical atmospheric resolution. Two major reasons for the improvements are identified. First, the western equatorial Atlantic westerly surface wind bias in spring can be largely eliminated, which is explained by a better representation of meridional and especially vertical zonal momentum transport. The enhanced atmospheric circulation along the equator in turn greatly improves the thermal structure of the upper equatorial Atlantic with much reduced warm sea surface temperature (SST) biases. Second, the coastline in the southeastern TA and steep orography are better resolved at high resolution, which improves wind structure and in turn reduces warm SST biases in the Benguela upwelling region. The strongly diminished wind and SST biases at high atmosphere model resolution allow for a more realistic latitudinal position of the intertropical convergence zone. Resulting stronger cross-equatorial winds, in conjunction with a shallower thermocline, enable a rapid cold tongue development in the eastern TA in boreal spring. This enables simulation of realistic interannual SST variability and its seasonal phase locking in the KCM, which primarily is the result of a stronger thermocline feedback. Our findings suggest that enhanced atmospheric resolution, both vertical and horizontal, could be a key to achieving more realistic simulation of TA climatology and interannual variability in climate models.

Atomic-scale distortions and temperature-dependent large pseudogap in thin films of the parent iron-chalcogenide superconductor Fe1+y Te

NASA Astrophysics Data System (ADS)

Gerbi, Andrea; Buzio, Renato; Kawale, Shrikant; Bellingeri, Emilio; Martinelli, Alberto; Bernini, Cristina; Tresca, Cesare; Capone, Massimo; Profeta, Gianni; Ferdeghini, Carlo

2017-12-01

We investigate with scanning tunneling microscopy/spectroscopy (STM/STS) and density functional theory (DFT) calculations the surface structures and the electronic properties of Fe1+y Te thin films grown by pulsed laser deposition. Contrary to the regular arrangement of antiferromagnetic nanostripes previously reported on cleaved single-crystal samples, the surface of Fe1+y Te thin films displays a peculiar distribution of spatially inhomogeneous nanostripes. Both STM and DFT calculations show the bias-dependent nature of such features and support the interpretation of spin-polarized tunneling between the FeTe surface and an unintentionally magnetized tip. In addition, the spatial inhomogeneity is interpreted as a purely electronic effect related to changes in hybridization and Fe-Fe bond length driven by local variations in the concentration of excess interstitial Fe cations. Unexpectedly, the surface density of states measured by STS strongly evolves with temperature in close proximity to the antiferromagnetic-paramagnetic first-order transition, and reveals a large pseudogap of 180-250 meV at about 50-65 K. We believe that in this temperature range a phase transition takes place, and the system orders and locks into particular combinations of orbitals and spins because of the interplay between excess interstitial magnetic Fe and strongly correlated d-electrons.

Late Cretaceous climate simulations with different CO2 levels and subarctic gateway configurations: A model-data comparison

NASA Astrophysics Data System (ADS)

Niezgodzki, Igor; Knorr, Gregor; Lohmann, Gerrit; Tyszka, Jarosław; Markwick, Paul J.

2017-09-01

We investigate the impact of different CO2 levels and different subarctic gateway configurations on the surface temperatures during the latest Cretaceous using the Earth System Model COSMOS. The simulated temperatures are compared with the surface temperature reconstructions based on a recent compilation of the latest Cretaceous proxies. In our numerical experiments, the CO2 level ranges from 1 to 6 times the preindustrial (PI) CO2 level of 280 ppm. On a global scale, the most reasonable match between modeling and proxy data is obtained for the experiments with 3 to 5 × PI CO2 concentrations. However, the simulated low- (high-) latitude temperatures are too high (low) as compared to the proxy data. The moderate CO2 levels scenarios might be more realistic, if we take into account proxy data and the dead zone effect criterion. Furthermore, we test if the model-data discrepancies can be caused by too simplistic proxy-data interpretations. This is distinctly seen at high latitudes, where most proxies are biased toward summer temperatures. Additional sensitivity experiments with different ocean gateway configurations and constant CO2 level indicate only minor surface temperatures changes (< 1°C) on a global scale, with higher values (up to 8°C) on a regional scale. These findings imply that modeled and reconstructed temperature gradients are to a large degree only qualitatively comparable, providing challenges for the interpretation of proxy data and/or model sensitivity. With respect to the latter, our results suggest that an assessment of greenhouse worlds is best constrained by temperatures in the midlatitudes.

Improving Subtropical Boundary Layer Cloudiness in the 2011 NCEP GFS

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

Fletcher, J. K.; Bretherton, Christopher S.; Xiao, Heng

2014-09-23

The current operational version of National Centers for Environmental Prediction (NCEP) Global Forecasting System (GFS) shows significant low cloud bias. These biases also appear in the Coupled Forecast System (CFS), which is developed from the GFS. These low cloud biases degrade seasonal and longer climate forecasts, particularly of short-wave cloud radiative forcing, and affect predicted sea surface temperature. Reducing this bias in the GFS will aid the development of future CFS versions and contributes to NCEP's goal of unified weather and climate modelling. Changes are made to the shallow convection and planetary boundary layer parameterisations to make them more consistentmore » with current knowledge of these processes and to reduce the low cloud bias. These changes are tested in a single-column version of GFS and in global simulations with GFS coupled to a dynamical ocean model. In the single-column model, we focus on changing parameters that set the following: the strength of shallow cumulus lateral entrainment, the conversion of updraught liquid water to precipitation and grid-scale condensate, shallow cumulus cloud top, and the effect of shallow convection in stratocumulus environments. Results show that these changes improve the single-column simulations when compared to large eddy simulations, in particular through decreasing the precipitation efficiency of boundary layer clouds. These changes, combined with a few other model improvements, also reduce boundary layer cloud and albedo biases in global coupled simulations.« less

Effect of negative bias on the composition and structure of the tungsten oxide thin films deposited by magnetron sputtering

NASA Astrophysics Data System (ADS)

Wang, Meihan; Lei, Hao; Wen, Jiaxing; Long, Haibo; Sawada, Yutaka; Hoshi, Yoichi; Uchida, Takayuki; Hou, Zhaoxia

2015-12-01

Tungsten oxide thin films were deposited at room temperature under different negative bias voltages (Vb, 0 to -500 V) by DC reactive magnetron sputtering, and then the as-deposited films were annealed at 500 °C in air atmosphere. The crystal structure, surface morphology, chemical composition and transmittance of the tungsten oxide thin films were characterized by X-ray diffraction (XRD), field emission scanning electron microscopy (FE-SEM), X-ray photoelectron spectroscopy (XPS) and UV-vis spectrophotometer. The XRD analysis reveals that the tungsten oxide films deposited at different negative bias voltages present a partly crystallized amorphous structure. All the films transfer from amorphous to crystalline (monoclinic + hexagonal) after annealing 3 h at 500 °C. Furthermore, the crystallized tungsten oxide films show different preferred orientation. The morphology of the tungsten oxide films deposited at different negative bias voltages is consisted of fine nanoscale grains. The grains grow up and conjunct with each other after annealing. The tungsten oxide films deposited at higher negative bias voltages after annealing show non-uniform special morphology. Substoichiometric tungsten oxide films were formed as evidenced by XPS spectra of W4f and O1s. As a result, semi-transparent films were obtained in the visible range for all films deposited at different negative bias voltages.

The Rossby Centre Regional Atmospheric Climate Model part II: application to the Arctic climate.

PubMed

Jones, Colin G; Wyser, Klaus; Ullerstig, Anders; Willén, Ulrika

2004-06-01

The Rossby Centre regional climate model (RCA2) has been integrated over the Arctic Ocean as part of the international ARCMIP project. Results have been compared to observations derived from the SHEBA data set. The standard RCA2 model overpredicts cloud cover and downwelling longwave radiation, during the Arctic winter. This error was improved by introducing a new cloud parameterization, which significantly improves the annual cycle of cloud cover. Compensating biases between clear sky downwelling longwave radiation and longwave radiation emitted from cloud base were identified. Modifications have been introduced to the model radiation scheme that more accurately treat solar radiation interaction with ice crystals. This leads to a more realistic representation of cloud-solar radiation interaction. The clear sky portion of the model radiation code transmits too much solar radiation through the atmosphere, producing a positive bias at the top of the frequent boundary layer clouds. A realistic treatment of the temporally evolving albedo, of both sea-ice and snow, appears crucial for an accurate simulation of the net surface energy budget. Likewise, inclusion of a prognostic snow-surface temperature seems necessary, to accurately simulate near-surface thermodynamic processes in the Arctic.

Detailed modeling of electron emission for transpiration cooling of hypersonic vehicles

NASA Astrophysics Data System (ADS)

Hanquist, Kyle M.; Hara, Kentaro; Boyd, Iain D.

2017-02-01

Electron transpiration cooling (ETC) is a recently proposed approach to manage the high heating loads experienced at the sharp leading edges of hypersonic vehicles. Computational fluid dynamics (CFD) can be used to investigate the feasibility of ETC in a hypersonic environment. A modeling approach is presented for ETC, which includes developing the boundary conditions for electron emission from the surface, accounting for the space-charge limit effects of the near-wall plasma sheath. The space-charge limit models are assessed using 1D direct-kinetic plasma sheath simulations, taking into account the thermionically emitted electrons from the surface. The simulations agree well with the space-charge limit theory proposed by Takamura et al. for emitted electrons with a finite temperature, especially at low values of wall bias, which validates the use of the theoretical model for the hypersonic CFD code. The CFD code with the analytical sheath models is then used for a test case typical of a leading edge radius in a hypersonic flight environment. The CFD results show that ETC can lower the surface temperature of sharp leading edges of hypersonic vehicles, especially at higher velocities, due to the increase in ionized species enabling higher electron heat extraction from the surface. The CFD results also show that space-charge limit effects can limit the ETC reduction of surface temperatures, in comparison to thermionic emission assuming no effects of the electric field within the sheath.

Noah-MP-Crop: Enhancing cropland representation in the community land surface modeling system

NASA Astrophysics Data System (ADS)

Liu, X.; Chen, F.; Barlage, M. J.; Zhou, G.; Niyogi, D.

2015-12-01

Croplands are important in land-atmosphere interactions and in modifying local and regional weather and climate. Despite their importance, croplands are poorly represented in the current version of the coupled Weather Research and Forecasting (WRF)/ Noah land-surface modeling system, resulting in significant surface temperature and humidity biases across agriculture- dominated regions of the United States. This study aims to improve the WRF weather forecasting and regional climate simulations during the crop growing season by enhancing the representation of cropland in the Noah-MP land model. We introduced dynamic crop growth parameterization into Noah-MP and evaluated the enhanced model (Noah-MP-Crop) at both the field and regional scales with multiple crop biomass datasets, surface fluxes and soil moisture/temperature observations. We also integrated a detailed cropland cover map into WRF, enabling the model to simulate corn and soybean field across the U.S. Great Plains. Results show marked improvement in the Noah-MP-Crop performance in simulating leaf area index (LAI), crop biomass, soil temperature, and surface fluxes. Enhanced cropland representation is not only crucial for improving weather forecasting but can also help assess potential impacts of weather variability on regional hydrometeorology and crop yields. In addition to its applications to WRF, Noah-MP-Crop can be applied in high-spatial-resolution regional crop yield modeling and drought assessments

Constructing a multidimensional free energy surface like a spider weaving a web.

PubMed

Chen, Changjun

2017-10-15

Complete free energy surface in the collective variable space provides important information of the reaction mechanisms of the molecules. But, sufficient sampling in the collective variable space is not easy. The space expands quickly with the number of the collective variables. To solve the problem, many methods utilize artificial biasing potentials to flatten out the original free energy surface of the molecule in the simulation. Their performances are sensitive to the definitions of the biasing potentials. Fast-growing biasing potential accelerates the sampling speed but decreases the accuracy of the free energy result. Slow-growing biasing potential gives an optimized result but needs more simulation time. In this article, we propose an alternative method. It adds the biasing potential to a representative point of the molecule in the collective variable space to improve the conformational sampling. And the free energy surface is calculated from the free energy gradient in the constrained simulation, not given by the negative of the biasing potential as previous methods. So the presented method does not require the biasing potential to remove all the barriers and basins on the free energy surface exactly. Practical applications show that the method in this work is able to produce the accurate free energy surfaces for different molecules in a short time period. The free energy errors are small in the cases of various biasing potentials. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Characterization of chromium compensated GaAs as an X-ray sensor material for charge-integrating pixel array detectors

NASA Astrophysics Data System (ADS)

Becker, J.; Tate, M. W.; Shanks, K. S.; Philipp, H. T.; Weiss, J. T.; Purohit, P.; Chamberlain, D.; Gruner, S. M.

2018-01-01

We studied the properties of chromium compensated GaAs when coupled to charge integrating ASICs as a function of detector temperature, applied bias and X-ray tube energy. The material is a photoresistor and can be biased to collect either electrons or holes by the pixel circuitry. Both are studied here. Previous studies have shown substantial hole trapping. This trapping and other sensor properties give rise to several non-ideal effects which include an extended point spread function, variations in the effective pixel size, and rate dependent offset shifts. The magnitude of these effects varies with temperature and bias, mandating good temperature uniformity in the sensor and very good temperature stabilization, as well as a carefully selected bias voltage.

GaInAsP/InP lateral-current-injection distributed feedback laser with a-Si surface grating.

PubMed

Shindo, Takahiko; Okumura, Tadashi; Ito, Hitomi; Koguchi, Takayuki; Takahashi, Daisuke; Atsumi, Yuki; Kang, Joonhyun; Osabe, Ryo; Amemiya, Tomohiro; Nishiyama, Nobuhiko; Arai, Shigehisa

2011-01-31

We fabricated a novel lateral-current-injection-type distributed feedback (DFB) laser with amorphous-Si (a-Si) surface grating as a step to realize membrane lasers. This laser consists of a thin GaInAsP core layer grown on a semi-insulating InP substrate and a 30-nm-thick a-Si surface layer for DFB grating. Under a room-temperature continuous-wave condition, a low threshold current of 7.0 mA and high efficiency of 43% from the front facet were obtained for a 2.0-μm stripe width and 300-μm cavity length. A small-signal modulation bandwidth of 4.8 GHz was obtained at a bias current of 30 mA.

Sensitivity of Pacific Cold Tongue and Double-ITCZ Bias to Convective Parameterization

NASA Astrophysics Data System (ADS)

Woelfle, M.; Bretherton, C. S.; Pritchard, M. S.; Yu, S.

2016-12-01

Many global climate models struggle to accurately simulate annual mean precipitation and sea surface temperature (SST) fields in the tropical Pacific basin. Precipitation biases are dominated by the double intertropical convergence zone (ITCZ) bias where models exhibit precipitation maxima straddling the equator while only a single Northern Hemispheric maximum exists in observations. The major SST bias is the enhancement of the equatorial cold tongue. A series of coupled model simulations are used to investigate the sensitivity of the bias development to convective parameterization. Model components are initialized independently prior to coupling to allow analysis of the transient response of the system directly following coupling. These experiments show precipitation and SST patterns to be highly sensitive to convective parameterization. Simulations in which the deep convective parameterization is disabled forcing all convection to be resolved by the shallow convection parameterization showed a degradation in both the cold tongue and double-ITCZ biases as precipitation becomes focused into off-equatorial regions of local SST maxima. Simulations using superparameterization in place of traditional cloud parameterizations showed a reduced cold tongue bias at the expense of additional precipitation biases. The equatorial SST responses to changes in convective parameterization are driven by changes in near equatorial zonal wind stress. The sensitivity of convection to SST is important in determining the precipitation and wind stress fields. However, differences in convective momentum transport also play a role. While no significant improvement is seen in these simulations of the double-ITCZ, the system's sensitivity to these changes reaffirm that improved convective parameterizations may provide an avenue for improving simulations of tropical Pacific precipitation and SST.

