The NCEP and NCAR are cooperating in a project (denoted “reanalysis”) to produce a 40-year record of global analyses of atmospheric fields in support of the needs of the research and climate monitoring communities. This effort involves the recovery of land surface, ship, rawinsonde, pibal, aircraft, satellite, and other data; quality controlling and assimilating these data with a data assimilation system that is kept unchanged over the reanalysis period 1957–96. This eliminates perceived climate jumps associated with changes in the data assimilation system. The NCEP/NCAR 40-yr reanalysis uses a frozen state-of-the-art global data assimilation system and a database as complete as possible. The data assimilation and the model used are identical to the global system implemented operationally at the NCEP on 11 January 1995, except that the horizontal resolution is T62 (about 210 km). The database has been enhanced with many sources of observations not available in real time for operations, provided b...

The NCEP/NCAR 40-Year Reanalysis Project

ERA-Interim is the latest global atmospheric reanalysis produced by the European Centre for Medium-Range Weather Forecasts (ECMWF). The ERA-Interim project was conducted in part to prepare for a new atmospheric reanalysis to replace ERA-40, which will extend back to the early part of the twentieth century. This article describes the forecast model, data assimilation method, and input datasets used to produce ERA-Interim, and discusses the performance of the system. Special emphasis is placed on various difficulties encountered in the production of ERA-40, including the representation of the hydrological cycle, the quality of the stratospheric circulation, and the consistency in time of the reanalysed fields. We provide evidence for substantial improvements in each of these aspects. We also identify areas where further work is needed and describe opportunities and objectives for future reanalysis projects at ECMWF. Copyright © 2011 Royal Meteorological Society

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

This paper proposes a revised vertical diffusion package with a nonlocal turbulent mixing coefficient in the planetary boundary layer (PBL). Based on the study of Noh et al. and accumulated results of the behavior of the Hong and Pan algorithm, a revised vertical diffusion algorithm that is suitable for weather forecasting and climate prediction models is developed. The major ingredient of the revision is the inclusion of an explicit treatment of entrainment processes at the top of the PBL. The new diffusion package is called the Yonsei University PBL (YSU PBL). In a one-dimensional offline test framework, the revised scheme is found to improve several features compared with the Hong and Pan implementation. The YSU PBL increases boundary layer mixing in the thermally induced free convection regime and decreases it in the mechanically induced forced convection regime, which alleviates the well-known problems in the Medium-Range Forecast (MRF) PBL. Excessive mixing in the mixed layer in the presenc...

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A New Vertical Diffusion Package with an Explicit Treatment of Entrainment Processes

The NCEP Climate Forecast System Reanalysis (CFSR) was completed for the 31-yr period from 1979 to 2009, in January 2010. The CFSR was designed and executed as a global, high-resolution coupled atmosphere–ocean–land surface–sea ice system to provide the best estimate of the state of these coupled domains over this period. The current CFSR will be extended as an operational, real-time product into the future. New features of the CFSR include 1) coupling of the atmosphere and ocean during the generation of the 6-h guess field, 2) an interactive sea ice model, and 3) assimilation of satellite radiances by the Gridpoint Statistical Interpolation (GSI) scheme over the entire period. The CFSR global atmosphere resolution is ~38 km (T382) with 64 levels extending from the surface to 0.26 hPa. The global ocean's latitudinal spacing is 0.25° at the equator, extending to a global 0.5° beyond the tropics, with 40 levels to a depth of 4737 m. The global land surface model has four soil levels and the global sea ice m...

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The NCEP Climate Forecast System Reanalysis

This paper addresses and documents a number of issues related to the implementation of an advanced land surface–hydrology model in the Penn State–NCAR fifth-generation Mesoscale Model (MM5). The concept adopted here is that the land surface model should be able to provide not only reasonable diurnal variations of surface heat fluxes as surface boundary conditions for coupled models, but also correct seasonal evolutions of soil moisture in the context of a long-term data assimilation system. In a similar way to that in which the modified Oregon State University land surface model (LSM) has been used in the NCEP global and regional forecast models, it is implemented in MM5 to facilitate the initialization of soil moisture. Also, 1-km resolution vegetation and soil texture maps are introduced in the coupled MM5–LSM system to help identify vegetation/water/soil characteristics at fine scales and capture the feedback of these land surface forcings. A monthly varying climatological 0.15° × 0.15° green ...

