Multidecadal assessment of the FYRE Climate daily high-resolution surface reanalysis over France (1871-2012)

Surface observations are usually too few and far between to properly assess multidecadal variations at the local scale and characterize historical local extreme events at the same time. A data assimilation scheme has been recently presented by Devers et al. (2020) to assimilate daily observations of temperature and precipitation into downscaled reconstructions from a global extended reanalysis through an Ensemble Kalman fitting approach and derive high-resolution fields. Recent studies also showed that assimilating observations at high temporal resolution does not guarantee correct multidecadal variations. This work thus proposes (1) to apply this scheme over France and over the 1871&#8211;2012 period based on the SCOPE Climate reconstructions background dataset (Caillouet et al., 2019) and all available daily historical surface observations of temperature and precipitation, (2) to develop an assimilation scheme at the yearly time scale and to apply it over the same period and lastly, (3) to derive the FYRE Climate reanalysis, a 25-member ensemble hybrid dataset resulting from the daily and yearly assimilation schemes, spanning the whole 1871&#8211;2012 period at a daily and 8-km resolution over France. Assimilating daily observations only allows reconstructing accurately daily characteristics, but fails in reproducing robust multidecadal variations when compared to independent datasets. Compared to reference homogenized series, FYRE Climate clearly performs better than the SCOPE Climate background in terms of bias, error, and correlation, but also better than the Safran surface reanalysis over France (Vidal et al., 2010) available from 1958 onward only. FYRE Climate also succeeds in reconstructing both local extreme events and multidecadal variability. It is made available from http://doi.org/10.5281/zenodo.4005573 (precipitation) and http://doi.org/10.5281/zenodo.4006472 (temperature). Further details on FYRE Climate can be found in Devers et al. (2021).Caillouet, L., Vidal, J.-P., Sauquet, E., Graff, B., Soubeyroux, J.-M. (2021) SCOPE Climate: a 142-year daily high-resolution ensemble meteorological reconstruction dataset over France. Earth System Science Data, 11, 241-260. https://doi.org/10.5194/essd-11-241-2019Devers, A., Vidal, J.-P., Lauvernet, C., Graff, B., Vannier, O. (2020) A framework for high-resolution meteorological surface reanalysis through offline data assimilation in an ensemble of downscaled reconstructions. Quarterly Journal of the Royal Meteorological Society, 2020, 146, 153-17. https://doi.org/10.1002/qj.3663Devers, A., Vidal, J.-P., Lauvernet, C., Vannier, O. (2021) FYRE Climate: A high-resolution reanalysis of daily precipitation and temperature in France from 1871 to 2012. Climate of the Past Discussions, in review, https://doi.org/10.5194/cp-2020-156Vidal, J.-P., Martin, E., Franchist&#233;guy, L., Baillon, M., Soubeyroux, J.-M. (2010) A 50-year high-resolution atmospheric reanalysis over France with the Safran system. International Journal of Climatology, 30, 1627-1644. https://doi.org/10.1002/joc.2003

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FYRE Climate: A high-resolution reanalysis of daily precipitation and temperature in France from 1871 to 2012

10.5194/cp-2020-156 ◽

2021 ◽

Author(s):

Alexandre Devers ◽

Jean-Philippe Vidal ◽

Claire Lauvernet ◽

Olivier Vannier

Keyword(s):

