The International Financial Statistics database covers about 200 countries and areas, with some aggregates calculated for selected regions, plus some world totals. Topics covered include balance of payments, commodity prices, exchange rates, fund position, government finance, industrial production, interest rates, international investment position, international liquidity, international transactions, labor statistics, money and banking, national accounts, population, prices, and real effective exchange rates.

The International Financial Statistics is based on various IMF data collections. It includes exchange rates series for all Fund member countries plus Anguilla, Aruba, China, P.R.: Hong Kong, China, P.R.: Macao, Montserrat, and the Netherlands Antilles. It also includes major Fund accounts series, real effective exchange rates, and other world, area, and country series. Data are available for most IMF member countries with some aggregates calculated for select regions, plus some world totals.

This data set contains the 0.1 degree resolution output from the ECMWF IFS (European Centre for Medium-Range Weather Forecasts Integrated Forecasting System) model during the SOCRATES field phase. Grids include analysis and forecast time steps at a three hourly interval to 48 hours and at six hour intervals to 120 hours. The ECMWF runs are available at 00 and 12 UTC daily. At 06 and 18 UTC just the analysis grids are included. These data are in GRIB format.

Taiwan BoP: IFS: CA: Debit data was reported at 4.000 USD mn in Sep 2018. This records a decrease from the previous number of 6.000 USD mn for Jun 2018. Taiwan BoP: IFS: CA: Debit data is updated quarterly, averaging 5.000 USD mn from Mar 1997 (Median) to Sep 2018, with 87 observations. The data reached an all-time high of 254.000 USD mn in Mar 2008 and a record low of 0.000 USD mn in Dec 2000. Taiwan BoP: IFS: CA: Debit data remains active status in CEIC and is reported by Central Bank of the Republic of China. The data is categorized under Global Database’s Taiwan – Table TW.JB009: Balance of Payments: IFS Format.

ECMWF IFS Ensemble (ENS): 51-member global probabilistic weather forecast model. 0.25° grid, 15-day horizon. Get ensemble means, quantiles, and members as JSON, CSV, or NDJSON from GribStream API. Open data (CC-BY-4.0).

The dataset used in this paper is the Integrated Forecast System (IFS) data, which is a high-resolution weather forecast dataset.

Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets. These data include all datasets published for 'CMIP6.HighResMIP.ECMWF.ECMWF-IFS-LR' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'.

The ECMWF-IFS-LR (50 km atmosphere and 100 km ocean) climate model, released in 2017, includes the following components: atmos: IFS (IFS CY43R1, Tco199, cubic octahedral reduced Gaussian grid equivalent to 800 x 400 longitude/latitude; 91 levels; top level 0.01 hPa), land: HTESSEL (as implemented in IFS CY43R1), ocean: NEMO3.4 (NEMO v3.4; ORCA1 tripolar grid; 362 x 292 longitude/latitude; 75 levels; top grid cell 0-1 m), seaIce: LIM2 (LIM v2; ORCA1 tripolar grid; 362 x 292 longitude/latitude). The model was run by the European Centre for Medium-Range Weather Forecasts, Reading RG2 9AX, UK (ECMWF) in native nominal resolutions: atmos: 50 km, land: 50 km, ocean: 100 km, seaIce: 100 km.

Project: These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6).

CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ).

The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. - Project website: https://pcmdi.llnl.gov/CMIP6.

Taiwan BoP: IFS: FA: OI: Liabilities data was reported at 5.678 USD bn in Dec 2017. This records a decrease from the previous number of 17.986 USD bn for Sep 2017. Taiwan BoP: IFS: FA: OI: Liabilities data is updated quarterly, averaging 2.682 USD bn from Mar 1997 (Median) to Dec 2017, with 84 observations. The data reached an all-time high of 19.213 USD bn in Sep 2013 and a record low of -14.481 USD bn in Dec 2015. Taiwan BoP: IFS: FA: OI: Liabilities data remains active status in CEIC and is reported by Central Bank of the Republic of China. The data is categorized under Global Database’s Taiwan – Table TW.JB009: Balance of Payments: IFS Format.