A Preliminary Evaluation of the GFS Physics in the Navy Global Environmental Model

NASA Astrophysics Data System (ADS)

Liu, M.; Langland, R.; Martini, M.; Viner, K.

2017-12-01

Global extended long-range weather forecast is a goal in the near future at Navy's Fleet Numerical Meteorology and Oceanography Center (FNMOC). In an effort to improve the performance of the Navy Global Environmental Model (NAVGEM) operated at FNMOC, and to gain more understanding of the impact of atmospheric physics in the long-range forecast, the physics package of the Global Forecast System (GFS) of the National Centers for Environmental Prediction is being evaluated in the framework of NAVGEM. That is GFS physics being transported by NAVGEM Semi-Lagrangian Semi-Implicit advection, and update-cycled by the 4D-variational data assimilation along with the assimilated land surface data of NASA's Land Information System. The output of free long runs of 10-day GFS physics forecast in a summer and a winter season are evaluated through the comparisons with the output of NAVGEM physics long forecast, and through the validations with observations and with the European Center's analyses data. It is found that the GFS physics is able to effectively reduce some of the modeling biases of NAVGEM, especially wind speed of the troposphere and land surface temperature that is an important surface boundary condition. The bias corrections increase with forecast leads, reaching maximum at 240 hours. To further understand the relative roles of physics and dynamics in extended long-range forecast, the tendencies of physics components and advection are also calculated and analyzed to compare their forces of magnitudes in the integration of winds, temperature, and moisture. The comparisons reveal the strength and limitation of GFS physics in the overall improvement of NAVGEM prediction system.

Estimating surface longwave radiative fluxes from satellites utilizing artificial neural networks

NASA Astrophysics Data System (ADS)

Nussbaumer, Eric A.; Pinker, Rachel T.

2012-04-01

A novel approach for calculating downwelling surface longwave (DSLW) radiation under all sky conditions is presented. The DSLW model (hereafter, DSLW/UMD v2) similarly to its predecessor, DSLW/UMD v1, is driven with a combination of Moderate Resolution Imaging Spectroradiometer (MODIS) level-3 cloud parameters and information from the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim model. To compute the clear sky component of DSLW a two layer feed-forward artificial neural network with sigmoid hidden neurons and linear output neurons is implemented; it is trained with simulations derived from runs of the Rapid Radiative Transfer Model (RRTM). When computing the cloud contribution to DSLW, the cloud base temperature is estimated by using an independent artificial neural network approach of similar architecture as previously mentioned, and parameterizations. The cloud base temperature neural network is trained using spatially and temporally co-located MODIS and CloudSat Cloud Profiling Radar (CPR) and the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) observations. Daily average estimates of DSLW from 2003 to 2009 are compared against ground measurements from the Baseline Surface Radiation Network (BSRN) giving an overall correlation coefficient of 0.98, root mean square error (rmse) of 15.84 W m-2, and a bias of -0.39 W m-2. This is an improvement over an earlier version of the model (DSLW/UMD v1) which for the same time period has an overall correlation coefficient 0.97 rmse of 17.27 W m-2, and bias of 0.73 W m-2.

Temperature effects on pitfall catches of epigeal arthropods: a model and method for bias correction.

PubMed

Saska, Pavel; van der Werf, Wopke; Hemerik, Lia; Luff, Martin L; Hatten, Timothy D; Honek, Alois; Pocock, Michael

2013-02-01

Carabids and other epigeal arthropods make important contributions to biodiversity, food webs and biocontrol of invertebrate pests and weeds. Pitfall trapping is widely used for sampling carabid populations, but this technique yields biased estimates of abundance ('activity-density') because individual activity - which is affected by climatic factors - affects the rate of catch. To date, the impact of temperature on pitfall catches, while suspected to be large, has not been quantified, and no method is available to account for it. This lack of knowledge and the unavailability of a method for bias correction affect the confidence that can be placed on results of ecological field studies based on pitfall data.Here, we develop a simple model for the effect of temperature, assuming a constant proportional change in the rate of catch per °C change in temperature, r , consistent with an exponential Q 10 response to temperature. We fit this model to 38 time series of pitfall catches and accompanying temperature records from the literature, using first differences and other detrending methods to account for seasonality. We use meta-analysis to assess consistency of the estimated parameter r among studies.The mean rate of increase in total catch across data sets was 0·0863 ± 0·0058 per °C of maximum temperature and 0·0497 ± 0·0107 per °C of minimum temperature. Multiple regression analyses of 19 data sets showed that temperature is the key climatic variable affecting total catch. Relationships between temperature and catch were also identified at species level. Correction for temperature bias had substantial effects on seasonal trends of carabid catches. Synthesis and Applications . The effect of temperature on pitfall catches is shown here to be substantial and worthy of consideration when interpreting results of pitfall trapping. The exponential model can be used both for effect estimation and for bias correction of observed data. Correcting for temperature-related trapping bias is straightforward and enables population estimates to be more comparable. It may thus improve data interpretation in ecological, conservation and monitoring studies, and assist in better management and conservation of habitats and ecosystem services. Nevertheless, field ecologists should remain vigilant for other sources of bias.

Precise Temperature Mapping of GaN-Based LEDs by Quantitative Infrared Micro-Thermography

PubMed Central

Chang, Ki Soo; Yang, Sun Choel; Kim, Jae-Young; Kook, Myung Ho; Ryu, Seon Young; Choi, Hae Young; Kim, Geon Hee

2012-01-01

A method of measuring the precise temperature distribution of GaN-based light-emitting diodes (LEDs) by quantitative infrared micro-thermography is reported. To reduce the calibration error, the same measuring conditions were used for both calibration and thermal imaging; calibration was conducted on a highly emissive black-painted area on a dummy sapphire wafer loaded near the LED wafer on a thermoelectric cooler mount. We used infrared thermal radiation images of the black-painted area on the dummy wafer and an unbiased LED wafer at two different temperatures to determine the factors that degrade the accuracy of temperature measurement, i.e., the non-uniform response of the instrument, superimposed offset radiation, reflected radiation, and emissivity map of the LED surface. By correcting these factors from the measured infrared thermal radiation images of biased LEDs, we determined a precise absolute temperature image. Consequently, we could observe from where the local self-heat emerges and how it distributes on the emitting area of the LEDs. The experimental results demonstrated that highly localized self-heating and a remarkable temperature gradient, which are detrimental to LED performance and reliability, arise near the p-contact edge of the LED surface at high injection levels owing to the current crowding effect. PMID:22666050

Internal Variability and Disequilibrium Confound Estimates of Climate Sensitivity from Observations

NASA Technical Reports Server (NTRS)

Marvel, Kate; Pincus, Robert; Schmidt, Gavin A.; Miller, Ron L.

2018-01-01

An emerging literature suggests that estimates of equilibrium climate sensitivity (ECS) derived from recent observations and energy balance models are biased low because models project more positive climate feedback in the far future. Here we use simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5) to show that across models, ECS inferred from the recent historical period (1979-2005) is indeed almost uniformly lower than that inferred from simulations subject to abrupt increases in CO2-radiative forcing. However, ECS inferred from simulations in which sea surface temperatures are prescribed according to observations is lower still. ECS inferred from simulations with prescribed sea surface temperatures is strongly linked to changes to tropical marine low clouds. However, feedbacks from these clouds are a weak constraint on long-term model ECS. One interpretation is that observations of recent climate changes constitute a poor direct proxy for long-term sensitivity.

Internal Variability and Disequilibrium Confound Estimates of Climate Sensitivity From Observations

NASA Astrophysics Data System (ADS)

Marvel, Kate; Pincus, Robert; Schmidt, Gavin A.; Miller, Ron L.

2018-02-01

An emerging literature suggests that estimates of equilibrium climate sensitivity (ECS) derived from recent observations and energy balance models are biased low because models project more positive climate feedback in the far future. Here we use simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5) to show that across models, ECS inferred from the recent historical period (1979-2005) is indeed almost uniformly lower than that inferred from simulations subject to abrupt increases in CO2 radiative forcing. However, ECS inferred from simulations in which sea surface temperatures are prescribed according to observations is lower still. ECS inferred from simulations with prescribed sea surface temperatures is strongly linked to changes to tropical marine low clouds. However, feedbacks from these clouds are a weak constraint on long-term model ECS. One interpretation is that observations of recent climate changes constitute a poor direct proxy for long-term sensitivity.

Satellite-Derived Sea Surface Temperature: Workshop 3

NASA Technical Reports Server (NTRS)

1985-01-01

This is the third of a series of three workshops, sponsored by the National Aeronautics and Space Administration, to investigate the state of the art in global sea surface temperature measurements from space. Three workshops were necessary to process and analyze sufficient data from which to draw conclusions on the accuracy and reliability of the satellite measurements. In this workshop, the final two (out of a total of four) months of satellite and in situ data chosen for study were processed and evaluated. Results from the AVHRR, HIRS, SMMR, and VAS sensors, in comparison with in situ data from ships, XBTs, and buoys, confirmed satellite rms accuracies in the 0.5 to 1.0 C range, but with variable biases. These accuracies may degrade under adverse conditions for specific sensors. A variety of color maps, plots, and statistical tables are provided for detailed study of the individual sensor SST measurements.

Contributions of Heterogeneous Ice Nucleation, Large-Scale Circulation, and Shallow Cumulus Detrainment to Cloud Phase Transition in Mixed-Phase Clouds with NCAR CAM5

NASA Astrophysics Data System (ADS)

Liu, X.; Wang, Y.; Zhang, D.; Wang, Z.

2016-12-01

Mixed-phase clouds consisting of both liquid and ice water occur frequently at high-latitudes and in mid-latitude storm track regions. This type of clouds has been shown to play a critical role in the surface energy balance, surface air temperature, and sea ice melting in the Arctic. Cloud phase partitioning between liquid and ice water determines the cloud optical depth of mixed-phase clouds because of distinct optical properties of liquid and ice hydrometeors. The representation and simulation of cloud phase partitioning in state-of-the-art global climate models (GCMs) are associated with large biases. In this study, the cloud phase partition in mixed-phase clouds simulated from the NCAR Community Atmosphere Model version 5 (CAM5) is evaluated against satellite observations. Observation-based supercooled liquid fraction (SLF) is calculated from CloudSat, MODIS and CPR radar detected liquid and ice water paths for clouds with cloud-top temperatures between -40 and 0°C. Sensitivity tests with CAM5 are conducted for different heterogeneous ice nucleation parameterizations with respect to aerosol influence (Wang et al., 2014), different phase transition temperatures for detrained cloud water from shallow convection (Kay et al., 2016), and different CAM5 model configurations (free-run versus nudged winds and temperature, Zhang et al., 2015). A classical nucleation theory-based ice nucleation parameterization in mixed-phase clouds increases the SLF especially at temperatures colder than -20°C, and significantly improves the model agreement with observations in the Arctic. The change of transition temperature for detrained cloud water increases the SLF at higher temperatures and improves the SLF mostly over the Southern Ocean. Even with the improved SLF from the ice nucleation and shallow cumulus detrainment, the low SLF biases in some regions can only be improved through the improved circulation with the nudging technique. Our study highlights the challenges of representations of large-scale moisture transport, cloud microphysics, ice nucleation, and cumulus detrainment in order to improve the mixed-phase transition in GCMs.

Zero-bias offsets in I-V characteristics of the staircase type quantum well infrared photodetectors

NASA Astrophysics Data System (ADS)

Nutku, Ferhat; Erol, Ayse; Arikan, M. Cetin; Ergun, Yuksel

2014-11-01

In this work, observed zero-bias offsets in I-V characteristics and differences in J-V characteristics of staircase quantum well infrared photodetectors were investigated. Temperature and voltage sweep rate dependence of the zero-bias offsets were studied on mesa structures shaped in different diameters. Furthermore, effect of mesa diameter on J-V characteristics was investigated. The temperature, initial bias voltage and voltage sweep rate dependence of the zero-bias offsets were explained by a qualitative model, which is based on a RC equivalent circuit of the quantum well infrared photodetector.

Foreground Bias from Parametric Models of Far-IR Dust Emission

NASA Technical Reports Server (NTRS)

Kogut, A.; Fixsen, D. J.

2016-01-01

We use simple toy models of far-IR dust emission to estimate the accuracy to which the polarization of the cosmic microwave background can be recovered using multi-frequency fits, if the parametric form chosen for the fitted dust model differs from the actual dust emission. Commonly used approximations to the far-IR dust spectrum yield CMB residuals comparable to or larger than the sensitivities expected for the next generation of CMB missions, despite fitting the combined CMB plus foreground emission to precision 0.1 percent or better. The Rayleigh-Jeans approximation to the dust spectrum biases the fitted dust spectral index by (Delta)(Beta)(sub d) = 0.2 and the inflationary B-mode amplitude by (Delta)(r) = 0.03. Fitting the dust to a modified blackbody at a single temperature biases the best-fit CMB by (Delta)(r) greater than 0.003 if the true dust spectrum contains multiple temperature components. A 13-parameter model fitting two temperature components reduces this bias by an order of magnitude if the true dust spectrum is in fact a simple superposition of emission at different temperatures, but fails at the level (Delta)(r) = 0.006 for dust whose spectral index varies with frequency. Restricting the observing frequencies to a narrow region near the foreground minimum reduces these biases for some dust spectra but can increase the bias for others. Data at THz frequencies surrounding the peak of the dust emission can mitigate these biases while providing a direct determination of the dust temperature profile.

Clumped Isotope Thermometry Reveals Variations in Soil Carbonate Seasonal Biases Over >4 km of Relief in the Semi-Arid Andes of Central Chile

NASA Astrophysics Data System (ADS)

Burgener, L. K.; Huntington, K. W.; Hoke, G. D.; Schauer, A. J.; Ringham, M. C.; Latorre Hidalgo, C.; Díaz, F.

2015-12-01

The application of carbonate clumped isotope thermometry to soil carbonates has the potential to shed new light on questions regarding terrestrial paleoclimate. In order to better utilize this paleoclimate tool, outstanding questions regarding seasonal biases in soil carbonate formation and the relationship between soil carbonate formation temperatures (T(Δ47)) and surface temperatures must be resolved. We address these questions by comparing C, O, and clumped isotope data from Holocene/modern soil carbonates to modern meteorological data. The data were collected along a 170 km transect with >4 km of relief in central Chile (~30°S). Previous studies have suggested that soil carbonates should record a warm season bias and form in isotopic equilibrium with soil water and soil CO2. We identify two discrete climate zones separated by the local winter snow line (~3200 m). Below this boundary, precipitation falls as rain and soil carbonate T(Δ47) values at depths >40 cm resemble summer soil temperatures; at higher elevations, precipitation falls as snow and T(Δ47) values resemble mean annual soil temperatures. Soil carbonates from the highest sample site (4700 m), which is devoid of vegetation and located near perennial snow fields, yield anomalous δ18O, δ13C, and T(Δ47) values, indicative of kinetic isotope effects that we attribute to cryogenic carbonate formation. Our results suggest that soil carbonates from depths <40 cm are affected by large, high frequency variations in temperature and precipitation, and should not be used as paleotemperature proxies. These findings (1) highlight the role of soil moisture in modulating soil carbonate formation and the resulting T(Δ47) values, (2) underscore the importance of understanding past soil moisture conditions when attempting to reconstruct paleotemperatures using carbonate clumped isotope thermometry, and (3) suggest that soil carbonates from high elevation or high latitude sites may form under non-equilibrium conditions.

