Sentences with phrase «reanalysis system»

A reanalysis system is a global large scale numerical forecast model (currently a numerical approximation of the ill posed hydrostatic system, e.g. the ECMWF model) that assimilates (inserts or mixes) observational data in with the numerical model forecast in an attempt to obtain a better set of global data.

ΔCRF is the change in TOA net flux anomaly if clouds were instantaneously removed, with everything else held fixed, and it is determined by subtracting ΔRall - sky, obtained from CERES measurements, from the clear - sky flux anomalies ΔRclear - sky, obtained from a reanalysis system.»

Balmaseda et al. (2013) was a key study on this subject, using ocean heat content data from the European Centre for Medium - Range Weather Forecasts» Ocean Reanalysis System 4 (ORAS4).

Several reanalysis systems are developed to generate high - resolution regional reanalysis data sets for Europe based on the NWP model COSMO.

Global average temperatures are also estimated using reanalysis systems, which use a weather forecasting system to combine many sources of data to provide a more complete picture of global temperatures.

The reanalysis systems have been underutilized for estimated temperature trends, warmest years, etc..

Zou (January 2017): Introduction to the SPARC Reanalysis Intercomparison Project (S - RIP) and overview of the reanalysis systems.

In addition, as land surface heterogeneity is a crucial part in high - resolution modeling especially with respect to land surface changes, we want to dedicate a larger part of the input data session to efforts of generating high - resolution land surface data sets (and time series of these) applicable as lower boundary conditions in atmospheric reanalysis systems as well as in coupled reanalysis approaches.

Not exact matches

Using NCEP / NCAR reanalysis the only weather that stands out as being anomalous is a high pressure system over the Arctic in 2010 presumably related in some way to high temperatures.

European Centre for Medium - Range Weather Forecasts (ECMWF) Integrated Forecast System (IFS) and the ERA - 40 Reanalysis

Zhang and Lindsay, 4.3 ± 0.8, Model The forecasting system is based on a synthesis of a model, the NCEP / NCAR reanalysis data, and satellite observations of ice concentration and sea surface temperature.

To study the historical evolution of the arctic system, 1948 - 2003 reanalysis data with varying NAO / AO indices will be input into the model.

The National Centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis (CFSR) spans 1979 to present.

The anomalous ridge was investigated using reanalysis data and the Community Earth System Model (CESM).

The modeling and assimilation in the GEOS5 system that performs the MERRA reanalysis runs at 72 terrain following (eta) coordinates.

The Arctic System Reanalysis (ASR), a high - resolution regional assimilation of model output, observations, and satellite data across the mid - and high latitudes of the Northern Hemisphere for the period 2000 — 2012 has been performed at 30 km (ASRv1) and 15 km (ASRv2) horizontal resolution using the polar version of the Weather Research and Forecasting (WRF) model and the WRF Data Assimilation (WRFDA) System.

In fact, a major rationale for doing reanalysis at all was the possibility to create long records of weather, using modern analysis / forecast systems, and without the operational discontinuities.

MERRA is a NASA reanalysis for the satellite era using a major new version (circa 2008) of the Goddard Earth Observing System Data Assimilation System Version 5 (GEOS - 5) produced by the NASA GSFC Global Modeling and Assimilation Office (GMAO).

I would say the Arctic System Reanalysis is precisely what you are looking for.

He plays a leading role in the Arctic System Reanalysis (ASR) and the Antarctic Mesoscale Prediction System (AMPS) and is a PI of the YOPP - endorsed AWARE project.

WDAC works with the The WCRP Modelling Advisory Council (WMAC) to promote effective use of observations with models and to address issues related to the coordinated development of data assimilation, reanalysis, Observing System Sensitivity Experiments, and paleoclimatic data and their assessments.

These include the primary surface temperature thermometer records (NASA GISS, NOAA, and HadCRUT); satellite measurements of the lower troposphere temperature processed by Remote Sensing Systems (RSS) and the University of Alabama - Huntsville (UAH); and 5 major reanalysis datasets which incorporate station data, aircraft data, satellite data, radiosonde data, buoy and ship measurements, and meteorological weather modeling.

The forecasting system is based on a synthesis of a model, the NCEP / NCAR reanalysis data, and satellite observations of ice concentration and sea surface temperature.

Metzger et al. (NRL Stennis Space Center), 5.0 (3.4 - 6.0), Modeling The Global Ocean Forecast System (GOFS) 3.1 was run in forecast mode without data assimilation, initialized with July 1, 2015 ice / ocean analyses, for ten simulations using National Centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis (CFSR) atmospheric forcing fields from 2005 - 2014.

Wang, 5.0 (± 0.27), Modeling A projected September Arctic sea ice extent of 5.0 million km2 is based on a NCEP ensemble mean CFSv2 forecast initialized from the NCEP Climate Forecast System Reanalysis (CFSR) that assimilates observed sea ice concentrations and other atmospheric and oceanic observations.

Data are from the NCEP — NCAR Reanalysis through the NOAA / Earth Systems Research Laboratory, generated online at http://www.esrl.noaa.gov/psd/cgi-bin/data/composites/printpage.pl

Here we test the null hypothesis that the observations are randomly distributed about the EM predictions using a new metric that quantifies the distance between the EM predictions from the National Centers for Environmental Prediction (NCEP) Climate Forecast System version 2 (CFSv2) and the observations represented by CFSv2 Reanalysis.