This dataset presents a 31-year IFS-FESOM coupled climate model simulation using constant 1950 radiative forcing, based on CMIP6 standards. It is part of the official coupled spin-up for EERIE phase 1 simulation and reaches a steady state after the first 10 years. The simulation features high-resolution grids: approximately 9 km for the atmospheric component (IFS) and 5 km for the ocean component (FESOM). The atmospheric component uses ECMWF IFS cycle 48R1, while the ocean model employs FESOM2.5 with an NG5 grid comprising about 7.5 million surface nodes. The dataset includes high-priority variables in both native high-resolution grids and interpolated to a 0.25-degree regular grid. Vertically, the atmosphere is resolved with 137 levels (output provided at 23 pressure levels), and the ocean with 70 depth levels. Prior to the main simulation, the ocean model underwent a 5-year stand-alone spin-up using EN4 boundary conditions. This high-resolution simulation effectively resolves mesoscale eddies in midlatitude oceans and simulates tropical instability waves, with a potential to offer insights on their role in our climate system. The EERIE version identifier for this dataset is v20240304.

This dataset contains model data for SNAPSI experiment 'free' produced by scientists at ECMWF (European Centre for Medium-Range Weather Forecasts, United Kingdom). This dataset contains all ensemble members by the ECMWF IFS model.

The SNAPSI project is a model intercomparison project to study the role of the stratosphere in subseasonal forecasts following stratospheric sudden warmings and the representation of stratosphere-troposphere coupling in subseasonal forecast models.

The free experiment is a set of retrospective, 45-day, 50-member ensemble forecasts. The forecasts are initialized on the date indicated by the sub-experiment id; for instance, the sub-experiment 's20180125' is initialized on 25 January 2018. The ocean, sea-ice, land-surface and ozone are all initialized and run prognostically.

Sources of additional information

The following web links are provided in the Details/Docs section of this catalogue record: - Stratospheric Nudging And Predictable Surface Impacts (SNAPSI): A Protocol for Investigating the Role of the Stratospheric Polar Vortex in Subseasonal to Seasonal Forecasts - New set of controlled numerical experiments: Stratospheric Nudging And Predictable Surface Impacts (SNAPSI) - ECMWF IFS model reference publication

This dataset includes the ECMWF-IFS4 model output prepared for SPECS SoilMoistureInit (1981-2013). These data were prepared by the European Centre for Medium-range Weather Forecasting (ECMWF), as part of the SPECS project. Model id is IFS4 (atmosphere: IFS4(201505212,CY41R1,N128TL255L91); ocean:NEMO3.4.1(L34E5,ORCA1_Z42,1°L42); seaice:N/A; MACC:N/A; land:CHTESSEL,ERA-Interim forcing, active lakes, GPCP correction, carbon fixes (CY40R1, internal exp.id g2ze, climate.v009); wave:WAM(CY41R1,1°); ozone:Cariolle(v2.9); climversion:climate.v010), no external forcing. frequency is daily and monthly. Daily Atmospheric variables are: clt pr psl rlut rsds tas tasmax tasmin tdps uas vas Monthly atmos variables: al clt hfls hfss mrso pr psl rls rlut rsds rsdt rss rsut snld ta tas tasmax tasmin tdps uas vas zg

ECMWF IFS (Integrated Forecasting System) global deterministic weather forecast model. 0.25° grid, 15-day range, open data (CC-BY-4.0). Access IFS forecasts as JSON, CSV, or NDJSON via GribStream API. Supports renewable energy, aviation, and research.

Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets. These data include all datasets published for 'CMIP6.HighResMIP.ECMWF.ECMWF-IFS-HR.control-1950' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'.

The ECMWF-IFS-HR (25 km atmosphere and 25 km ocean) climate model, released in 2017, includes the following components: atmos: IFS (IFS CY43R1, Tco399, cubic octahedral reduced Gaussian grid equivalent to 1600 x 800 longitude/latitude; 91 levels; top level 0.01 hPa), land: HTESSEL (as implemented in IFS CY43R1), ocean: NEMO3.4 (NEMO v3.4; ORCA025 tripolar grid; 1442 x 1021 longitude/latitude; 75 levels; top grid cell 0-1 m), seaIce: LIM2 (LIM v2; ORCA025 tripolar grid; 1442 x 1021 longitude/latitude). The model was run by the European Centre for Medium-Range Weather Forecasts, Reading RG2 9AX, UK (ECMWF) in native nominal resolutions: atmos: 25 km, land: 25 km, ocean: 25 km, seaIce: 25 km.