Precipitation phase partitioning variability across the Northern Hemisphere

NASA Astrophysics Data System (ADS)

Jennings, K. S.; Winchell, T. S.; Livneh, B.; Molotch, N. P.

2017-12-01

Precipitation phase drives myriad hydrologic, climatic, and biogeochemical processes. Despite its importance, many of the land surface models used to simulate such processes and their sensitivity to climate warming rely on simple, spatially uniform air temperature thresholds to partition rainfall and snowfall. Our analysis of a 29-year dataset with 18.7 million observations of precipitation phase from 12,143 stations across the Northern Hemisphere land surface showed marked spatial variability in the near-surface air temperature at which precipitation is equally likely to fall as rain and snow, the 50% rain-snow threshold. This value averaged 1.0°C and ranged from -0.4°C to 2.4°C for 95% of the stations analyzed. High-elevation continental areas such as the Rocky Mountains of the western U.S. and the Tibetan Plateau of central Asia generally exhibited the warmest thresholds, in some cases exceeding 3.0°C. Conversely, the coldest thresholds were observed on the Pacific Coast of North America, the southeast U.S., and parts of Eurasia, with values dropping below -0.5°C. Analysis of the meteorological conditions during storm events showed relative humidity exerted the strongest control on phase partitioning, with surface pressure playing a secondary role. Lower relative humidity and surface pressure were both associated with warmer 50% rain-snow thresholds. Additionally, we trained a binary logistic regression model on the observations to classify rain and snow events and found including relative humidity as a predictor variable significantly increased model performance between 0.6°C and 3.8°C when phase partitioning is most uncertain. We then used the optimized model and a spatially continuous reanalysis product to map the 50% rain-snow threshold across the Northern Hemisphere. The map reproduced patterns in the observed thresholds with a mean bias of 0.5°C relative to the station data. The above results suggest land surface models could be improved by incorporating relative humidity into their precipitation phase prediction schemes or by using a spatially variable, optimized rain-snow temperature threshold. This is particularly important for climate warming simulations where misdiagnosing a shift from snow to rain or inaccurately quantifying snowfall fraction would likely lead to biased results.

Improving Numerical Weather Predictions of Summertime Precipitation Over the Southeastern U.S. Through a High-Resolution Initialization of the Surface State

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; Kumar, Sujay V.; Krikishen, Jayanthi; Jedlovec, Gary J.

2011-01-01

It is hypothesized that high-resolution, accurate representations of surface properties such as soil moisture and sea surface temperature are necessary to improve simulations of summertime pulse-type convective precipitation in high resolution models. This paper presents model verification results of a case study period from June-August 2008 over the Southeastern U.S. using the Weather Research and Forecasting numerical weather prediction model. Experimental simulations initialized with high-resolution land surface fields from the NASA Land Information System (LIS) and sea surface temperature (SST) derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) are compared to a set of control simulations initialized with interpolated fields from the National Centers for Environmental Prediction 12-km North American Mesoscale model. The LIS land surface and MODIS SSTs provide a more detailed surface initialization at a resolution comparable to the 4-km model grid spacing. Soil moisture from the LIS spin-up run is shown to respond better to the extreme rainfall of Tropical Storm Fay in August 2008 over the Florida peninsula. The LIS has slightly lower errors and higher anomaly correlations in the top soil layer, but exhibits a stronger dry bias in the root zone. The model sensitivity to the alternative surface initial conditions is examined for a sample case, showing that the LIS/MODIS data substantially impact surface and boundary layer properties.

Numerical Representation of Wintertime Near-Surface Inversions in the Arctic with a 2.5-km Version of the Global Environmental Multiscale (GEM) Model

NASA Astrophysics Data System (ADS)

Dehghan, A.; Mariani, Z.; Gascon, G.; Bélair, S.; Milbrandt, J.; Joe, P. I.; Crawford, R.; Melo, S.

2017-12-01

Environment and Climate Change Canada (ECCC) is implementing a 2.5-km resolution version of the Global Environmental Multiscale (GEM) model over the Canadian Arctic. Radiosonde observations were used to evaluate the numerical representation of surface-based temperature inversion which is a major feature in the Arctic region. Arctic surface-based inversions are often created by imbalance between radiative cooling processes at surface and warm air advection above. This can have a significant effect on vertical mixing of pollutants and moisture, and ultimately, on cloud formation. It is therefore important to correctly predict the existence of surface inversions along with their characteristics (i.e., intensity and depth). Previous climatological studies showed that the frequency and intensity of surface-based inversions are larger during colder months in the Arctic. Therefore, surface-based inversions were estimated using radiosonde measurements during winter (December 2015 to February 2016) at Iqaluit (Nunavut, Canada). Results show that the inversion intensity can exceed 10 K with depths as large as 1 km. Preliminary evaluation of GEM outputs reveals that the model tends to underestimate the intensity of near-surface inversions, and in some cases, the model failed to predict an inversion. This study presents the factors contributing to this bias including surface temperature and snow cover.

Reliability of self-aligned, ledge passivated 7.5 GHz GaAs/AlGaAs HBT power amplifiers under RF bias stress at elevated temperatures

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

Henderson, T.S.; Ikalainen, P.K.

1995-12-31

The authors report a two-temperature RF bias stress test on nominal 1.2 W 7.5 GHz GaAs/AlGaAs HBT unit cell amplifiers. MTTF`s of 2020 and 1340 hours were obtained at Tj = 218{degrees}C and 245{degrees}C, respectively, under nominal input bias. An activation energy of 0.42 eV is estimated, consistent with published results for similar devices under DC bias stress.

Hindcasting 2000 years of Pacific sea and land surface temperature changes

NASA Astrophysics Data System (ADS)

Friedel, M. J.

2010-12-01

Studies of climate variability often rely on surface temperature change anomalies. Here regional Pacific sea and land surface temperature data were extended from a century to millennial scale using a type of unsupervised artificial neural network. In this approach, the imputation of annual climate fields was done based on the nonlinear and self-organized relations among modern (1897-2003) sea and land temperature and paleo-proxy (0-2000) land-based Palmer Drought Severity Index data vectors. Stochastic crossvalidation (using median values from 30 Monte Carlo trials) of the model revealed that predictions of temperature change over the regions of 00N30N, 30N60N, 60N-90N, and 60S-60N latitude were globally unbiased and highly correlated (Spearman Rho > 0.94) with the modern observations. The prediction uncertainty was characterized as nonlinear with minor (<5%) local bias attributed to unaccounted for measurement uncertainty. Quantile modeling of the reconstructed temperature change data revealed interruptions in the long-term climate record by short-term changes that coincided with the so-called Medieval Warm Period (~900 to ~1250) and Little Ice Age (~1400 to ~1850). These interruptions were present at all latitudes but the structure shifted toward lower magnitudes as the region moved toward the equator. In all cases, the maximum temperature change was slightly greater than during the Medieval Warm Period. These findings demonstrated that the El Niño Southern Oscillation operated over a continuum of temporal and spatial scales. These findings have broad economic, political, and social implications with respect to developing water resource policies.

Forward- and reverse-bias tunneling effects in n/+/p silicon solar cells

NASA Technical Reports Server (NTRS)

Garlick, G. F. J.; Kachare, A. H.

1980-01-01

Excess currents due to field-assisted tunneling in both forward and reverse bias directions have been observed in n(+)-p silicon solar cells. These currents arise from the effect of conducting paths produced in the depletion layer by n(+) diffusion and cell processing. Forward-bias data indicate a small potential barrier with height of 0.04 eV at the n(+) end of conducting paths. Under reverse bias, excess tunneling currents involve a potential barrier at the p end of the conducting paths, the longer paths being associated with smaller barrier heights and dominating at the lower temperatures. Low-reverse-bias data give energy levels of 0.11 eV for lower temperatures (253-293 K) and 0.35 eV for higher temperatures (293-380 K). A model is suggested to explain the results.

Comparison of Blackbody Sources for Low-Temperature IR Calibration

NASA Astrophysics Data System (ADS)

Ljungblad, S.; Holmsten, M.; Josefson, L. E.; Klason, P.

2015-12-01

Radiation thermometers are traditionally mostly used in high-temperature applications. They are, however, becoming more common in different applications at room temperature or below, in applications such as monitoring frozen food and evaluating heat leakage in buildings. To measure temperature accurately with a pyrometer, calibration is essential. A problem with traditional, commercially available, blackbody sources is that ice is often formed on the surface when measuring temperatures below 0°C. This is due to the humidity of the surrounding air and, as ice does not have the same emissivity as the blackbody source, it biases the measurements. An alternative to a traditional blackbody source has been tested by SP Technical Research Institute of Sweden. The objective is to find a cost-efficient method of calibrating pyrometers by comparison at the level of accuracy required for the intended use. A disc-shaped blackbody with a surface pyramid pattern is placed in a climatic chamber with an opening for field of view of the pyrometer. The temperature of the climatic chamber is measured with two platinum resistance thermometers in the air in the vicinity of the disc. As a rule, frost will form only if the deposition surface is colder than the surrounding air, and, as this is not the case when the air of the climatic chamber is cooled, there should be no frost or ice formed on the blackbody surface. To test the disc-shaped blackbody source, a blackbody cavity immersed in a conventional stirred liquid bath was used as a reference blackbody source. Two different pyrometers were calibrated by comparison using the two different blackbody sources, and the results were compared. The results of the measurements show that the disc works as intended and is suitable as a blackbody radiation source.

Combined effects of wind and solar irradiance on the spatial variation of midday air temperature over a mountainous terrain

NASA Astrophysics Data System (ADS)

Kim, Soo-Ock; Kim, Jin-Hee; Kim, Dae-Jun; Shim, Kyo Moon; Yun, Jin I.

2015-08-01

When the midday temperature distribution in a mountainous region was estimated using data from a nearby weather station, the correction of elevation difference based on temperature lapse caused a large error. An empirical approach reflecting the effects of solar irradiance and advection was suggested in order to increase the reliability of the results. The normalized slope irradiance, which was determined by normalizing the solar irradiance difference between a horizontal surface and a sloping surface from 1100 to 1500 LST on a clear day, and the deviation relationship between the horizontal surface and the sloping surface at the 1500 LST temperature on each day were presented as simple empirical formulas. In order to simulate the phenomenon that causes immigrant air parcels to push out or mix with the existing air parcels in order to decrease the solar radiation effects, an advection correction factor was added to exponentially reduce the solar radiation effect with an increase in wind speed. In order to validate this technique, we estimated the 1500 LST air temperatures on 177 clear days in 2012 and 2013 at 10 sites with different slope aspects in a mountainous catchment and compared these values to the actual measured data. The results showed that this technique greatly improved the error bias and the overestimation of the solar radiation effect in comparison with the existing methods. By applying this technique to the Korea Meteorological Administration's 5-km grid data, it was possible to determine the temperature distribution at a 30-m resolution over a mountainous rural area south of Jiri Mountain National Park, Korea.

The accuracy of temperature distributions used to derive the net transport for a zonally averaged model

NASA Technical Reports Server (NTRS)

Remsberg, Ellis E.; Bhatt, Praful P.

1994-01-01

Comparisons of satellite-derived temperatures with correlative temperatures indicate that the LIMS temperatures are accurate and contain more of the needed vertical resolution for calculating a residual mean circulation for transporting tracer-like species. Generally, the LIMS temperatures are accurate to at least 2 K. Other satellite data sets are comprised of temperatures with coarser vertical resolution, leading to biases that occur with an error pattern that is characteristic of their resolution. Their biases exceed 2 K at some altitudes. Retrievals of species using an infrared limb emission technique are sensitive to any temperature bias. Generally, the IMS comparisons with other data sets for ozone and water vapor are good to better than 20 percent; this represents an independent confirmation of the quality of LIMS and temperatures. Zonal mean comparisons between LIMS and SAMS temperatures also indicate agreement to better than 2 K from about 7 to 2hPa. Therefore, we are confident that SAMS N2O and CH4 are relatively free of temperature bias in that region. These factors support the generally good agreement in G90 between model N2O transported using a LIMS-derived RMC and the N2O contours from SAMS.

Simultaneous Assimilation of AMSR-E Brightness Temperature and MODIS LST to Improve Soil Moisture with Dual Ensemble Kalman Smoother

NASA Astrophysics Data System (ADS)

Huang, Chunlin; Chen, Weijin; Wang, Weizhen; Gu, Juan

2017-04-01

Uncertainties in model parameters can easily cause systematic differences between model states and observations from ground or satellites, which significantly affect the accuracy of soil moisture estimation in data assimilation systems. In this paper, a novel soil moisture assimilation scheme is developed to simultaneously assimilate AMSR-E brightness temperature (TB) and MODIS Land Surface Temperature (LST), which can correct model bias by simultaneously updating model states and parameters with dual ensemble Kalman filter (DEnKS). The Common Land Model (CoLM) and a Q-h Radiative Transfer Model (RTM) are adopted as model operator and observation operator, respectively. The assimilation experiment is conducted in Naqu, Tibet Plateau, from May 31 to September 27, 2011. Compared with in-situ measurements, the accuracy of soil moisture estimation is tremendously improved in terms of a variety of scales. The updated soil temperature by assimilating MODIS LST as input of RTM can reduce the differences between the simulated and observed brightness temperatures to a certain degree, which helps to improve the estimation of soil moisture and model parameters. The updated parameters show large discrepancy with the default ones and the former effectively reduces the states bias of CoLM. Results demonstrate the potential of assimilating both microwave TB and MODIS LST to improve the estimation of soil moisture and related parameters. Furthermore, this study also indicates that the developed scheme is an effective soil moisture downscaling approach for coarse-scale microwave TB.

Tropical Indian Ocean surface salinity bias in Climate Forecasting System coupled models and the role of upper ocean processes

NASA Astrophysics Data System (ADS)

Parekh, Anant; Chowdary, Jasti S.; Sayantani, Ojha; Fousiya, T. S.; Gnanaseelan, C.

2016-04-01

In the present study sea surface salinity (SSS) biases and seasonal tendency over the Tropical Indian Ocean (TIO) in the coupled models [Climate Forecasting System version 1 (CFSv1) and version 2 (CFSv2)] are examined with respect to observations. Both CFSv1 and CFSv2 overestimate SSS over the TIO throughout the year. CFSv1 displays improper SSS seasonal cycle over the Bay of Bengal (BoB), which is due to weaker model precipitation and improper river runoff especially during summer and fall. Over the southeastern Arabian Sea (AS) weak horizontal advection associated with East Indian coastal current during winter limits the formation of spring fresh water pool. On the other hand, weaker Somali jet during summer results for reduced positive salt tendency in the central and eastern AS. Strong positive precipitation bias in CFSv1 over the region off Somalia during winter, weaker vertical mixing and absence of horizontal salt advection lead to unrealistic barrier layer during winter and spring. The weaker stratification and improper spatial distribution of barrier layer thickness (BLT) in CFSv1 indicate that not only horizontal flux distribution but also vertical salt distribution displays large discrepancies. Absence of fall Wyrtki jet and winter equatorial currents in this model limit the advection of horizontal salt flux to the eastern equatorial Indian Ocean. The associated weaker stratification in eastern equatorial Indian Ocean can lead to deeper mixed layer and negative Sea Surface Temperature (SST) bias, which in turn favor positive Indian Ocean Dipole bias in CFSv1. It is important to note that improper spatial distribution of barrier layer and stratification can alter the air-sea interaction and precipitation in the models. On the other hand CFSv2 could produce the seasonal evolution and spatial distribution of SSS, BLT and stratification better than CFSv1. However CFSv2 displays positive bias in evaporation over the whole domain and negative bias in precipitation over the BoB and equatorial Indian Ocean, resulting net reduction in the fresh water availability. This net reduction in fresh water forcing and the associated weaker stratification lead to deeper (than observed) mixed layer depth and is primarily responsible for the cold SST bias in CFSv2. However overall improvement of mean salinity distribution in CFSv2 is about 30 % and the mean error has reduced by more than 1 psu over the BoB. This improvement is mainly due to better fresh water forcing and model physics. Realistic run off information, better ocean model and high resolution in CFSv2 contributed for the improvement. Further improvement can be achieved by reducing biases in the moisture flux and precipitation.

