Comparisons of observational data sets for evaluating the CMIP5 precipitation extreme simulations over Asia

S Dong; Y Sun

doi:10.3354/cr01534

Consistency of nonlinear interacting ghost dark energy with recent observations

International Journal of Modern Physics D ◽

10.1142/s0218271817501243 ◽

2017 ◽

Vol 26 (11) ◽

pp. 1750124 ◽

Cited By ~ 4

Author(s):

E. Ebrahimi ◽

H. Golchin ◽

A. Mehrabi ◽

S. M. S. Movahed

Keyword(s):

Dark Energy ◽

Observational Data ◽

Nonlinear Interaction ◽

Acoustic Oscillation ◽

Joint Analysis ◽

Data Sets ◽

Dark Energy Density ◽

Ghost Dark Energy ◽

Interaction Terms ◽

Best Fit

In this paper, we investigate ghost dark energy model in the presence of nonlinear interaction between dark energy and dark matter. We also extend the analysis to the so-called generalized ghost dark energy (GGDE) which [Formula: see text]. The model contains three free parameters as [Formula: see text] and [Formula: see text] (the coupling coefficient of interactions). We propose three kinds of nonlinear interaction terms and discuss the behavior of equation of state, deceleration and dark energy density parameters of the model. We also find the squared sound speed and search for signs of stability of the model. To compare the interacting GGDE model with observational data sets, we use more recent observational outcomes, namely SNIa from JLA catalog, Hubble parameter, baryonic acoustic oscillation and the most relevant CMB parameters including, the position of acoustic peaks, shift parameters and redshift to recombination. For GGDE with the first nonlinear interaction, the joint analysis indicates that [Formula: see text], [Formula: see text] and [Formula: see text] at 1 optimal variance error. For the second interaction, the best fit values at [Formula: see text] confidence are [Formula: see text], [Formula: see text] and [Formula: see text]. According to combination of all observational data sets considered in this paper, the best fit values for third nonlinearly interacting model are [Formula: see text], [Formula: see text] and [Formula: see text] at [Formula: see text] confidence interval. Finally, we found that the presence of interaction is compatible in mentioned models via current observational datasets.

Download Full-text

Sensitivity of precipitation in the highlands and lowlands of Peru to physics parameterization options in WRFV3.8.1

10.5194/gmd-2021-307 ◽

2021 ◽

Author(s):

Santos J. González-Rojí ◽

Martina Messmer ◽

Christoph C. Raible ◽

Thomas F. Stocker

Keyword(s):

Observational Data ◽

Amazon Basin ◽

Cumulus Parameterization ◽

Data Sets ◽

Monthly Precipitation ◽

Microphysics Scheme ◽

The Andes ◽

Station Data ◽

Pattern Correlation ◽

Simulated Precipitation

Abstract. The performance of the Weather Research and Forecasting (WRF) model version 3.8.1 at convection-permitting scale is evaluated by means of several sensitivity simulations over southern Peru down to a grid resolution of 1 km, whereby the main focus is on the domain with 5 km horizontal resolution. Different configurations of microphysics, cumulus, longwave radiation and planetary boundary layer schemes are tested. For the year 2008, the simulated precipitation amounts and patterns are compared to gridded observational data sets and weather station data gathered from Peru, Bolivia and Brazil. The temporal correlation of simulated monthly precipitation sums against in-situ and gridded observational data show that the most challenging regions for WRF are the slopes along both sides of the Andes, i.e., elevations between 1000 and 3000 m above sea level. The pattern correlation analysis between simulated precipitation and station data suggests that all tested WRF setups perform rather poorly along the northeastern slopes of the Andes during the entire year. In the southwestern region of the domain the performance of all setups is better except for the driest period (May–September). The results of the pattern correlation to the gridded observational data sets show that all setups perform reasonably well except along both slopes during the dry season. The precipitation patterns reveal that the typical setup used over Europe is too dry throughout the entire year, and that the experiment with the combination of the single-moment 6-class microphysics scheme and the Grell–Freitas cumulus parameterization in the domains with resolutions larger than 5 km, suitable for East Africa, does not perfectly apply to other equatorial regions such as the Amazon basin in southeastern Peru. The experiment with the Stony–Brook University microphysics scheme and the Grell-Freitas cumulus parameterization tends to overestimate precipitation over the northeastern slopes of the Andes, but allows to enforce a positive feedback between the soil moisture, air temperature, relative humidity, mid-level cloud cover and finally, also precipitation. Hence, this setup is the one providing the most accurate results over the Peruvian Amazon, and particularly over the department of Madre de Dios, which is a region of interest because it is considered the biodiversity hotspot of Peru. The robustness of this particular parameterization option is backed up by similar results obtained during wet climate conditions observed in 2012.