Project: These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6).

CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ).

The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. - Project website: https://pcmdi.llnl.gov/CMIP6.

This presentation is aimed at those who are starting up the learning curve on all the international socioeconomic data sources out there. Comparisons of coverage, ease of use, advantages and disadvantages will be presented for services such as World Development Indicators (WDI), International Financial Statistics (IFS), the Economist Intelligence Unit (EIU) WorldDATA, United Nations Data bases, etc. A secondary focus will evaluate what else is worth exploring besides the big, well-known data providers just mentioned. (Note: Data associated with this presentation is available on the DLI FTP site under folder 1873-220.)

Taiwan BoP: IFS: CA: Credit data was reported at 11.000 USD mn in Sep 2018. This records an increase from the previous number of 3.000 USD mn for Jun 2018. Taiwan BoP: IFS: CA: Credit data is updated quarterly, averaging 0.000 USD mn from Mar 1997 (Median) to Sep 2018, with 87 observations. The data reached an all-time high of 49.000 USD mn in Jun 2013 and a record low of 0.000 USD mn in Sep 2012. Taiwan BoP: IFS: CA: Credit data remains active status in CEIC and is reported by Central Bank of the Republic of China. The data is categorized under Global Database’s Taiwan – Table TW.JB009: Balance of Payments: IFS Format.

This dataset includes the ECMWF-IFS model output prepared for SPECS seasonal (1981-2012). These data were prepared by the European Centre for Medium-range Weather Forecasting (ECMWF), as part of the SPECS project. Model id is IFS (IFS C36R4), frequency is daily and monthly. Daily Atmospheric variables are: rlut Monthly atmos variables: al clt hfls hfss mrso pr psl rls rsds rss snld tas tdps uas vas Monthly ocean variables: mlotst sos t20d thetao tos uo vo

This dataset contains 15-day forecasts of the atmospheric model variables generated by the ECMWF Integrated Forecasting System (IFS) at 0.25 degree resolution. We refer to these as Near-Realtime (NRT) because new products are released twice a day after the release of the ECMWF realtime forecast data, of which this is a subset. Data may be distributed and used commercially with proper attribution. Products are available in Earth Engine starting with the implementation of Cycle 49r1 on 2024/11/12; earlier products are not included. For general information about how to use ECMWF NRT datasets, see their user documentation. Sources files are available in the Google Cloud marketplace.

This dataset contains model data for SNAPSI experiment 'control' produced by scientists at ECMWF (European Centre for Medium-Range Weather Forecasts, United Kingdom). This dataset contains all ensemble members produced by the ECMWF IFS model.

The SNAPSI project is a model intercomparison project to study the role of the stratosphere in subseasonal forecasts following stratospheric sudden warmings and the representation of stratosphere-troposphere coupling in subseasonal forecast models.

The control experiment is a set of retrospective, 45-day, 50-member ensemble forecasts. Following the initial date, the stratospheric zonal mean temperatures and zonal winds are nudged towards the time-evolving climatological state. The forecasts are initialized on the date indicated by the sub-experiment id; for instance, the sub-experiment 's20180125' is initialized on 25 January 2018. The ocean, sea-ice, land-surface and ozone are all initialized and run prognostically.

Sources of additional information

The following web links are provided in the Details/Docs section of this catalogue record: - Stratospheric Nudging And Predictable Surface Impacts (SNAPSI): A Protocol for Investigating the Role of the Stratospheric Polar Vortex in Subseasonal to Seasonal Forecasts - New set of controlled numerical experiments: Stratospheric Nudging And Predictable Surface Impacts (SNAPSI) - ECMWF IFS model reference publication

Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

Graph and download economic data for Nominal External Balance of Goods and Services for Turkey (NNXGSXDCTRA) from 1998 to 2024 about external, Turkey, balance, goods, and services.

Graph and download economic data for Real Changes in Inventories for Japan (NINVRXDCJPA) from 1994 to 2024 about change, inventories, Japan, and real.