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Chapter 1: Observation operators
Chapter 2: Observation processing
Chapter 3: Observation screening

Image Removed IFS_CY40R1_Part1.pdfDocumentation for Part I: Observation Processing

Data assimilation

Chapter 1: Overview
Chapter 2: 4D variational assimilation
Chapter 3: Tangent-linear physics
Chapter 4: Background term
Chapter 5: Observation-related processing
Chapter 6: Background, analysis and forecast errors
Chapter 7: Gravity-wave control
Chapter 8: Diagnostics
Chapter 9: Land-surface analysis
Chapter 10: Analysis of sea-ice concentration and sea surface temperature
Chapter 11: Data flow
References

Image Removed IFS_CY40R1_Part2.pdfDocumentation for Part II: Data Assimilation

Dynamics and numerical procedures

Chapter 1: Introduction
Chapter 2: Basic equations and discretization
Chapter 3: Semi-Lagrangian formulation
References

Image Removed IFS_CY40R1_Part3.pdfDocumentation for Part III: Dynamics and Numerical Procedures

Physical processes

Chapter 1: Overview
Chapter 2: Radiation
Chapter 3: Turbulent transport and interactions with the surface
Chapter 4: Subgrid-scale orographic drag
Chapter 5: Non-orographic gravity wave drag
Chapter 6: Convection
Chapter 7: Clouds and large-scale precipitation
Chapter 8: Surface parametrization
Chapter 9: Methane oxidation
Chapter 10: Ozone chemistry parametrization
Chapter 11: Climatological data
References

Image Removed IFS_CY40R1_Part4.pdfDocumentation for Part IV: Physical Processes

Ensemble Prediction System

Chapter 1: Methodology
Chapter 2: Computational details: initial perturbations
Chapter 3: Computational details: non-linear integrations
References

Image Removed IFS_CY40R1_Part5.pdfDocumentation for Part V: The Ensemble Prediction System

Technical and Computational Procedures

Chapter 1: Structure, data flow and standards
Chapter 2: Parallel implementation
Appendix A: Structure, data flow and standards
Appendix B: Message Passing Library (MPL)
Appendix C: The TRANS package
Appendix D: FullPos user guide
Appendix E: FullPos technical guide
Appendix F: Coding standards
Appendix G: The Perforce source code management system user guide

Image Removed IFS_CY40R1_Part6.pdfDocumentation for Part VI: Technical and Computational Procedures

Wave Model

Chapter 1: Introduction
Chapter 2: The kinematic part of the energy balance equation
Chapter 3: Parametrization of source terms and the energy balance in a growing wind sea
Chapter 4: Data assimilation in WAM
Chapter 5: Numerical scheme
Chapter 6: WAM model software package
Chapter 7: Wind wave interaction at ECMWF
Chapter 8: Extreme wave forecasting
Chapter 9: Second-order spectrum
References

Image Removed IFS_CY40R1_Part7.pdfDocumentation for Part VII: ECMWF Wave Model

Meteorological changes

Vertical resolution of ENS

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Modifications to convection to address the diurnal cycle of precipitation (ECMWF Newsletter No. 136, pages 15–22). A package of changes introduced to vertical diffusion in stable conditions, turbulent orographic drag, orographic gravity wave drag and surface-atmosphere coupling over forests, which improves boundary layer winds (e.g. at wind turbine hub height) and improves northern hemisphere winter scores (ECMWF Newsletter No. 138 , pages 24-29). An error in the handling of snow albedo in the radiation scheme is corrected.

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SSMIS 183 GHz channels activated in all-sky microwave radiance assimilation, enhanced use of AMSU-A, AMSU-B and MHS data over sea ice, situation-dependent observation errors and revised quality-control for AMVs.

Meteorological impact

Comparison of scores of model cycle 40r1 and cycle 38r2

Upper air

The new cycle significantly improves the performance of HRES in the northern hemisphere, especially during autumn/winter time, and it has a neutral to slightly negative impact in the southern hemisphere. The temperature and humidity forecasts are also significantly improved in the lower troposphere in the tropics, while the 850 hPa winds are slightly degraded in certain tropical regions. This issue will be addressed in a forthcoming cycle. ENS and model changes associated with Cycle 40r1 produce overall improvements in probabilistic scores, except for a slight deterioration of tropical and southern hemisphere winds. The inclusion of the EDA-based land-surface temperature and moisture perturbations in ENS improves reliability, especially in the short range.

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The diurnal cycle of convection over land has been dramatically improved (see ECMWF Newsletter 136 - pages 15-22) so that the peak precipitation occurs later in the afternoon/early evening than in previous cycles. Verification of wind speed at a few tall tower locations in Europe has shown that the night time winds have improved in the height range from 50 to 200m, which is relevant for wind energy applications. There is a slight deterioration of ENS temperature in the extratropics. The overall impact on total cloud cover is neutral in the tropics and slightly positive in the extratropics. Precipitation is neutral in the HRES and significantly improved in the ENS for the tropics. Ocean coupling from day 0 in the ENS leads to better SST prediction in cases of slow tropical cyclone propagation.

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See ENS model level definitions for L91 and the correspondence between the L62 and L91 Most of the additional levels are added in the stratosphere. Levels below ~153 hPa are the same in the two representations (i.e., the 47 levels from 16 to 62 in the L62 representation map identically to levels 45 to 91 in the L91 representation).

See the  list of all other model level definitions currently in use

Changes to the GRIB data

ENS model level fields only

The increase in the number of vertical levels from 62 to 91 in the ensemble forecast model is reflected in changes to the GRIB headers, specifically the GRIB 2 Section 4 "Product definition section":

SectionOctetsgrib_api keyOld valueNew value
46-7NV126184
435-nnpvL62L91

Changes to GRIB headers affecting all fields

The GRIB model identifiers (generating process identification number) have changed as follow:

ModelOld IDNew ID
Atmospheric143144
Ocean wave109110
Limited-area ocean wave209210

The GRIB model identifiers are found in:

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