Download Full-text

Sensible use of observational clinical data

Statistical Methods in Medical Research ◽

10.1177/0962280211403598 ◽

2011 ◽

Vol 22 (1) ◽

pp. 7-13 ◽

Cited By ~ 20

Author(s):

J Marc Overhage ◽

Lauren M Overhage

Keyword(s):

Health Care ◽

Clinical Trials ◽

Medical Research ◽

Observational Data ◽

Clinical Data ◽

Low Cost ◽

Clinical Care ◽

Data Sets ◽

Large Size ◽

Health Care Operations

Observational data sets offer many potential advantages for medical research including their low cost, large size and generalisability. Because they are collected for clinical care and health care operations purposes, observational data sets have some limitations that must be considered in order to perform useful analyses. Sensible use of observational data sets can yield valuable insights, particularly when clinical trials are impractical.

Download Full-text

Constraining models of activity on comet 67P/Churyumov-Gerasimenko with Rosetta trajectory, rotation, and water production measurements

Astronomy and Astrophysics ◽

10.1051/0004-6361/201834415 ◽

2019 ◽

Vol 630 ◽

pp. A18 ◽

Cited By ~ 12

Author(s):

N. Attree ◽

L. Jorda ◽

O. Groussin ◽

S. Mottola ◽

N. Thomas ◽

...

Keyword(s):

Momentum Transfer ◽

Observational Data ◽

Activity Pattern ◽

Seasonal Effects ◽

Data Sets ◽

Gravitational Acceleration ◽

Water Production ◽

Active Fraction ◽

Trajectory Data ◽

Comet 67P

Aims. We use four observational data sets, mainly from the Rosetta mission, to constrain the activity pattern of the nucleus of comet 67P/Churyumov-Gerasimenko (67P). Methods. We developed a numerical model that computes the production rate and non-gravitational acceleration of the nucleus of comet 67P as a function of time, taking into account its complex shape with a shape model reconstructed from OSIRIS imagery. We used this model to fit three observational data sets: the trajectory data from flight dynamics; the rotation state as reconstructed from OSIRIS imagery; and the water production measurements from ROSINA of 67P. The two key parameters of our model, adjusted to fit the three data sets all together, are the activity pattern and the momentum transfer efficiency (i.e., the so-called η parameter of the non-gravitational forces). Results. We find an activity pattern that can successfully reproduce the three data sets simultaneously. The fitted activity pattern exhibits two main features: a higher effective active fraction in two southern super-regions (~10%) outside perihelion compared to the northern regions (<4%), and a drastic rise in effective active fraction of the southern regions (~25−35%) around perihelion. We interpret the time-varying southern effective active fraction by cyclic formation and removal of a dust mantle in these regions. Our analysis supports moderate values of the momentum transfer coefficient η in the range 0.6–0.7; values η ≤ 0.5 or η ≥ 0.8 significantly degrade the fit to the three data sets. Our conclusions reinforce the idea that seasonal effects linked to the orientation of the spin axis play a key role in the formation and evolution of dust mantles, and in turn, they largely control the temporal variations of the gas flux.

Download Full-text

Non-steroidal anti-inflammatory drugs and their benefits and harms: the challenge of interpreting meta-analyses and observational data sets when balanced data are not analyzed and reported

Arthritis Research & Therapy ◽

10.1186/s13075-015-0650-1 ◽

2015 ◽

Vol 17 (1) ◽

Cited By ~ 1

Author(s):

Lee S. Simon

Keyword(s):

Observational Data ◽

Data Sets ◽

Inflammatory Drugs ◽

Anti Inflammatory ◽

Meta Analyses

Download Full-text

Low-frequency variations in surface atmospheric humidity, temperature, and precipitation: Inferences from reanalyses and monthly gridded observational data sets

Journal of Geophysical Research Atmospheres ◽

10.1029/2009jd012442 ◽

2010 ◽

Vol 115 (D1) ◽

Cited By ~ 312

Author(s):

A. J. Simmons ◽

K. M. Willett ◽

P. D. Jones ◽

P. W. Thorne ◽

D. P. Dee

Keyword(s):

Observational Data ◽

Low Frequency ◽

Data Sets ◽

Atmospheric Humidity ◽

Temperature And Precipitation ◽

Frequency Variations

Download Full-text

The Hong Kong/AAO/Strasbourg Hα (HASH) Planetary Nebula Database

Proceedings of the International Astronomical Union ◽

10.1017/s1743921317003234 ◽

2016 ◽

Vol 12 (S323) ◽

pp. 327-328

Author(s):

Ivan S. Bojičić ◽

Quentin A. Parker ◽

David J. Frew

Keyword(s):

Hong Kong ◽

Observational Data ◽

Planetary Nebula ◽

Scattered Data ◽

Easy Access ◽

Online Research ◽

Data Sets ◽

Main Motivation ◽

Research Platform ◽

Imaging And Spectroscopy

AbstractThe Hong Kong/AAO/Strasbourg Hα (HASH) planetary nebula database is an online research platform providing free and easy access to the largest and most comprehensive catalogue of known Galactic PNe and a repository of observational data (imaging and spectroscopy) for these and related astronomical objects. The main motivation for creating this system is resolving some of long standing problems in the field e.g. problems with mimics and dubious and/or misidentifications, errors in observational data and consolidation of the widely scattered data-sets. This facility allows researchers quick and easy access to the archived and new observational data and creating and sharing of non-redundant PN samples and catalogues.