Estimates of surface humidity and latent heat fluxes over oceans from SSM/I data

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

Cho, S.H.; Atlas, R.M.; Shie, C.L.

1995-08-01

Monthly averages of daily latent heat fluxes over the oceans for February and August 1988 are estimated using a stability-dependent bulk scheme. Daily fluxes are computed from daily SSM/I (Special Sensor Microwave/Imager) wind speeds and EOF-retrieved SSM/I surface humidity, National Meteorological Center sea surface temperatures, and the European Centre for Medium-Range Weather Forecasts analyzed 2-m temperatures. Daily surface specific humidity (Q) is estimated from SSM/I precipitable water of total (W) and a 500-m bottom layer (W{sub B}) using an EOF (empirical orthogonal function) method. This method has six W-based categories of EOFs (independent of geographical locations) and is developed usingmore » 23 177 FGGE IIb humidity soundings over the global oceans. For 1200 FGGE IIb humidity soundings, the accuracy of EOF-retrieved Q is 0.75 g kg{sup -1} for the case without errors in W and W{sub B} and increases to 1.16 g kg{sup -1} for the case with errors in W and W{sub B}. Compared to 342 collocated radiosonde observations, the EOF-retrieved SSM/I Q has an accuracy of 1.7 g kg{sup -1}. The method improves upon the humidity retrieval of Liu and is competitive with that of Schulz et al. The SSM/I surface humidity and latent heat fluxes of these two months agree reasonably well with those of COADS (Comprehensive Ocean-Atmosphere Data Set). Compared to the COADS, the sea-air humidity difference of SSM/I has a positive bias of approximately 1-3 g kg{sup -1} (an overestimation of flux) over the wintertime eastern equatorial Pacific Ocean, it has a negative bias of about 1-2 g kg{sup -1} (an underestimation of flux). The results further suggest that the two monthly flux estimates, computed from daily and monthly mean data, do not differ significantly over the oceans. 35 refs., 12 figs., 4 tabs.« less

Assessing Confidence in Pliocene Sea Surface Temperatures to Evaluate Predictive Models

NASA Technical Reports Server (NTRS)

Dowsett, Harry J.; Robinson, Marci M.; Haywood, Alan M.; Hill, Daniel J.; Dolan, Aisling. M.; Chan, Wing-Le; Abe-Ouchi, Ayako; Chandler, Mark A.; Rosenbloom, Nan A.; Otto-Bliesner, Bette L.;

Assessing confidence in Pliocene sea surface temperatures to evaluate predictive models

USGS Publications Warehouse

Dowsett, Harry J.; Robinson, Marci M.; Haywood, Alan M.; Hill, Daniel J.; Dolan, Aisling M.; Stoll, Danielle K.; Chan, Wing-Le; Abe-Ouchi, Ayako; Chandler, Mark A.; Rosenbloom, Nan A.; Otto-Bliesner, Bette L.; Bragg, Fran J.; Lunt, Daniel J.; Foley, Kevin M.; Riesselman, Christina R.

2012-01-01

In light of mounting empirical evidence that planetary warming is well underway, the climate research community looks to palaeoclimate research for a ground-truthing measure with which to test the accuracy of future climate simulations. Model experiments that attempt to simulate climates of the past serve to identify both similarities and differences between two climate states and, when compared with simulations run by other models and with geological data, to identify model-specific biases. Uncertainties associated with both the data and the models must be considered in such an exercise. The most recent period of sustained global warmth similar to what is projected for the near future occurred about 3.3–3.0 million years ago, during the Pliocene epoch. Here, we present Pliocene sea surface temperature data, newly characterized in terms of level of confidence, along with initial experimental results from four climate models. We conclude that, in terms of sea surface temperature, models are in good agreement with estimates of Pliocene sea surface temperature in most regions except the North Atlantic. Our analysis indicates that the discrepancy between the Pliocene proxy data and model simulations in the mid-latitudes of the North Atlantic, where models underestimate warming shown by our highest-confidence data, may provide a new perspective and insight into the predictive abilities of these models in simulating a past warm interval in Earth history. This is important because the Pliocene has a number of parallels to present predictions of late twenty-first century climate.

MesoNAM Verification Phase II

NASA Technical Reports Server (NTRS)

Watson, Leela R.

2011-01-01

The 45th Weather Squadron Launch Weather Officers use the 12-km resolution North American Mesoscale model (MesoNAM) forecasts to support launch weather operations. In Phase I, the performance of the model at KSC/CCAFS was measured objectively by conducting a detailed statistical analysis of model output compared to observed values. The objective analysis compared the MesoNAM forecast winds, temperature, and dew point to the observed values from the sensors in the KSC/CCAFS wind tower network. In Phase II, the AMU modified the current tool by adding an additional 15 months of model output to the database and recalculating the verification statistics. The bias, standard deviation of bias, Root Mean Square Error, and Hypothesis test for bias were calculated to verify the performance of the model. The results indicated that the accuracy decreased as the forecast progressed, there was a diurnal signal in temperature with a cool bias during the late night and a warm bias during the afternoon, and there was a diurnal signal in dewpoint temperature with a low bias during the afternoon and a high bias during the late night.

Simulated building energy demand biases resulting from the use of representative weather stations

DOE PAGES

Burleyson, Casey D.; Voisin, Nathalie; Taylor, Z. Todd; ...

2017-11-06

Numerical building models are typically forced with weather data from a limited number of “representative cities” or weather stations representing different climate regions. The use of representative weather stations reduces computational costs, but often fails to capture spatial heterogeneity in weather that may be important for simulations aimed at understanding how building stocks respond to a changing climate. Here, we quantify the potential reduction in temperature and load biases from using an increasing number of weather stations over the western U.S. Our novel approach is based on deriving temperature and load time series using incrementally more weather stations, ranging frommore » 8 to roughly 150, to evaluate the ability to capture weather patterns across different seasons. Using 8 stations across the western U.S., one from each IECC climate zone, results in an average absolute summertime temperature bias of ~4.0 °C with respect to a high-resolution gridded dataset. The mean absolute bias drops to ~1.5 °C using all available weather stations. Temperature biases of this magnitude could translate to absolute summertime mean simulated load biases as high as 13.5%. Increasing the size of the domain over which biases are calculated reduces their magnitude as positive and negative biases may cancel out. Using 8 representative weather stations can lead to a 20–40% bias of peak building loads during both summer and winter, a significant error for capacity expansion planners who may use these types of simulations. Using weather stations close to population centers reduces both mean and peak load biases. Our approach could be used by others designing aggregate building simulations to understand the sensitivity to their choice of weather stations used to drive the models.« less

Simulated building energy demand biases resulting from the use of representative weather stations

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

Burleyson, Casey D.; Voisin, Nathalie; Taylor, Z. Todd

Numerical building models are typically forced with weather data from a limited number of “representative cities” or weather stations representing different climate regions. The use of representative weather stations reduces computational costs, but often fails to capture spatial heterogeneity in weather that may be important for simulations aimed at understanding how building stocks respond to a changing climate. Here, we quantify the potential reduction in temperature and load biases from using an increasing number of weather stations over the western U.S. Our novel approach is based on deriving temperature and load time series using incrementally more weather stations, ranging frommore » 8 to roughly 150, to evaluate the ability to capture weather patterns across different seasons. Using 8 stations across the western U.S., one from each IECC climate zone, results in an average absolute summertime temperature bias of ~4.0 °C with respect to a high-resolution gridded dataset. The mean absolute bias drops to ~1.5 °C using all available weather stations. Temperature biases of this magnitude could translate to absolute summertime mean simulated load biases as high as 13.5%. Increasing the size of the domain over which biases are calculated reduces their magnitude as positive and negative biases may cancel out. Using 8 representative weather stations can lead to a 20–40% bias of peak building loads during both summer and winter, a significant error for capacity expansion planners who may use these types of simulations. Using weather stations close to population centers reduces both mean and peak load biases. Our approach could be used by others designing aggregate building simulations to understand the sensitivity to their choice of weather stations used to drive the models.« less

Predictive Modeling of Risk Associated with Temperature Extremes over Continental US

NASA Astrophysics Data System (ADS)

Kravtsov, S.; Roebber, P.; Brazauskas, V.

2016-12-01

We build an extremely statistically accurate, essentially bias-free empirical emulator of atmospheric surface temperature and apply it for meteorological risk assessment over the domain of continental US. The resulting prediction scheme achieves an order-of-magnitude or larger gain of numerical efficiency compared with the schemes based on high-resolution dynamical atmospheric models, leading to unprecedented accuracy of the estimated risk distributions. The empirical model construction methodology is based on our earlier work, but is further modified to account for the influence of large-scale, global climate change on regional US weather and climate. The resulting estimates of the time-dependent, spatially extended probability of temperature extremes over the simulation period can be used as a risk management tool by insurance companies and regulatory governmental agencies.

Excess junction current of silicon solar cells

NASA Technical Reports Server (NTRS)

Wang, E. Y.; Legge, R. N.; Christidis, N.

1973-01-01

The current-voltage characteristics of n(plus)-p silicon solar cells with 0.1, 1.0, 2.0, and 10 ohm-cm p-type base materials have been examined in detail. In addition to the usual I-V measurements, we have studied the temperature dependence of the slope of the I-V curve at the origin by the lock-in technique. The excess junction current coefficient (Iq) deduced from the slope at the origin depends on the square root of the intrinsic carrier concentration. The Iq obtained from the I-V curve fitting over the entire forward bias region at various temperatures shows the same temperature dependence. This result, in addition to the presence of an aging effect, suggest that the surface channel effect is the dominant cause of the excess junction current.

Design and validation of MEDRYS, a Mediterranean Sea reanalysis over the period 1992-2013

NASA Astrophysics Data System (ADS)

Hamon, Mathieu; Beuvier, Jonathan; Somot, Samuel; Lellouche, Jean-Michel; Greiner, Eric; Jordà, Gabriel; Bouin, Marie-Noëlle; Arsouze, Thomas; Béranger, Karine; Sevault, Florence; Dubois, Clotilde; Drevillon, Marie; Drillet, Yann

2016-04-01

The French research community in the Mediterranean Sea modeling and the French operational ocean forecasting center Mercator Océan have gathered their skill and expertise in physical oceanography, ocean modeling, atmospheric forcings and data assimilation to carry out a MEDiterranean sea ReanalYsiS (MEDRYS) at high resolution for the period 1992-2013. The ocean model used is NEMOMED12, a Mediterranean configuration of NEMO with a 1/12° ( ˜ 7 km) horizontal resolution and 75 vertical z levels with partial steps. At the surface, it is forced by a new atmospheric-forcing data set (ALDERA), coming from a dynamical downscaling of the ERA-Interim atmospheric reanalysis by the regional climate model ALADIN-Climate with a 12 km horizontal and 3 h temporal resolutions. This configuration is used to carry a 34-year hindcast simulation over the period 1979-2013 (NM12-FREE), which is the initial state of the reanalysis in October 1992. MEDRYS uses the existing Mercator Océan data assimilation system SAM2 that is based on a reduced-order Kalman filter with a three-dimensional (3-D) multivariate modal decomposition of the forecast error. Altimeter data, satellite sea surface temperature (SST) and temperature and salinity vertical profiles are jointly assimilated. This paper describes the configuration we used to perform MEDRYS. We then validate the skills of the data assimilation system. It is shown that the data assimilation restores a good average temperature and salinity at intermediate layers compared to the hindcast. No particular biases are identified in the bottom layers. However, the reanalysis shows slight positive biases of 0.02 psu and 0.15 °C above 150 m depth. In the validation stage, it is also shown that the assimilation allows one to better reproduce water, heat and salt transports through the Strait of Gibraltar. Finally, the ability of the reanalysis to represent the sea surface high-frequency variability is shown.

Dynamically biased statistical model for the ortho/para conversion in the H2 + H3+ → H3+ + H2 reaction.

PubMed

Gómez-Carrasco, Susana; González-Sánchez, Lola; Aguado, Alfredo; Sanz-Sanz, Cristina; Zanchet, Alexandre; Roncero, Octavio

2012-09-07

In this work we present a dynamically biased statistical model to describe the evolution of the title reaction from statistical to a more direct mechanism, using quasi-classical trajectories (QCT). The method is based on the one previously proposed by Park and Light [J. Chem. Phys. 126, 044305 (2007)]. A recent global potential energy surface is used here to calculate the capture probabilities, instead of the long-range ion-induced dipole interactions. The dynamical constraints are introduced by considering a scrambling matrix which depends on energy and determine the probability of the identity/hop/exchange mechanisms. These probabilities are calculated using QCT. It is found that the high zero-point energy of the fragments is transferred to the rest of the degrees of freedom, what shortens the lifetime of H(5)(+) complexes and, as a consequence, the exchange mechanism is produced with lower proportion. The zero-point energy (ZPE) is not properly described in quasi-classical trajectory calculations and an approximation is done in which the initial ZPE of the reactants is reduced in QCT calculations to obtain a new ZPE-biased scrambling matrix. This reduction of the ZPE is explained by the need of correcting the pure classical level number of the H(5)(+) complex, as done in classical simulations of unimolecular processes and to get equivalent quantum and classical rate constants using Rice-Ramsperger-Kassel-Marcus theory. This matrix allows to obtain a ratio of hop/exchange mechanisms, α(T), in rather good agreement with recent experimental results by Crabtree et al. [J. Chem. Phys. 134, 194311 (2011)] at room temperature. At lower temperatures, however, the present simulations predict too high ratios because the biased scrambling matrix is not statistical enough. This demonstrates the importance of applying quantum methods to simulate this reaction at the low temperatures of astrophysical interest.