High Resolution ◽

Extreme Events ◽

Bias Error ◽

High Temporal Resolution ◽

Temperature And Precipitation ◽

Climate Reconstructions ◽

Assimilation Scheme ◽

Surface Observations ◽

Better Than ◽

Local Extreme

Abstract. Surface observations are usually too few and far between to properly assess multidecadal variations at the local scale and characterize historical local extreme events at the same time. A data assimilation scheme has been recently presented to assimilate daily observations of temperature and precipitation into downscaled reconstructions from a global extended reanalysis through an Ensemble Kalman fitting approach and derive high-resolution fields. Recent studies also showed that assimilating observations at high temporal resolution does not guarantee correct multidecadal variations. The current paper thus proposes (1) to apply this scheme over France and over the 1871–2012 period based on the SCOPE Climate reconstructions background dataset and all available daily historical surface observations of temperature and precipitation, (2) to develop an assimilation scheme at the yearly time scale and to apply it over the same period and lastly, (3) to derive the FYRE Climate reanalysis, a 25-member ensemble hybrid dataset resulting from the daily and yearly assimilation schemes, spanning the whole 1871–2012 period at a daily and 8-km resolution over France. Assimilating daily observations only allows reconstructing accurately daily characteristics, but fails in reproducing robust multidecadal variations when compared to independent datasets. Combining the daily and yearly assimilation schemes, FYRE Climate clearly performs better than the SCOPE Climate background in terms of bias, error, and correlation, but also better than the Safran reference surface reanalysis over France available from 1958 onward only. FYRE Climate also succeeds in reconstructing both local extreme events and multidecadal variability. It is made freely available from http://doi.org/10.5281/zenodo.4005573 (precipitation) and http://doi.org/10.5281/zenodo.4006472 (temperature).

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FYRE Climate: a high-resolution reanalysis of daily precipitation and temperature in France from 1871 to 2012

Climate of the Past ◽

10.5194/cp-17-1857-2021 ◽

2021 ◽

Vol 17 (5) ◽

pp. 1857-1879

Author(s):

Alexandre Devers ◽

Jean-Philippe Vidal ◽

Claire Lauvernet ◽

Olivier Vannier

Keyword(s):

High Resolution ◽

Data Assimilation ◽

Extreme Events ◽

High Temporal Resolution ◽

Temperature And Precipitation ◽

Data Assimilation Scheme ◽

Assimilation Scheme ◽

Surface Observations ◽

Better Than ◽

Local Extreme

Abstract. Surface observations are usually too few and far between to properly assess multidecadal variations at the local scale and characterize historical local extreme events at the same time. A data assimilation scheme has been recently presented to assimilate daily observations of temperature and precipitation into downscaled reconstructions from a global extended reanalysis through an Ensemble Kalman fitting approach and to derive high-resolution fields. Recent studies also showed that assimilating observations at high temporal resolution does not guarantee correct multidecadal variations. The current paper thus proposes (1) to apply the data assimilation scheme over France and over the 1871–2012 period based on the SCOPE Climate reconstructions background dataset and all available daily historical surface observations of temperature and precipitation, (2) to develop an assimilation scheme at the yearly timescale and to apply it over the same period and lastly, (3) to derive the FYRE Climate reanalysis, a 25-member ensemble hybrid dataset resulting from the daily and yearly assimilation schemes, spanning the whole 1871–2012 period at a daily and 8 km resolution over France. Assimilating daily observations only allows reconstructing accurately daily characteristics, but fails in reproducing robust multidecadal variations when compared to independent datasets. Combining the daily and yearly assimilation schemes, FYRE Climate clearly performs better than the SCOPE Climate background in terms of bias, error, and correlation, but also better than the Safran reference surface reanalysis over France available from 1958 onward only. FYRE Climate also succeeds in reconstructing both local extreme events and multidecadal variability. It is freely available at https://doi.org/10.5281/zenodo.4005573 (precipitation, Devers et al., 2020b) and https://doi.org/10.5281/zenodo.4006472 (temperature, Devers et al., 2020c).

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Extreme Events Representation in CMCC-CM2 High and Very-High Resolution General Circulation Models

10.5194/gmd-2021-294 ◽

2021 ◽

Author(s):

Enrico Scoccimarro ◽

Daniele Peano ◽

Silvio Gualdi ◽

Alessio Bellucci ◽

Tomas Lovato ◽

...