Download Full-text

Identifying environmental controls on vegetation greenness phenology through model-data integration

Biogeosciences Discussions ◽

10.5194/bgd-11-10917-2014 ◽

2014 ◽

Vol 11 (7) ◽

pp. 10917-11025

Author(s):

M. Forkel ◽

N. Carvalhais ◽

S. Schaphoff ◽

W. v. Bloh ◽

M. Migliavacca ◽

...

Keyword(s):

Time Series ◽

Observational Data ◽

Water Availability ◽

Boreal Forests ◽

Growing Season ◽

The Arctic ◽

Data Sets ◽

Vegetation Greenness ◽

Environmental Controls ◽

Dynamics Of Vegetation

Abstract. Existing dynamic global vegetation models (DGVMs) have a~limited ability in reproducing phenology and decadal dynamics of vegetation greenness as observed by satellites. These limitations in reproducing observations reflect a poor understanding and description of the environmental controls on phenology, which strongly influence the ability to simulate longer term vegetation dynamics, e.g. carbon allocation. Combining DGVMs with observational data sets can potentially help to revise current modelling approaches and thus to enhance the understanding of processes that control seasonal to long-term vegetation greenness dynamics. Here we implemented a~new phenology model within the LPJmL (Lund Potsdam Jena managed lands) DGVM and integrated several observational data sets to improve the ability of the model in reproducing satellite-derived time series of vegetation greenness. Specifically, we optimized LPJmL parameters against observational time series of the fraction of absorbed photosynthetic active radiation (FAPAR), albedo and gross primary production to identify the main environmental controls for seasonal vegetation greenness dynamics. We demonstrated that LPJmL with new phenology and optimized parameters better reproduces seasonality, inter-annual variability and trends of vegetation greenness. Our results indicate that soil water availability is an important control on vegetation phenology not only in water-limited biomes but also in boreal forests and the arctic tundra. Whereas water availability controls phenology in water-limited ecosystems during the entire growing season, water availability co-modulates jointly with temperature the beginning of the growing season in boreal and arctic regions. Additionally, water availability contributes to better explain decadal greening trends in the Sahel and browning trends in boreal forests. These results emphasize the importance of considering water availability in a new generation of phenology modules in DGVMs in order to correctly reproduce observed seasonal to decadal dynamics of vegetation greenness.

Download Full-text

A 20-year record (1998–2017) of permafrost, active layer, and meteorological conditions at a High Arctic permafrost research site (Bayelva, Spitsbergen): an opportunity to validate remote sensing data and land surface, snow, and permafrost models

10.5194/essd-2017-100 ◽

2017 ◽

Cited By ~ 2

Author(s):

Julia Boike ◽

Inge Juszak ◽

Stephan Lange ◽

Sarah Chadburn ◽

Eleanor Burke ◽

...

Keyword(s):

Energy Balance ◽

High Resolution ◽

Observational Data ◽

Digital Elevation Model ◽

Positive Feedback ◽

The Arctic ◽

Data Sets ◽

Data Set ◽

Digital Elevation ◽

Elevation Model

Abstract. Most permafrost is located in the Arctic, where frozen organic carbon makes it an important component of the global climate system. Despite the fact that the Arctic climate changes more rapidly than the rest of the globe, observational data density in the region is low. Permafrost thaw and carbon release to the atmosphere are a positive feedback mechanism that can exacerbate climate warming. This positive feedback functions via changing land-atmosphere energy and mass exchanges. There is thus a great need to understand links between the energy balance, which can vary rapidly over hourly to annual time scales, and permafrost, which changes slowly over long time periods. This understanding thus mandates long-term observational data sets. Such a data set is available from the Bayelva Site at Ny-Ålesund, Svalbard, where meteorology, energy balance components and subsurface observations have been made for the last 20 years. Additional data include a high resolution digital elevation model and a panchromatic image. This paper presents the data set produced so far, explains instrumentation, calibration, processing and data quality control, as well as the sources for various resulting data sets. The resulting data set is unique in the Arctic and serves a baseline for future studies. Since the data provide observations of temporally variable parameters that mitigate energy fluxes between permafrost and atmosphere, such as snow depth and soil moisture content, they are suitable for use in integrating, calibrating and testing permafrost as a component in Earth System Models. The data set also includes a high resolution digital elevation model that can be used together with the snow physical information for snow pack modeling. The presented data are available in the supplementary material for this paper and through the PANGAEA website ( https://doi.pangaea.de/10.1594/PANGAEA.880120).

Download Full-text