Dynamically biased statistical model for the ortho/para conversion in the H2+H3+ --> H3++ H2 reaction

NASA Astrophysics Data System (ADS)

Gómez-Carrasco, Susana; González-Sánchez, Lola; Aguado, Alfredo; Sanz-Sanz, Cristina; Zanchet, Alexandre; Roncero, Octavio

2012-09-01

In this work we present a dynamically biased statistical model to describe the evolution of the title reaction from statistical to a more direct mechanism, using quasi-classical trajectories (QCT). The method is based on the one previously proposed by Park and Light [J. Chem. Phys. 126, 044305 (2007), 10.1063/1.2430711]. A recent global potential energy surface is used here to calculate the capture probabilities, instead of the long-range ion-induced dipole interactions. The dynamical constraints are introduced by considering a scrambling matrix which depends on energy and determine the probability of the identity/hop/exchange mechanisms. These probabilities are calculated using QCT. It is found that the high zero-point energy of the fragments is transferred to the rest of the degrees of freedom, what shortens the lifetime of H_5^+ complexes and, as a consequence, the exchange mechanism is produced with lower proportion. The zero-point energy (ZPE) is not properly described in quasi-classical trajectory calculations and an approximation is done in which the initial ZPE of the reactants is reduced in QCT calculations to obtain a new ZPE-biased scrambling matrix. This reduction of the ZPE is explained by the need of correcting the pure classical level number of the H_5^+ complex, as done in classical simulations of unimolecular processes and to get equivalent quantum and classical rate constants using Rice-Ramsperger-Kassel-Marcus theory. This matrix allows to obtain a ratio of hop/exchange mechanisms, α(T), in rather good agreement with recent experimental results by Crabtree et al. [J. Chem. Phys. 134, 194311 (2011), 10.1063/1.3587246] at room temperature. At lower temperatures, however, the present simulations predict too high ratios because the biased scrambling matrix is not statistical enough. This demonstrates the importance of applying quantum methods to simulate this reaction at the low temperatures of astrophysical interest.

Temperature and voltage dependence of barrier height and ideality factor in Au/0.07 graphene-doped PVA/n-Si structures

NASA Astrophysics Data System (ADS)

Altındal Yerişkin, S.; Balbaşı, M.; Demirezen, S.

2017-04-01

In this study, Au/0.07 graphene-doped PVA/n-Si structures were fabricated and current conduction mechanism in these structures were investigated in the temperature range of 80-380 K through forward bias current-voltage ( I- V) measurements. Main electrical parameters were extracted from I-V data. Zero-bias barrier height (\\overline{Φ}_{B0}) and ideality factor (n) were found strong functions of temperature and their values ranged from 0.234 eV and 4.98 (at 80 K) to 0.882 eV and 1.15 (at 380 K), respectively. Φ ap versus q/2k T plot was drawn to obtain an evidence of a Gaussian distribution of the barrier heights (BHs) and it revealed two distinct linear regions with different slopes and intercepts. The mean values of BH ( Φ Bo) and zero-bias standard deviation (σ s ) were obtained from the intercept and slope of the linear regions of this plot as 1.30 eV and 0.16 V for the first region (280-380 K) and 0.74 eV and 0.085 V for the second region (80-240 K), respectively. Thus, the values of \\overline{Φ}_{B0} and effective Richardson constant ( A*) were also found from the intercept and slope of the modified Richardson plot [ln( I s /T 2) - q 2 σ o 2 /2k 2 T 2 vs q/ kT] as 1.31 eV and 130 A/cm2 K2 for the first region and 0.76 eV and 922 A/cm2 K2 for the second region, respectively. The value of A* for the first region was very close to the theoretical value for n-Si (112 A/cm2 K2). The energy density distribution profile of surface states (Nss) was also extracted from the forward bias I-V data by taking into account voltage dependent effective BH (Φe) and n.

Response of the plasma to the size of an anode electrode biased near the plasma potential

DOE PAGES

Barnat, E. V.; Laity, G. R.; Baalrud, S. D.

2014-10-01

As the size of a positively biased electrode increases, the nature of the interface formed between the electrode and the host plasma undergoes a transition from an electron-rich structure (electron sheath) to an intermediate structure containing both ion and electron rich regions (double layer) and ultimately forms an electron-depleted structure (ion sheath). In this study, measurements are performed to further test how the size of an electron-collecting electrode impacts the plasma discharge the electrode is immersed in. This is accomplished using a segmented disk electrode in which individual segments are individually biased to change the effective surface area of themore » anode. Measurements of bulk plasma parameters such as the collected current density, plasma potential, electron density, electron temperature and optical emission are made as both the size and the bias placed on the electrode are varied. Abrupt transitions in the plasma parameters resulting from changing the electrode surface area are identified in both argon and helium discharges and are compared to the interface transitions predicted by global current balance [S. D. Baalrud, N. Hershkowitz, and B. Longmier, Phys. Plasmas 14, 042109 (2007)]. While the size-dependent transitions in argon agree, the size-dependent transitions observed in helium systematically occur at lower electrode sizes than those nominally derived from prediction. Thus, the discrepancy in helium is anticipated to be caused by the finite size of the interface that increases the effective area offered to the plasma for electron loss to the electrode.« less

Exacerbation of South Asian monsoon biases in GCMs using when using coupled ocean models

NASA Astrophysics Data System (ADS)

Turner, Andrew

2015-04-01

Cold biases during spring in the northern Arabian Sea of coupled ocean-atmosphere GCMs have previously been shown to limit monsoon rainfall over South Asia during the subsequent summer, by limiting the availability of moisture being advected. The cold biases develop following advection of cold dry air on anomalous northerly low level flow, suggestive of a too-strong winter monsoon in the coupled GCMs. As the same time, these cold biases and the anomalous advection have been related to larger scales by interaction with progression of the midlatitude westerly upper level flow. In this study we compare monsoon characteristics in 20th century historical and AMIP integrations of the CMIP5 multi-model database. We use a period of 1979-2005, common to both the AMIP and historical integrations. While all available observed boundary conditions, including sea-surface temperature (SST), are prescribed in the AMIP integrations, the historical integrations feature ocean-atmosphere models that generate SSTs via air-sea coupled processes. In AMIP experiments, the seasonal mean monsoon rainfall is shown to be systematically larger than in the coupled versions, with an earlier onset date also shown using a variety of circulation and precipitation metrics. In addition, examination of the springtime jet structure suggests that it sits too far south in the coupled models, leading to a delayed formation of the South Asia High over the Tibetan Plateau in summer. Further, we show that anomalous low entropy air is being advected near the surface from the north over the Arabian Sea in spring in the coupled models.

Interfacial layer thickness dependent electrical characteristics of Au/(Zn-doped PVA)/n-4H-SiC (MPS) structures at room temperature

NASA Astrophysics Data System (ADS)

Lapa, Havva Elif; Kökce, Ali; Al-Dharob, Mohammed; Orak, İkram; Özdemir, Ahmet Faruk; Altındal, Semsettin

2017-10-01

Au/(Zn-doped PVA)/n-4H-SiC metal/polymer/semiconductor (MPS) structures with different interfacial layer thickness values (50, 150, 500 nm) were fabricated and their electrical characteristics were compared. Their electrical parameters (i.e. reverse-bias saturation current (Io), ideality factor (n), zero-bias barrier height (BH) (Φbo), series and shunt resistances (Rs, Rsh)) were calculated from the forward bias current-voltage (IF-VF) data whereas other parameters (i.e. Fermi energy level (EF), BH (Vb) and donor concentration (Nd)) were calculated from the linear part of C-2-V characteristics at room temperature. Obtained results confirmed that the values of n, Φbo, Rs and Rsh increase with increasing interlayer thickness, and linear correlation between n and Φbo was observed. The high values of n for three structures can be ascribed to the presence of an interlayer, surface states (Nss) and barrier inhomogeneities. The energy density distribution profile of Nss was obtained from the IF-VF data by taking into account voltage-dependent effective BH (Ve) and n for each structure. The Ri vs V plot for these structures was obtained using both Ohm's law and Nicollian-Brews method. All these experimental results show that the interfacial layer and its thickness play an important role in main electric parameters of these structures.

Exploration, Sampling, And Reconstruction of Free Energy Surfaces with Gaussian Process Regression.

PubMed

Mones, Letif; Bernstein, Noam; Csányi, Gábor

2016-10-11

Practical free energy reconstruction algorithms involve three separate tasks: biasing, measuring some observable, and finally reconstructing the free energy surface from those measurements. In more than one dimension, adaptive schemes make it possible to explore only relatively low lying regions of the landscape by progressively building up the bias toward the negative of the free energy surface so that free energy barriers are eliminated. Most schemes use the final bias as their best estimate of the free energy surface. We show that large gains in computational efficiency, as measured by the reduction of time to solution, can be obtained by separating the bias used for dynamics from the final free energy reconstruction itself. We find that biasing with metadynamics, measuring a free energy gradient estimator, and reconstructing using Gaussian process regression can give an order of magnitude reduction in computational cost.

Biogenic isoprene emissions driven by regional weather predictions using different initialization methods: case studies during the SEAC4RS and DISCOVER-AQ airborne campaigns

NASA Astrophysics Data System (ADS)

Huang, Min; Carmichael, Gregory R.; Crawford, James H.; Wisthaler, Armin; Zhan, Xiwu; Hain, Christopher R.; Lee, Pius; Guenther, Alex B.

2017-08-01

Land and atmospheric initial conditions of the Weather Research and Forecasting (WRF) model are often interpolated from a different model output. We perform case studies during NASA's SEAC4RS and DISCOVER-AQ Houston airborne campaigns, demonstrating that using land initial conditions directly downscaled from a coarser resolution dataset led to significant positive biases in the coupled NASA-Unified WRF (NUWRF, version 7) surface and near-surface air temperature and planetary boundary layer height (PBLH) around the Missouri Ozarks and Houston, Texas, as well as poorly partitioned latent and sensible heat fluxes. Replacing land initial conditions with the output from a long-term offline Land Information System (LIS) simulation can effectively reduce the positive biases in NUWRF surface air temperature by ˜ 2 °C. We also show that the LIS land initialization can modify surface air temperature errors almost 10 times as effectively as applying a different atmospheric initialization method. The LIS-NUWRF-based isoprene emission calculations by the Model of Emissions of Gases and Aerosols from Nature (MEGAN, version 2.1) are at least 20 % lower than those computed using the coarser resolution data-initialized NUWRF run, and are closer to aircraft-observation-derived emissions. Higher resolution MEGAN calculations are prone to amplified discrepancies with aircraft-observation-derived emissions on small scales. This is possibly a result of some limitations of MEGAN's parameterization and uncertainty in its inputs on small scales, as well as the representation error and the neglect of horizontal transport in deriving emissions from aircraft data. This study emphasizes the importance of proper land initialization to the coupled atmospheric weather modeling and the follow-on emission modeling. We anticipate it to also be critical to accurately representing other processes included in air quality modeling and chemical data assimilation. Having more confidence in the weather inputs is also beneficial for determining and quantifying the other sources of uncertainties (e.g., parameterization, other input data) of the models that they drive.

Enhanced superconductivity at the interface of W/Sr2RuO4 point contact

NASA Astrophysics Data System (ADS)

Wei, Jian; Wang, He; Lou, Weijian; Luo, Jiawei; Liu, Ying; Ortmann, J. E.; Mao, Z. Q.

Differential resistance measurements are conducted for point contacts (PCs) between the Sr2RuO4 (SRO) single crystal and the tungsten tip. Since the tungsten tip is hard enough to penetrate through the surface layer, consistent superconducting features are observed. Firstly, with the tip pushed towards the crystal, the zero bias conductance peak (ZBCP) due to Andreev reflection at the normal-superconducting interface increases from 3% to more than 20%, much larger than previously reported, and extends to temperature higher than the bulk transition temperature. Reproducible ZBCP within 0.2 mV may also help determine the gap value of SRO, on which no consensus has been reached. Secondly, the logarithmic background can be fitted with the Altshuler-Aronov theory of electron-electron interaction for tunneling into quasi two dimensional electron system. Feasibility of such fitting confirms that spectroscopic information like density of states is probed, and electronic temperature retrieved from such fitting can be important to analyse the PC spectra. Third, at bias much higher than 0.2 mV there are conductance dips due to the critical current effect and these dips persist up to 6.2 K. For more details see. National Basic Research Program of China (973 Program) through Grant No. 2011CBA00106 and No. 2012CB927400.

Raman studied of undoped amorphous carbon thin film deposited by bias assisted-CVD

NASA Astrophysics Data System (ADS)

Ishak, A.; Fadzilah, A. N.; Dayana, K.; Saurdi, I.; Malek, M. F.; Nurbaya, Z.; Shafura, A. K.; Rusop, M.

2018-05-01

The undoped amorphous carbon thin film carbon was deposited at 200°C-350°C by bias assisted-CVD using palm oil as a precursor material. The effect of different substrate deposition temperatures on structural and electrical properties of undoped doped amorphous carbon film was discussed. The structural of undoped amorphous carbon films were correlated with Raman analysis through the evolution of D and G bands, Fourier spectra, and conductivity measurement. The spectral evolution observed showed the increase of upward shift of D and G peaks as substrate deposition temperatures increased. The spectral evolution observed at different substrate deposition temperatures show progressive formation of crystallites. It was predicted that small number of hydrogen is terminated with carbon at surface of thin film as shown by FTIR spectra since palm oil has high number of hydrogen (C67H127O8). These structural changes were further correlated with conductivity and the results obtained are discussed and compared. The conductivity is found in the range of 10-8 Scm-1. The increase of conductivity is correlated by the change of structural properties as correlated with characteristic parameters of Raman spectra including the position of G peak, full width at half maximum of G peak, and ID/IG and FTIR result.

The regional climate model REMO (v2015) coupled with the 1-D freshwater lake model FLake (v1): Fenno-Scandinavian climate and lakes

NASA Astrophysics Data System (ADS)

Pietikäinen, Joni-Pekka; Markkanen, Tiina; Sieck, Kevin; Jacob, Daniela; Korhonen, Johanna; Räisänen, Petri; Gao, Yao; Ahola, Jaakko; Korhonen, Hannele; Laaksonen, Ari; Kaurola, Jussi

2018-04-01

The regional climate model REMO was coupled with the FLake lake model to include an interactive treatment of lakes. Using this new version, the Fenno-Scandinavian climate and lake characteristics were studied in a set of 35-year hindcast simulations. Additionally, sensitivity tests related to the parameterization of snow albedo were conducted. Our results show that overall the new model version improves the representation of the Fenno-Scandinavian climate in terms of 2 m temperature and precipitation, but the downside is that an existing wintertime cold bias in the model is enhanced. The lake surface water temperature, ice depth and ice season length were analyzed in detail for 10 Finnish, 4 Swedish and 2 Russian lakes and 1 Estonian lake. The results show that the model can reproduce these characteristics with reasonably high accuracy. The cold bias during winter causes overestimation of ice layer thickness, for example, at several of the studied lakes, but overall the values from the model are realistic and represent the lake physics well in a long-term simulation. We also analyzed the snow depth on ice from 10 Finnish lakes and vertical temperature profiles from 5 Finnish lakes and the model results are realistic.

Thermoreflectance microscopy measurements of the Joule heating characteristics of high- Tc superconducting terahertz emitters

NASA Astrophysics Data System (ADS)

Kashiwagi, Takanari; Tanaka, Taiga; Watanabe, Chiharu; Kubo, Hiroyuki; Komori, Yuki; Yuasa, Takumi; Tanabe, Yuki; Ota, Ryusei; Kuwano, Genki; Nakamura, Kento; Tsujimoto, Manabu; Minami, Hidetoshi; Yamamoto, Takashi; Klemm, Richard A.; Kadowaki, Kazuo

2017-12-01

Joule heating is the central issue in order to develop high-power and high-performance terahertz (THz) emission from mesa devices employing the intrinsic Josephson junctions in a layered high transition-temperature Tc superconductor. Here, we describe a convenient local thermal measurement technique using charge-coupled-device-based thermoreflectance microscopy, with the highest spatial resolution to date. This technique clearly proves that the relative temperature changes of the mesa devices between different bias points on the current-voltage characteristics can be measured very sensitively. In addition, the heating characteristics on the surface of the mesa devices can be detected more directly without any special treatment of the mesa surface such as previous coatings with SiC micro-powders. The results shown here clearly indicate that the contact resistance strongly affects the formation of an inhomogeneous temperature distribution on the mesa structures. Since the temperature and sample dependencies of the Joule heating characteristics can be measured quickly, this simple thermal evaluation technique is a useful tool to check the quality of the electrical contacts, electrical wiring, and sample defects. Thus, this technique could help to reduce the heating problems and to improve the performance of superconducting THz emitter devices.