The datasets considered include a blended in situ - satellite dataset extending from 1923 to 2012 (Brown), the National Oceanic and Atmospheric Administration (NOAA) snow chart Climate Data Record for 1968 — 2012, the Global Land Data Assimilation System version 2.0 (GLDAS - 2 Noah) reanalysis for 1951 — 2010, and the NOAA 20th - century reanalysis, version 2 (20CR2) covering 1948 — 2012.

The National Centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis (CFSR) data were used for atmospheric forcing along WRF lateral boundaries from 1979 until the respective initialization date and time.

NRL - ocn - ice, 5.2 (4.3 - 6.0), Modeling (ice - ocean) The Global Ocean Forecast System (GOFS) 3.1 was run in forecast mode without data assimilation, initialized with June 1, 2016 ice / ocean analyses, for ten simulations using National Centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis (CFSR) atmospheric forcing fields from 2005 - 2014.

The 6th ECMWF reanalysis (ERA6) will use the (C++ based) Object - Oriented Prediction System (OOPS) and (Fortran - based) Integrated Forecasting System (IFS) and there is a requirement to optimise the variational bias correction system under OOPS anSystem (OOPS) and (Fortran - based) Integrated Forecasting System (IFS) and there is a requirement to optimise the variational bias correction system under OOPS anSystem (IFS) and there is a requirement to optimise the variational bias correction system under OOPS ansystem under OOPS and IFS.

Artic System Reanalysis: Call for community involvement.

Additional data that we use to aid our interpretations include geopotential height and 10 - m wind fields from the National Centers for Environmental Prediction, version 2 (NCEP2) reanalysis for 1979 - 2008 (Kanamitsu et al. 2002), obtained from the NOAA Earth Systems Research Laboratory (http://www.esrl.noaa.gov/psd/data/gridded/).

Our delegates, Juan Garces de Marcilla, ECMWF's Director of Copernicus Services, Joaquin Munoz Sabater, C3S reanalysis scientist and Angel Lopez Alos, System Analyst ECMWF's C3S Production Team, presented how ECMWF is implementing the EU - funded Copernicus Climate Change Service (C3S) and Atmosphere Monitoring Service (CAMS).

The ECMWF provides its supercomputer - run Integrated Forecasting System, a world - renowned numerical weather prediction model, as a basis for some Copernicus services, such as atmospheric forecasts and reanalysis data.

WGNE also monitors the advances in data assimilation and analysis methods and is the focal point in the WCRP for encouraging and reviewing the reanalysis projects carried out at various centres with fixed state - of - the - art assimilation systems providing a multi-year homogenous data set for a range of atmospheric and climate diagnostic studies.

The also used observation data: ``... inferred them from observations of barometric pressure, sea surface temperature, and sea - ice concentration using a physically based data assimilation system called the 20th Century Reanalysis.»

Dear Mostafa, Hourly data are available from NOAA NCEP's Climate Forecast System Reanalysis (CFSR, http://reanalyses.org/atmosphere/overview-current-reanalyses#CFSR) See the Data Access links.

Using a state - of - the - art data assimilation system and surface pressure observations, the Twentieth Century Reanalysis Project is generating a six - hourly, four - dimensional global atmospheric dataset spanning 1851 to 2014 to place current atmospheric circulation patterns into a historical perspective.

The ERA - Interim reanalysis: Configuration and performance of the data assimilation system.

The era - interim reanalysis: Configuration and performance of the data assimilation system.

20th Century Reanalysis: Methods and Applications To better understand and model the observed variability of the earth system, one can rapidly expand the available record by objectively combining disparate observations with numerical model - generated guesses.

Furthermore, the NCEP Reanalysis and other reanalysis products suffer from horrible model bias and inhomogeneities related to the evolving observing system, mainly the inclusion of new satellite rReanalysis and other reanalysis products suffer from horrible model bias and inhomogeneities related to the evolving observing system, mainly the inclusion of new satellite rreanalysis products suffer from horrible model bias and inhomogeneities related to the evolving observing system, mainly the inclusion of new satellite retrievals.

To answer this question I looked at more than just the traditional Hadley, NASA and NOAA datasets, but also the measurements of the lower troposphere processed by Remote Sensing Systems (RSS) and the University of Alabama - Huntsville (UAH) as well as the 5 major reanalysis datasets which incorporate station data, aircraft data, satellite data, radiosonde data and meteorological weather modeling.

Using NCEP - 2 reanalysis data, Lim and Simmonds (2002) showed that for 1979 to 1999, increasing trends in the annual number of explosively developing (deepening by 1 hPa per hour or more) extratropical cyclones are signifi cant in the SH and over the globe (0.56 and 0.78 more systems per year, respectively), while the positive trend did not achieve signifi cance in the NH.

ac, that seems understandable to some extent, but what would you say if someone else (perhaps even yourself in a few years time, performing a reanalysis with a better model) came up with a different system that also gave perfectly calibrated predictions but which differed from your «true» values?

10) Part of the CMIP5 era of GCMs, the recently released Community Climate System Model version 4 (CCSM4) shows major circulation biases as compared with ECMWF 40 - year reanalysis data.

As reanalysis datasets become more diverse (atmosphere, ocean and land components), more complete (moving towards Earth - system coupled reanalysis), more detailed, and of longer timespan, community efforts to evaluate and intercompare them become more important.