https://www.sjsu.edu/people/frank.freedman/courses/metr130/s1/Paper-Chen-and-Dudhia---MWR.pdf

Coupling an Advanced Land Surface–Hydrology Model with the Penn State–NCAR MM5 Modeling System. Part I: Model Implementation and Sensitivity

A series of automated tests is developed for tower and aircraft time series to identify instrumentation problems, flux sampling problems, and physically plausible but unusual situations. The automated procedures serve as a safety net for quality controlling data. A number of special flags are developed representing a variety of potential problems such as inconsistencies between different tower levels and the flux error due to fluctuations of aircraft height. The tests are implemented by specifying critical values for parameters representing each specific error. The critical values are developed empirically from experience of applying the tests to real turbulent time series. When these values are exceeded, the record is flagged for further inspection and comparison with the rest of the concurrent data. The inspection step is necessary to either verify an instrumentation problem or identify physically plausible behavior. The set of tests is applied to tower data from the Riso Air Sea Experiment and...

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Quality Control and Flux Sampling Problems for Tower and Aircraft Data

A simple formulation of the boundary layer is developed for use in large-scale models and other situations where simplicity is required. The formulation is suited for use in models where some resolution is possible within the boundary layer, but where the resolution is insufficient for resolving the detailed boundary-layer structure and overlying capping inversion. Surface fluxes are represented in terms of similarity theory while turbulent diffusivities above the surface layer are formulated in terms of bulk similarity considerations and matching conditions at the top of the surface layer. The boundary-layer depth is expressed in terms of a bulk Richardson number which is modified to include the influence of thermals. Attention is devoted to the interrelationship between predicted boundary-layer growth, the turbulent diffusivity profile, ‘countergradient’ heat flux and truncation errors. The model predicts growth of the convectively mixed layer reasonably well and is well-behaved in cases of weak surface heat flux and transitions between stable and unstable cases. The evolution of the modelled boundary layer is studied for different ratios of surface evaporation to potential evaporation. Typical variations of surface evaporation result in a much greater variation in boundary-layer depth than that caused by the choice of the boundary-layer depth formulation.

A simple model of the atmospheric boundary layer; sensitivity to surface evaporation

This Chapter summarizes the steps of quality assurance and quality control of flux measurements with the eddy covariance method An important part is the di erent steps of the control for electronic, meteorological and statistical problems The fulfillment of the theoretical assumptions of the measuring method and thenon-steady state test and the integral turbulence test are extensively discussed as well as an overall flagging for data quality and a site specific quality analysis using footprint models Finally, problems are discussed which are not included yet in the control program, mainly connected with the complicated turbulence structure at a forest site

Post-Field Data Quality Control

Various features of different stability regimes of the stable boundary layer are discussed. Traditional layering is examined in terms of the roughness sublayer, surface layer, local similarity, z-less stratification and the region near the boundary-layer top. In the very stable case, the strongest turbulence may be detached from the surface and generated by shear associated with a low level jet, gravity waves or meandering motions. In this case, similarity theory and the traditional concept of a boundary-layer break down. The elevated turbulence may intermittently recouple to the surface. Inability to adequately measure turbulent fluxes in very stable conditions limits our knowledge of this regime.

Stratified atmospheric boundary layers

A two-layer model of soil hydrology and thermodynamics is combined with a one-dimensional model of the planetary boundary layer to study various interactions between evolution of the boundary layer and soil moisture transport. Boundary-layer moistening through surface evaporation reduces the potential and actual surface evaporation as well as the boundary-layer growth. With more advanced stages of soil drying, the restricted surface evaporation allows greater sensible heat flux which enhances boundary-layer growth and entrainment drying.

Larry Mahrt

Papers

Quality Control and Flux Sampling Problems for Tower and Aircraft Data

A simple model of the atmospheric boundary layer; sensitivity to surface evaporation

Post-Field Data Quality Control

Stratified atmospheric boundary layers

Interaction between soil hydrology and boundary-layer development