Nucleation and growth kinetics during metal-induced layer exchange crystallization of Ge thin films at low temperatures

NASA Astrophysics Data System (ADS)

Hu, Shu; McIntyre, Paul C.

2012-02-01

The kinetics of Al-catalyzed layer exchange crystallization of amorphous germanium (Ge) thin films at low temperatures is reported. Observation of Ge mass transport from an underlying amorphous Ge layer to the Al film surface through an interposed sub-nanometer GeOx interfacial layer allows independent measurement of the areal density and average area of crystalline Ge islands formed on the film surface. We show that bias-voltage stressing of the interfacial layer can be used to control the areal density of nucleated Ge islands. Based on experimental observations, the Johnson-Mehl-Avrami-Kolmogorov phase transformation theory is used to model nanoscale nucleation and growth of Ge islands in two dimensions. Ge island nucleation kinetics follows an exponentially decaying nucleation rate with time. Ge island growth kinetics switches from linear growth at a constant growth velocity to diffusion-limited growth as the growth front advances. The transition point between these two regimes depends on the Ge nucleation site density and the annealing temperature. Knowledge of the kinetics of low-temperature crystallization is important in achieving textured polycrystalline Ge thin films with large grains for applications in large-area electronics and solar energy conversion.

Methodology and results of calculating central California surface temperature trends: Evidence of human-induced climate change?

USGS Publications Warehouse

Christy, J.R.; Norris, W.B.; Redmond, K.; Gallo, K.P.

2006-01-01

A procedure is described to construct time series of regional surface temperatures and is then applied to interior central California stations to test the hypothesis that century-scale trend differences between irrigated and nonirrigated regions may be identified. The procedure requires documentation of every point in time at which a discontinuity in a station record may have occurred through (a) the examination of metadata forms (e.g., station moves) and (b) simple statistical tests. From this "homogeneous segments" of temperature records for each station are defined. Biases are determined for each segment relative to all others through a method employing mathematical graph theory. The debiased segments are then merged, forming a complete regional time series. Time series of daily maximum and minimum temperatures for stations in the irrigated San Joaquin Valley (Valley) and nearby nonirrigated Sierra Nevada (Sierra) were generated for 1910-2003. Results show that twentieth-century Valley minimum temperatures are warming at a highly significant rate in all seasons, being greatest in summer and fall (> +0.25??C decade-1). The Valley trend of annual mean temperatures is +0.07?? ?? 0.07??C decade-1. Sierra summer and fall minimum temperatures appear to be cooling, but at a less significant rate, while the trend of annual mean Sierra temperatures is an unremarkable -0.02?? ?? 0.10??C decade-1. A working hypothesis is that the relative positive trends in Valley minus Sierra minima (>0.4??C decade-1 for summer and fall) are related to the altered surface environment brought about by the growth of irrigated agriculture, essentially changing a high-albedo desert into a darker, moister, vegetated plain. ?? 2006 American Meteorological Society.

Gating of high-mobility InAs metamorphic heterostructures

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

Shabani, J.; McFadden, A. P.; Shojaei, B.

We investigate the performance of gate-defined devices fabricated on high mobility InAs metamorphic heterostructures. We find that heterostructures capped with In{sub 0.75}Ga{sub 0.25}As often show signs of parallel conduction due to proximity of their surface Fermi level to the conduction band minimum. Here, we introduce a technique that can be used to estimate the density of this surface charge that involves cool-downs from room temperature under gate bias. We have been able to remove the parallel conduction under high positive bias, but achieving full depletion has proven difficult. We find that by using In{sub 0.75}Al{sub 0.25}As as the barrier withoutmore » an In{sub 0.75}Ga{sub 0.25}As capping, a drastic reduction in parallel conduction can be achieved. Our studies show that this does not change the transport properties of the quantum well significantly. We achieved full depletion in InAlAs capped heterostructures with non-hysteretic gating response suitable for fabrication of gate-defined mesoscopic devices.« less

Biased four-point probe resistance

NASA Astrophysics Data System (ADS)

Garcia-Vazquez, Valentin

2017-11-01

The implications of switching the current polarity in a four-point probe resistance measurement are presented. We demonstrate that, during the inversion of the applied current, any change in the voltage V produced by a continuous drop of the sample temperature T will induce a bias in the temperature-dependent DC resistance. The analytical expression for the bias is deduced and written in terms of the variations of the measured voltages with respect to T and by the variations of T with respect to time t. Experimental data measured on a superconducting Nb thin film confirm that the bias of the normal-state resistance monotonically increases with the cooling rate dT/dt while keeping fixed dV/dT; on the other hand, the bias increases with dV/dT, reaching values up to 13% with respect to the unbiased resistance obtained at room temperature.

Temperature effects in contacts between a metal and a semiconductor nanowire near the degenerate doping

NASA Astrophysics Data System (ADS)

Sun, Zhuting; Burgess, Tim; Tan, H. H.; Jagadish, Chennupati; Kogan, Andrei

2018-04-01

We have investigated the nonlinear conductance in diffusion-doped Si:GaAs nanowires contacted by patterned metal films in a wide range of temperatures T. The wire resistance R W and the zero bias resistance R C, dominated by the contacts, exhibit very different responses to temperature changes. While R W shows almost no dependence on T, R C varies by several orders of magnitude as the devices are cooled from room temperature to T = 5 K. We develop a model that employs a sharp donor level very low in the GaAs conduction band and show that our observations are consistent with the model predictions. We then demonstrate that such measurements can be used to estimate carrier properties in nanostructured semiconductors and obtain an estimate for N D, the doping density in our samples. We also discuss the effects of surface states and dielectric confinement on carrier density in semiconductor nanowires.

Ensemble assimilation of ARGO temperature profile, sea surface temperature, and altimetric satellite data into an eddy permitting primitive equation model of the North Atlantic Ocean

NASA Astrophysics Data System (ADS)

Yan, Y.; Barth, A.; Beckers, J. M.; Candille, G.; Brankart, J. M.; Brasseur, P.

2015-07-01

Sea surface height, sea surface temperature, and temperature profiles at depth collected between January and December 2005 are assimilated into a realistic eddy permitting primitive equation model of the North Atlantic Ocean using the Ensemble Kalman Filter. Sixty ensemble members are generated by adding realistic noise to the forcing parameters related to the temperature. The ensemble is diagnosed and validated by comparison between the ensemble spread and the model/observation difference, as well as by rank histogram before the assimilation experiments. An incremental analysis update scheme is applied in order to reduce spurious oscillations due to the model state correction. The results of the assimilation are assessed according to both deterministic and probabilistic metrics with independent/semiindependent observations. For deterministic validation, the ensemble means, together with the ensemble spreads are compared to the observations, in order to diagnose the ensemble distribution properties in a deterministic way. For probabilistic validation, the continuous ranked probability score (CRPS) is used to evaluate the ensemble forecast system according to reliability and resolution. The reliability is further decomposed into bias and dispersion by the reduced centered random variable (RCRV) score in order to investigate the reliability properties of the ensemble forecast system. The improvement of the assimilation is demonstrated using these validation metrics. Finally, the deterministic validation and the probabilistic validation are analyzed jointly. The consistency and complementarity between both validations are highlighted.

Thermocouple Errors when Mounted on Cylindrical Surfaces in Abnormal Thermal Environments.

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

Nakos, James T.; Suo-Anttila, Jill M.; Zepper, Ethan T.

Mineral-insulated, metal-sheathed, Type-K thermocouples are used to measure the temperature of various items in high-temperature environments, often exceeding 1000degC (1273 K). The thermocouple wires (chromel and alumel) are protected from the harsh environments by an Inconel sheath and magnesium oxide (MgO) insulation. The sheath and insulation are required for reliable measurements. Due to the sheath and MgO insulation, the temperature registered by the thermocouple is not the temperature of the surface of interest. In some cases, the error incurred is large enough to be of concern because these data are used for model validation, and thus the uncertainties of themore » data need to be well documented. This report documents the error using 0.062" and 0.040" diameter Inconel sheathed, Type-K thermocouples mounted on cylindrical surfaces (inside of a shroud, outside and inside of a mock test unit). After an initial transient, the thermocouple bias errors typically range only about +-1-2% of the reading in K. After all of the uncertainty sources have been included, the total uncertainty to 95% confidence, for shroud or test unit TCs in abnormal thermal environments, is about +-2% of the reading in K, lower than the +-3% typically used for flat shrouds. Recommendations are provided in Section 6 to facilitate interpretation and use of the results. .« less

Multi-model assessment of the impact of soil moisture initialization on mid-latitude summer predictability

NASA Astrophysics Data System (ADS)

Ardilouze, Constantin; Batté, L.; Bunzel, F.; Decremer, D.; Déqué, M.; Doblas-Reyes, F. J.; Douville, H.; Fereday, D.; Guemas, V.; MacLachlan, C.; Müller, W.; Prodhomme, C.

2017-12-01

Land surface initial conditions have been recognized as a potential source of predictability in sub-seasonal to seasonal forecast systems, at least for near-surface air temperature prediction over the mid-latitude continents. Yet, few studies have systematically explored such an influence over a sufficient hindcast period and in a multi-model framework to produce a robust quantitative assessment. Here, a dedicated set of twin experiments has been carried out with boreal summer retrospective forecasts over the 1992-2010 period performed by five different global coupled ocean-atmosphere models. The impact of a realistic versus climatological soil moisture initialization is assessed in two regions with high potential previously identified as hotspots of land-atmosphere coupling, namely the North American Great Plains and South-Eastern Europe. Over the latter region, temperature predictions show a significant improvement, especially over the Balkans. Forecast systems better simulate the warmest summers if they follow pronounced dry initial anomalies. It is hypothesized that models manage to capture a positive feedback between high temperature and low soil moisture content prone to dominate over other processes during the warmest summers in this region. Over the Great Plains, however, improving the soil moisture initialization does not lead to any robust gain of forecast quality for near-surface temperature. It is suggested that models biases prevent the forecast systems from making the most of the improved initial conditions.

Developing a Data Record of Lower Troposphere Temperature Profiles for Diurnal Land-Atmosphere Coupling Investigations

NASA Astrophysics Data System (ADS)

Lin, Z.; Li, D.

2017-12-01

The lower troposphere, including the planetary boundary layer, is strongly influenced by the land surface at diurnal scales. However, investigations of diurnal land-atmosphere coupling are significantly hindered by the lack of profile measurements that resolve the diurnal cycle. This study aims to bridge this gap by developing a decade-long (from 2007 to 2016) data record of diurnal temperature profiles in the lower troposphere (from the surface to about 4 km above the surface), which is based on the Aircrafts Communications Addressing and Reporting System (ACARS) meteorological observations. We first identify the number of profiles within an hour for each airport over the CONUS. At each airport, only data that passed at least level-1 quality check are retained. 40 airports out of 275 are then selected, which have data for more than 12 hours per day. These selected airports are mainly located along the east and west coasts, as expected. Because the data are recorded at irregular heights, we resample each profile in the lowest 4 km or so to pre-defined vertical coordinates. These temperature profiles are further bias-corrected by comparing to collocated radiosonde observations. This consistent data record of diurnal temperature profiles in the lower troposphere can be also used for regional climatology research, short-term weather forecasts, and numerical model evaluation.

Investigating Surface Bias Errors in the Weather Research and Forecasting (WRF) Model using a Geographic Information System (GIS)

DTIC Science & Technology

2015-02-01

WRF ) Model using a Geographic Information System (GIS) by Jeffrey A Smith, Theresa A Foley, John W Raby, and Brian Reen...ARL-TR-7212 ● FEB 2015 US Army Research Laboratory Investigating Surface Bias Errors in the Weather Research and Forecasting ( WRF ) Model...SUBTITLE Investigating surface bias errors in the Weather Research and Forecasting ( WRF ) Model using a Geographic Information System (GIS) 5a

Statistical methods for change-point detection in surface temperature records

NASA Astrophysics Data System (ADS)

Pintar, A. L.; Possolo, A.; Zhang, N. F.

2013-09-01

We describe several statistical methods to detect possible change-points in a time series of values of surface temperature measured at a meteorological station, and to assess the statistical significance of such changes, taking into account the natural variability of the measured values, and the autocorrelations between them. These methods serve to determine whether the record may suffer from biases unrelated to the climate signal, hence whether there may be a need for adjustments as considered by M. J. Menne and C. N. Williams (2009) "Homogenization of Temperature Series via Pairwise Comparisons", Journal of Climate 22 (7), 1700-1717. We also review methods to characterize patterns of seasonality (seasonal decomposition using monthly medians or robust local regression), and explain the role they play in the imputation of missing values, and in enabling robust decompositions of the measured values into a seasonal component, a possible climate signal, and a station-specific remainder. The methods for change-point detection that we describe include statistical process control, wavelet multi-resolution analysis, adaptive weights smoothing, and a Bayesian procedure, all of which are applicable to single station records.

Cryogenic rf test of the first SRF cavity etched in an rf Ar/Cl2 plasma

NASA Astrophysics Data System (ADS)

Upadhyay, J.; Palczewski, A.; Popović, S.; Valente-Feliciano, A.-M.; Im, Do; Phillips, H. L.; Vušković, L.

2017-12-01

An apparatus and a method for etching of the inner surfaces of superconducting radio frequency (SRF) accelerator cavities are described. The apparatus is based on the reactive ion etching performed in an Ar/Cl2 cylindrical capacitive discharge with reversed asymmetry. To test the effect of the plasma etching on the cavity rf performance, a 1497 MHz single cell SRF cavity was used. The single cell cavity was mechanically polished and buffer chemically etched and then rf tested at cryogenic temperatures to provide a baseline characterization. The cavity's inner wall was then exposed to the capacitive discharge in a mixture of Argon and Chlorine. The inner wall acted as the grounded electrode, while kept at elevated temperature. The processing was accomplished by axially moving the dc-biased, corrugated inner electrode and the gas flow inlet in a step-wise manner to establish a sequence of longitudinally segmented discharges. The cavity was then tested in a standard vertical test stand at cryogenic temperatures. The rf tests and surface condition results, including the electron field emission elimination, are presented.

Different types of drifts in two seasonal forecast systems and their dependence on ENSO

NASA Astrophysics Data System (ADS)

Hermanson, L.; Ren, H.-L.; Vellinga, M.; Dunstone, N. D.; Hyder, P.; Ineson, S.; Scaife, A. A.; Smith, D. M.; Thompson, V.; Tian, B.; Williams, K. D.

2017-11-01

Seasonal forecasts using coupled ocean-atmosphere climate models are increasingly employed to provide regional climate predictions. For the quality of forecasts to improve, regional biases in climate models must be diagnosed and reduced. The evolution of biases as initialized forecasts drift away from the observations is poorly understood, making it difficult to diagnose the causes of climate model biases. This study uses two seasonal forecast systems to examine drifts in sea surface temperature (SST) and precipitation, and compares them to the long-term bias in the free-running version of each model. Drifts are considered from daily to multi-annual time scales. We define three types of drift according to their relation with the long-term bias in the free-running model: asymptoting, overshooting and inverse drift. We find that precipitation almost always has an asymptoting drift. SST drifts on the other hand, vary between forecasting systems, where one often overshoots and the other often has an inverse drift. We find that some drifts evolve too slowly to have an impact on seasonal forecasts, even though they are important for climate projections. The bias found over the first few days can be very different from that in the free-running model, so although daily weather predictions can sometimes provide useful information on the causes of climate biases, this is not always the case. We also find that the magnitude of equatorial SST drifts, both in the Pacific and other ocean basins, depends on the El Niño Southern Oscillation (ENSO) phase. Averaging over all hindcast years can therefore hide the details of ENSO state dependent drifts and obscure the underlying physical causes. Our results highlight the need to consider biases across a range of timescales in order to understand their causes and develop improved climate models.

Improving simulations of precipitation phase and snowpack at a site subject to cold air intrusions: Snoqualmie Pass, WA

NASA Astrophysics Data System (ADS)

Wayand, Nicholas E.; Stimberis, John; Zagrodnik, Joseph P.; Mass, Clifford F.; Lundquist, Jessica D.

2016-09-01

Low-level cold air from eastern Washington often flows westward through mountain passes in the Washington Cascades, creating localized inversions and locally reducing climatological temperatures. The persistence of this inversion during a frontal passage can result in complex patterns of snow and rain that are difficult to predict. Yet these predictions are critical to support highway avalanche control, ski resort operations, and modeling of headwater snowpack storage. In this study we used observations of precipitation phase from a disdrometer and snow depth sensors across Snoqualmie Pass, WA, to evaluate surface-air-temperature-based and mesoscale-model-based predictions of precipitation phase during the anomalously warm 2014-2015 winter. Correlations of phase between surface-based methods and observations were greatly improved (r2 from 0.45 to 0.66) and frozen precipitation biases reduced (+36% to -6% of accumulated snow water equivalent) by using air temperature from a nearby higher-elevation station, which was less impacted by low-level inversions. Alternatively, we found a hybrid method that combines surface-based predictions with output from the Weather Research and Forecasting mesoscale model to have improved skill (r2 = 0.61) over both parent models (r2 = 0.42 and 0.55). These results suggest that prediction of precipitation phase in mountain passes can be improved by incorporating observations or models from above the surface layer.

Evaluation of CMIP5 Ability to Reproduce 20th Century Regional Trends in Surface Air Temperature and Precipitation over CONUS

NASA Astrophysics Data System (ADS)

Lee, J.; Waliser, D. E.; Lee, H.; Loikith, P. C.; Kunkel, K.

2017-12-01

Monitoring temporal changes in key climate variables, such as surface air temperature and precipitation, is an integral part of the ongoing efforts of the United States National Climate Assessment (NCA). Climate models participating in CMIP5 provide future trends for four different emissions scenarios. In order to have confidence in the future projections of surface air temperature and precipitation, it is crucial to evaluate the ability of CMIP5 models to reproduce observed trends for three different time periods (1895-1939, 1940-1979, and 1980-2005). Towards this goal, trends in surface air temperature and precipitation obtained from the NOAA nClimGrid 5 km gridded station observation-based product are compared during all three time periods to the 206 CMIP5 historical simulations from 48 unique GCMs and their multi-model ensemble (MME) for NCA-defined climate regions during summer (JJA) and winter (DJF). This evaluation quantitatively examines the biases of simulated trends of the spatially averaged temperature and precipitation in the NCA climate regions. The CMIP5 MME reproduces historical surface air temperature trends for JJA for all time period and all regions, except the Northern Great Plains from 1895-1939 and Southeast during 1980-2005. Likewise, for DJF, the MME reproduces historical surface air temperature trends across all time periods over all regions except the Southeast from 1895-1939 and the Midwest during 1940-1979. The Regional Climate Model Evaluation System (RCMES), an analysis tool which supports the NCA by providing access to data and tools for regional climate model validation, facilitates the comparisons between the models and observation. The RCMES Toolkit is designed to assist in the analysis of climate variables and the procedure of the evaluation of climate projection models to support the decision-making processes. This tool is used in conjunction with the above analysis and results will be presented to demonstrate its capability to access observation and model datasets, calculate evaluation metrics, and visualize the results. Several other examples of the RCMES capabilities can be found at https://rcmes.jpl.nasa.gov.

Seal assembly

DOEpatents

Johnson, Roger Neal; Longfritz, William David

2001-01-01

A seal assembly that seals a gap formed by a groove comprises a seal body, a biasing element, and a connection that connects the seal body to the biasing element to form the seal assembly. The seal assembly further comprises a concave-shaped center section and convex-shaped contact portions at each end of the seal body. The biasing element is formed from an elastic material and comprises a convex-shaped center section and concave-shaped biasing zones that are opposed to the convex-shaped contact portions. The biasing element is adapted to be compressed to change a width of the seal assembly from a first width to a second width that is smaller than the first width. In the compressed state, the seal assembly can be disposed in the groove. After release of the compressing force, the seal assembly expands. The contact portions will move toward a surface of the groove and the biasing zones will move into contact with another surface of the groove. The biasing zones will bias the contact portions of the seal body against the surface of the groove.

Conventional and novel body temperature measurement during rest and exercise induced hyperthermia.

PubMed

Towey, Colin; Easton, Chris; Simpson, Robert; Pedlar, Charles

2017-01-01

Despite technological advances in thermal sensory equipment, few core temperature (T CORE ) measurement techniques have met the established validity criteria in exercise science. Additionally, there is debate as to what method serves as the most practically viable, yet upholds the proposed measurement accuracy. This study assessed the accuracy of current and novel T CORE measurement techniques in comparison to rectal temperature (T REC ) as a reference standard. Fifteen well-trained subjects (11 male, 4 female) completed 60min of exercise at an intensity equating to the lactate threshold; measured via a discontinuous exercise test. T REC was significantly elevated from resting values (37.2±0.3°C) at the end of moderate intensity exercise (39.6±0.04°C; P=0.001). Intestinal telemetric pill (T PILL ) temperature and temporal artery temperature (T TEM ) did not differ significantly from T REC at rest or during exercise (P>0.05). However, aural canal temperature (T AUR ) and thermal imaging temperature (T IMA ) were both significantly lower than T REC (P<0.05). Bland Altman analysis revealed only T PILL was within acceptable limits of agreement (mean bias; 0.04°C), while T TEM , T AUR and T IMA demonstrated mean bias values outside of the acceptable range (>0.27°C). Against T REC , these results support the use of T PILL over all other techniques as a valid measure of T CORE at rest and during exercise induced hyperthermia. Novel findings illustrate that T IMA (when measured at the inner eye canthus) shows poor agreement to T REC during rest and exercise, which is similar to other 'surface' measures. Crown Copyright © 2016. Published by Elsevier Ltd. All rights reserved.

Are Sea Surface Temperature satellite measurements reliable proxies of lagoon temperature in the South Pacific?

NASA Astrophysics Data System (ADS)

Van Wynsberge, Simon; Menkes, Christophe; Le Gendre, Romain; Passfield, Teuru; Andréfouët, Serge

2017-12-01

In remote coral reef environments, lagoon and reef in situ measurements of temperature are scarce. Sea Surface Temperature (SST) measured by satellite has been frequently used as a proxy of the lagoon temperature experienced by coral reef organisms (TL) especially during coral bleaching events. However, the link between SST and TL is poorly characterized. First, we compared the correlation between various SST series and TL from 2012 to 2016 in three atolls and one island in the Central South Pacific Ocean. Simple linear correlation between SST and TL ranged between 0.44 and 0.97 depending on lagoons, localities of sensors, and type of SST data. High-resolution-satellite-measurements of SST inside the lagoons did not outperform oceanic SST series, suggesting that SST products are not adapted for small lagoons. Second, we modelled the difference between oceanic SST and TL as a function of the drivers of lagoon water renewal and mixing, namely waves, tide, wind, and season. The multivariate models reduced significantly the bias between oceanic SST and TL. In atoll lagoons, and probably in other hydrodynamically semi-open systems, a correction taking into account these factors is necessary when SST are used to characterize organisms' thermal stress thresholds.

Reducing the Impact of Sampling Bias in NASA MODIS and VIIRS Level 3 Satellite Derived IR SST Observations over the Arctic

NASA Astrophysics Data System (ADS)

Minnett, P. J.; Liu, Y.; Kilpatrick, K. A.

2016-12-01

Sea-surface temperature (SST) measurements by satellites in the northern hemisphere high latitudes confront several difficulties. Year-round prevalent clouds, effects near ice edges, and the relative small difference between SST and low-level cloud temperatures lead to a significant loss of infrared observations regardless of the more frequent polar satellite overpasses. Recent research (Liu and Minnett, 2016) identified sampling issues in the Level 3 NASA MODIS SST products when 4km observations are aggregated into global grids at different time and space scales, particularly in the Arctic, where a binary decision cloud mask designed for global data is often overly conservative at high latitudes and results in many gaps and missing data. This under sampling of some Arctic regions results in a warm bias in Level 3 products, likely a result of warmer surface temperature, more distant from the ice edge, being identified more frequently as cloud free. Here we present an improved method for cloud detection in the Arctic using a majority vote from an ensemble of four classifiers trained based on an Alternative Decision Tree (ADT) algorithm (Freund and Mason 1999, Pfahringer et. al. 2001). This new cloud classifier increases sampling of clear pixel by 50% in several regions and generally produces cooler monthly average SST fields in the ice-free Arctic, while still retaining the same error characteristics at 1km resolution relative to in situ observations. SST time series of 12 years of MODIS (Aqua and Terra) and more recently VIIRS sensors are compared and the improvements in errors and uncertainties resulting from better cloud screening for Level 3 gridded products are assessed and summarized.

Improving past sea surface temperature reconstructions from the Southern Hemisphere oceans using planktonic foraminiferal census data

NASA Astrophysics Data System (ADS)

Haddam, N. A.; Michel, E.; Siani, G.; Cortese, G.; Bostock, H. C.; Duprat, J. M.; Isguder, G.

2016-06-01

We present an improved database of planktonic foraminiferal census counts from the Southern Hemisphere oceans (SHO) from 15°S to 64°S. The SHO database combines three existing databases. Using this SHO database, we investigated dissolution biases that might affect faunal census counts. We suggest a depth/ΔCO32- threshold of ~3800 m/ΔCO32- = ~ -10 to -5 µmol/kg for the Pacific and Indian Oceans and ~4000 m/ΔCO32- = ~0 to 10 µmol/kg for the Atlantic Ocean, under which core-top assemblages can be affected by dissolution and are less reliable for paleo-sea surface temperature (SST) reconstructions. We removed all core tops beyond these thresholds from the SHO database. This database has 598 core tops and is able to reconstruct past SST variations from 2° to 25.5°C, with a root mean square error of 1.00°C, for annual temperatures. To inspect how dissolution affects SST reconstruction quality, we tested the data base with two "leave-one-out" tests, with and without the deep core tops. We used this database to reconstruct summer SST (SSST) over the last 20 ka, using the Modern Analog Technique method, on the Southeast Pacific core MD07-3100. This was compared to the SSST reconstructed using the three databases used to compile the SHO database, thus showing that the reconstruction using the SHO database is more reliable, as its dissimilarity values are the lowest. The most important aspect here is the importance of a bias-free, geographic-rich database. We leave this data set open-ended to future additions; the new core tops must be carefully selected, with their chronological frameworks, and evidence of dissolution assessed.

A 20 year independent record of sea surface temperature for climate from Along-Track Scanning Radiometers

NASA Astrophysics Data System (ADS)

Merchant, Christopher J.; Embury, Owen; Rayner, Nick A.; Berry, David I.; Corlett, Gary K.; Lean, Katie; Veal, Karen L.; Kent, Elizabeth C.; Llewellyn-Jones, David T.; Remedios, John J.; Saunders, Roger

2012-12-01

A new record of sea surface temperature (SST) for climate applications is described. This record provides independent corroboration of global variations estimated from SST measurements made in situ. Infrared imagery from Along-Track Scanning Radiometers (ATSRs) is used to create a 20 year time series of SST at 0.1° latitude-longitude resolution, in the ATSR Reprocessing for Climate (ARC) project. A very high degree of independence of in situ measurements is achieved via physics-based techniques. Skin SST and SST estimated for 20 cm depth are provided, with grid cell uncertainty estimates. Comparison with in situ data sets establishes that ARC SSTs generally have bias of order 0.1 K or smaller. The precision of the ARC SSTs is 0.14 K during 2003 to 2009, from three-way error analysis. Over the period 1994 to 2010, ARC SSTs are stable, with better than 95% confidence, to within 0.005 K yr-1(demonstrated for tropical regions). The data set appears useful for cleanly quantifying interannual variability in SST and major SST anomalies. The ARC SST global anomaly time series is compared to the in situ-based Hadley Centre SST data set version 3 (HadSST3). Within known uncertainties in bias adjustments applied to in situ measurements, the independent ARC record and HadSST3 present the same variations in global marine temperature since 1996. Since the in situ observing system evolved significantly in its mix of measurement platforms and techniques over this period, ARC SSTs provide an important corroboration that HadSST3 accurately represents recent variability and change in this essential climate variable.

Sampling Soil CO2 for Isotopic Flux Partitioning: Non Steady State Effects and Methodological Biases

NASA Astrophysics Data System (ADS)

Snell, H. S. K.; Robinson, D.; Midwood, A. J.

2014-12-01

Measurements of δ13C of soil CO2 are used to partition the surface flux into autotrophic and heterotrophic components. Models predict that the δ13CO2 of the soil efflux is perturbed by non-steady state (NSS) diffusive conditions. These could be large enough to render δ13CO2 unsuitable for accurate flux partitioning. Field studies sometimes find correlations between efflux δ13CO2 and flux or temperature, or that efflux δ13CO2 is not correlated as expected with biological drivers. We tested whether NSS effects in semi-natural soil were comparable with those predicted. We compared chamber designs and their sensitivity to changes in efflux δ13CO2. In a natural soil mesocosm, we controlled temperature to generate NSS conditions of CO2 production. We measured the δ13C of soil CO2 using in situ probes to sample the subsurface, and dynamic and forced-diffusion chambers to sample the surface efflux. Over eight hours we raised soil temperature by 4.5 OC to increase microbial respiration. Subsurface CO2 concentration doubled, surface efflux became 13C-depleted by 1 ‰ and subsurface CO2 became 13C-enriched by around 2 ‰. Opposite changes occurred when temperature was lowered and CO2 production was decreasing. Different chamber designs had inherent biases but all detected similar changes in efflux δ13CO2, which were comparable to those predicted. Measurements using dynamic chambers were more 13C-enriched than expected, probably due to advection of CO2 into the chamber. In the mesocosm soil, δ13CO2 of both efflux and subsurface was determined by physical processes of CO2 production and diffusion. Steady state conditions are unlikely to prevail in the field, so spot measurements of δ13CO2 and assumptions based on the theoretical 4.4 ‰ diffusive fractionation will not be accurate for estimating source δ13CO2. Continuous measurements could be integrated over a period suitable to reduce the influence of transient NSS conditions. It will be difficult to disentangle biologically driven changes in soil δ13CO2 from physical controls, particularly as they occur on similar timescales and are driven by the same environmental variables, such as temperature, moisture and daylight.

Using Data Assimilation Diagnostics to Assess the SMAP Level-4 Soil Moisture Product

NASA Technical Reports Server (NTRS)

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

2018-01-01

The Soil Moisture Active Passive (SMAP) mission 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 and related land surface variables from 31 March 2015 to present with approx.2.5-day latency. The ensemble-based L4_SM algorithm assimilates SMAP brightness temperature (Tb) observations into the Catchment land surface model. This study describes the spatially distributed L4_SM analysis and assesses the observation-minus-forecast (O-F) Tb residuals and the soil moisture and temperature analysis increments. Owing to the climatological rescaling of the Tb observations prior to assimilation, the analysis is essentially unbiased, with global mean values of approx. 0.37 K for the O-F Tb residuals and practically zero for the soil moisture and temperature increments. There are, however, modest regional (absolute) biases in the O-F residuals (under approx. 3 K), the soil moisture increments (under approx. 0.01 cu m/cu m), and the surface soil temperature increments (under approx. 1 K). Typical instantaneous values are approx. 6 K for O-F residuals, approx. 0.01 (approx. 0.003) cu m/cu m for surface (root-zone) soil moisture increments, and approx. 0.6 K for surface soil temperature increments. The O-F diagnostics indicate that the actual errors in the system are overestimated in deserts and densely vegetated regions and underestimated in agricultural regions and transition zones between dry and wet climates. The O-F auto-correlations suggest that the SMAP observations are used efficiently in western North America, the Sahel, and Australia, but not in many forested regions and the high northern latitudes. A case study in Australia demonstrates that assimilating SMAP observations successfully corrects short-term errors in the L4_SM rainfall forcing.

Global Assessment of the SMAP Level-4 Soil Moisture Product Using Assimilation Diagnostics

NASA Technical Reports Server (NTRS)

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

2018-01-01

The Soil Moisture Active Passive (SMAP) mission 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 and related land surface variables from 31 March 2015 to present with approx. 2.5-day latency. The ensemble-based L4_SM algorithm assimilates SMAP brightness temperature (Tb) observations into the Catchment land surface model. This study describes the spatially distributed L4_SM analysis and assesses the observation-minus-forecast (O-F) Tb residuals and the soil moisture and temperature analysis increments. Owing to the climatological rescaling of the Tb observations prior to assimilation, the analysis is essentially unbiased, with global mean values of approx. 0.37 K for the O-F Tb residuals and practically zero for the soil moisture and temperature increments. There are, however, modest regional (absolute) biases in the O-F residuals (under approx. 3 K), the soil moisture increments (under approx. 0.01 cu m/cu m), and the surface soil temperature increments (under approx. 1 K). Typical instantaneous values are approx. 6 K for O-F residuals, approx. 0.01 (approx. 0.003) cu m/cu m for surface (root-zone) soil moisture increments, and approx. 0.6 K for surface soil temperature increments. The O-F diagnostics indicate that the actual errors in the system are overestimated in deserts and densely vegetated regions and underestimated in agricultural regions and transition zones between dry and wet climates. The O-F auto-correlations suggest that the SMAP observations are used efficiently in western North America, the Sahel, and Australia, but not in many forested regions and the high northern latitudes. A case study in Australia demonstrates that assimilating SMAP observations successfully corrects short-term errors in the L4_SM rainfall forcing.

bcROCsurface: an R package for correcting verification bias in estimation of the ROC surface and its volume for continuous diagnostic tests.

PubMed

To Duc, Khanh

2017-11-18

Receiver operating characteristic (ROC) surface analysis is usually employed to assess the accuracy of a medical diagnostic test when there are three ordered disease status (e.g. non-diseased, intermediate, diseased). In practice, verification bias can occur due to missingness of the true disease status and can lead to a distorted conclusion on diagnostic accuracy. In such situations, bias-corrected inference tools are required. This paper introduce an R package, named bcROCsurface, which provides utility functions for verification bias-corrected ROC surface analysis. The shiny web application of the correction for verification bias in estimation of the ROC surface analysis is also developed. bcROCsurface may become an important tool for the statistical evaluation of three-class diagnostic markers in presence of verification bias. The R package, readme and example data are available on CRAN. The web interface enables users less familiar with R to evaluate the accuracy of diagnostic tests, and can be found at http://khanhtoduc.shinyapps.io/bcROCsurface_shiny/ .

Temperature dependence of electroresistance for La0.67Ba0.33MnO3 manganite

NASA Astrophysics Data System (ADS)

Kumar, Rajesh; Gupta, Ajai K.; Kumar, Vijay; Bhalla, G. L.; Khare, Neeraj

2007-12-01

The influence of dc biasing current on temperature dependence of resistance of La0.67Ba0.33MnO3 bulk sample is reported. A decrease in the resistance (electroresistance) on the application of higher bias current is observed. The electroresistance is maximum at metal insulator transition temperature (TMI) and decreases when the temperature is either increased or decreased from TMI. A two-phase model is proposed to explain the occurrence of electroresistance. The higher bias current leads to an increase in alignment of spins and thus, in turn, leads to an increase in spin stiffness coefficient and decrease in the resistance at TMI.

Molecules for organic electronics studied one by one.

PubMed

Meyer, Jörg; Wadewitz, Anja; Lokamani; Toher, Cormac; Gresser, Roland; Leo, Karl; Riede, Moritz; Moresco, Francesca; Cuniberti, Gianaurelio

2011-08-28

The electronic and geometrical structure of single difluoro-bora-1,3,5,7-tetraphenyl-aza-dipyrromethene (aza-BODIPY) molecules adsorbed on the Au(111) surface is investigated by low temperature scanning tunneling microscopy and spectroscopy in conjunction with ab initio density functional theory simulations of the density of states and of the interaction with the substrate. Our DFT calculations indicate that the aza-bodipy molecule forms a chemical bond with the Au(111) substrate, with distortion of the molecular geometry and significant charge transfer between the molecule and the substrate. Nevertheless, most likely due to the low corrugation of the Au(111) surface, diffusion of the molecule is observed for applied bias in excess of 1 V.

Evaluation of urban surface parameterizations in the WRF model using measurements during the Texas Air Quality Study 2006 field campaign

NASA Astrophysics Data System (ADS)

Lee, S.-H.; Kim, S.-W.; Angevine, W. M.; Bianco, L.; McKeen, S. A.; Senff, C. J.; Trainer, M.; Tucker, S. C.; Zamora, R. J.

2010-10-01

The impact of urban surface parameterizations in the WRF (Weather Research and Forecasting) model on the simulation of local meteorological fields is investigated. The Noah land surface model (LSM), a modified LSM, and a single-layer urban canopy model (UCM) have been compared, focusing on urban patches. The model simulations were performed for 6 days from 12 August to 17 August during the Texas Air Quality Study 2006 field campaign. Analysis was focused on the Houston-Galveston metropolitan area. The model simulated temperature, wind, and atmospheric boundary layer (ABL) height were compared with observations from surface meteorological stations (Continuous Ambient Monitoring Stations, CAMS), wind profilers, the NOAA Twin Otter aircraft, and the NOAA Research Vessel Ronald H. Brown. The UCM simulation showed better results in the comparison of ABL height and surface temperature than the LSM simulations, whereas the original LSM overestimated both the surface temperature and ABL height significantly in urban areas. The modified LSM, which activates hydrological processes associated with urban vegetation mainly through transpiration, slightly reduced warm and high biases in surface temperature and ABL height. A comparison of surface energy balance fluxes in an urban area indicated the UCM reproduces a realistic partitioning of sensible heat and latent heat fluxes, consequently improving the simulation of urban boundary layer. However, the LSMs have a higher Bowen ratio than the observation due to significant suppression of latent heat flux. The comparison results suggest that the subgrid heterogeneity by urban vegetation and urban morphological characteristics should be taken into account along with the associated physical parameterizations for accurate simulation of urban boundary layer if the region of interest has a large fraction of vegetation within the urban patch. Model showed significant discrepancies in the specific meteorological conditions when nocturnal low-level jets exist and a thermal internal boundary layer over water forms.

Impacts of Model Bias on the Climate Change Signal and Effects of Weighted Ensembles of Regional Climate Model Simulations: A Case Study over Southern Québec, Canada

DOE PAGES

Eum, Hyung-Il; Gachon, Philippe; Laprise, René

2016-01-01

This study examined the impact of model biases on climate change signals for daily precipitation and for minimum and maximum temperatures. Through the use of multiple climate scenarios from 12 regional climate model simulations, the ensemble mean, and three synthetic simulations generated by a weighting procedure, we investigated intermodel seasonal climate change signals between current and future periods, for both median and extreme precipitation/temperature values. A significant dependence of seasonal climate change signals on the model biases over southern Québec in Canada was detected for temperatures, but not for precipitation. This suggests that the regional temperature change signal is affectedmore » by local processes. Seasonally, model bias affects future mean and extreme values in winter and summer. In addition, potentially large increases in future extremes of temperature and precipitation values were projected. For three synthetic scenarios, systematically less bias and a narrow range of mean change for all variables were projected compared to those of climate model simulations. In addition, synthetic scenarios were found to better capture the spatial variability of extreme cold temperatures than the ensemble mean scenario. Finally, these results indicate that the synthetic scenarios have greater potential to reduce the uncertainty of future climate projections and capture the spatial variability of extreme climate events.« less

Impacts of Model Bias on the Climate Change Signal and Effects of Weighted Ensembles of Regional Climate Model Simulations: A Case Study over Southern Québec, Canada

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

Eum, Hyung-Il; Gachon, Philippe; Laprise, René

This study examined the impact of model biases on climate change signals for daily precipitation and for minimum and maximum temperatures. Through the use of multiple climate scenarios from 12 regional climate model simulations, the ensemble mean, and three synthetic simulations generated by a weighting procedure, we investigated intermodel seasonal climate change signals between current and future periods, for both median and extreme precipitation/temperature values. A significant dependence of seasonal climate change signals on the model biases over southern Québec in Canada was detected for temperatures, but not for precipitation. This suggests that the regional temperature change signal is affectedmore » by local processes. Seasonally, model bias affects future mean and extreme values in winter and summer. In addition, potentially large increases in future extremes of temperature and precipitation values were projected. For three synthetic scenarios, systematically less bias and a narrow range of mean change for all variables were projected compared to those of climate model simulations. In addition, synthetic scenarios were found to better capture the spatial variability of extreme cold temperatures than the ensemble mean scenario. Finally, these results indicate that the synthetic scenarios have greater potential to reduce the uncertainty of future climate projections and capture the spatial variability of extreme climate events.« less

Accuracy and precision of polar lower stratospheric temperatures from reanalyses evaluated from A-Train CALIOP and MLS, COSMIC GPS RO, and the equilibrium thermodynamics of supercooled ternary solutions and ice clouds

NASA Astrophysics Data System (ADS)

Lambert, Alyn; Santee, Michelle L.

2018-02-01

We investigate the accuracy and precision of polar lower stratospheric temperatures (100-10 hPa during 2008-2013) reported in several contemporary reanalysis datasets comprising two versions of the Modern-Era Retrospective analysis for Research and Applications (MERRA and MERRA-2), the Japanese 55-year Reanalysis (JRA-55), the European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA-I), and the National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis (NCEP-CFSR). We also include the Goddard Earth Observing System model version 5.9.1 near-real-time analysis (GEOS-5.9.1). Comparisons of these datasets are made with respect to retrieved temperatures from the Aura Microwave Limb Sounder (MLS), Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) Global Positioning System (GPS) radio occultation (RO) temperatures, and independent absolute temperature references defined by the equilibrium thermodynamics of supercooled ternary solutions (STSs) and ice clouds. Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) observations of polar stratospheric clouds are used to determine the cloud particle types within the Aura MLS geometric field of view. The thermodynamic calculations for STS and the ice frost point use the colocated MLS gas-phase measurements of HNO3 and H2O. The estimated bias and precision for the STS temperature reference, over the 68 to 21 hPa pressure range, are 0.6-1.5 and 0.3-0.6 K, respectively; for the ice temperature reference, they are 0.4 and 0.3 K, respectively. These uncertainties are smaller than those estimated for the retrieved MLS temperatures and also comparable to GPS RO uncertainties (bias < 0.2 K, precision > 0.7 K) in the same pressure range. We examine a case study of the time-varying temperature structure associated with layered ice clouds formed by orographic gravity waves forced by flow over the Palmer Peninsula and compare how the wave amplitudes are reproduced by each reanalysis dataset. We find that the spatial and temporal distribution of temperatures below the ice frost point, and hence the potential to form ice polar stratospheric clouds (PSCs) in model studies driven by the reanalyses, varies significantly because of the underlying differences in the representation of mountain wave activity. High-accuracy COSMIC temperatures are used as a common reference to intercompare the reanalysis temperatures. Over the 68-21 hPa pressure range, the biases of the reanalyses with respect to COSMIC temperatures for both polar regions fall within the narrow range of -0.6 K to +0.5 K. GEOS-5.9.1, MERRA, MERRA-2, and JRA-55 have predominantly cold biases, whereas ERA-I has a predominantly warm bias. NCEP-CFSR has a warm bias in the Arctic but becomes substantially colder in the Antarctic. Reanalysis temperatures are also compared with the PSC reference temperatures. Over the 68-21 hPa pressure range, the reanalysis temperature biases are in the range -1.6 to -0.3 K with standard deviations ˜ 0.6 K for the CALIOP STS reference, and in the range -0.9 to +0.1 K with standard deviations ˜ 0.7 K for the CALIOP ice reference. Comparisons of MLS temperatures with the PSC reference temperatures reveal vertical oscillations in the MLS temperatures and a significant low bias in MLS temperatures of up to 3 K.

Mesoscale Simulations of a Florida Sea Breeze Using the PLACE Land Surface Model Coupled to a 1.5-Order Turbulence Parameterization

NASA Technical Reports Server (NTRS)

Lynn, Barry H.; Stauffer, David R.; Wetzel, Peter J.; Tao, Wei-Kuo; Perlin, Natal; Baker, R. David; Munoz, Ricardo; Boone, Aaron; Jia, Yiqin

1999-01-01

A sophisticated land-surface model, PLACE, the Parameterization for Land Atmospheric Convective Exchange, has been coupled to a 1.5-order turbulent kinetic energy (TKE) turbulence sub-model. Both have been incorporated into the Penn State/National Center for Atmospheric Research (PSU/NCAR) mesoscale model MM5. Such model improvements should have their greatest effect in conditions where surface contrasts dominate over dynamic processes, such as the simulation of warm-season, convective events. A validation study used the newly coupled model, MM5 TKE-PLACE, to simulate the evolution of Florida sea-breeze moist convection during the Convection and Precipitation Electrification Experiment (CaPE). Overall, eight simulations tested the sensitivity of the MM5 model to combinations of the new and default model physics, and initialization of soil moisture and temperature. The TKE-PLACE model produced more realistic surface sensible heat flux, lower biases for surface variables, more realistic rainfall, and cloud cover than the default model. Of the 8 simulations with different factors (i.e., model physics or initialization), TKE-PLACE compared very well when each simulation was ranked in terms of biases of the surface variables and rainfall, and percent and root mean square of cloud cover. A factor separation analysis showed that a successful simulation required the inclusion of a multi-layered, land surface soil vegetation model, realistic initial soil moisture, and higher order closure of the planetary boundary layer (PBL). These were needed to realistically model the effect of individual, joint, and synergistic contributions from the land surface and PBL on the CAPE sea-breeze, Lake Okeechobee lake breeze, and moist convection.