Keyword(s):

High Resolution ◽

Extreme Events ◽

General Circulation ◽

Climate Models ◽

General Circulation Models ◽

Horizontal Resolution ◽

Historical Period ◽

Climate Modelling ◽

Temperature And Precipitation ◽

Very High

Abstract. The recent advancements in climate modelling partially build on the improvement of horizontal resolution in different components of the simulating system. A higher resolution is expected to provide a better representation of the climate variability, and in this work we are particularly interested in the potential improvements in representing extreme events of high temperature and precipitation. The two versions of the CMCC-CM2 model used here, adopt the highest horizontal resolutions available within the last family of the global coupled climate models de¬veloped at CMCC to participate in the CMIP6 effort. The main aim of this study is to document the ability of the CMCC-CM2 models in representing the spatial distribution of extreme events of temperature and precipitation, under the historical period, comparing model results to observations (ERA5 Reanalysis and CHIRPS observations). For a more detailed evaluation we investigate both 6 hourly and daily time series for the definition of the extreme conditions. In terms of mean climate, the two models are able to realistically reproduce the main patterns of temperature and precipitation. The very-high resolution version (¼ degree horizontal resolution) of the atmospheric model provides better results than the high resolution one (one degree), not only in terms of means but also in terms of extreme events of temperature defined at daily and 6-hourly frequency. This is also the case of average precipitation. On the other hand the extreme precipitation is not improved by the adoption of a higher horizontal resolution.

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Validating the French hYdrometeorological REanalysis (FYRE) with documentary evidence

10.5194/egusphere-egu2020-8394 ◽

2020 ◽

Author(s):

Jean-Philippe Vidal ◽

Alexandre Devers ◽

Claire Lauvernet ◽

Olivier Vannier ◽

Laurie Caillouet ◽

...

Keyword(s):

High Resolution ◽

Data Assimilation ◽

Ensemble Kalman Filter ◽

Low Flow ◽

Documentary Evidence ◽

Science Data ◽

Temperature And Precipitation ◽

Extreme Hydrological Events ◽

Streamflow Reconstructions

The recently developed French hYdrometerological Reanalysis (FYRE) covers the period 1871-2012 and provide high-resolution ensemble reconstructions of both climate and hydrology over France. FYRE Climate combines a statistical downscaling of the global Twentieth Century reanalysis (Caillouet et al., 2019) with in-situ station observations through Ensemble Kalman filter (EnKF) data assimilation (Devers et al., 2020). FYRE Climate is composed of 25 members of daily temperature and precipitation fields on a 8~km grid over France. It served as forcings for a conceptual hydrological model over 661 near-natural catchments to build streamflow reconstructions spanning 142 years. These reconstructions have then been combined with historical streamflow observations, again through EnKF data assimilation, to build the FYRE Hydro 25-member daily hydrological reanalysis over the 661 catchments.FYRE Hydro is here validated with various types of documentary evidence (poem, complaint letter, and photograph), focusing on extreme low-flow events and their spatial and temporal fingerprint. They serve as examples of naturally extreme hydrological events that are exacerbated through human interventions, the magnitude of which has yet to be consistently quantified over the course of the Anthropocene.&#160;ReferencesCaillouet, L., Vidal, J.-P., Sauquet, E., Graff, B., Soubeyroux, J.-M. (2019) SCOPE Climate: a 142-year daily high-resolution ensemble meteorological reconstruction dataset over France. Earth System Science Data, 11, 241-260. https://doi.org./10.5194/essd-11-241-2019Devers, A., Vidal, J.-P., Lauvernet, C., Graff, B., Vannier, O. (2020) A framework for high-resolution meteorological surface reanalysis through offline data assimilation in an ensemble of downscaled reconstructions. Quarterly Journal of the Royal Meteorological Society. https://doi.org./10.1002/qj.3663

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Assessing the Impact of the Assimilation of SWOT Observations in a Global High-Resolution Analysis and Forecasting System Part 1: Methods

Frontiers in Marine Science ◽

10.3389/fmars.2021.691955 ◽

2021 ◽

Vol 8 ◽

Author(s):

Mounir Benkiran ◽

Giovanni Ruggiero ◽

Eric Greiner ◽

Pierre-Yves Le Traon ◽

Elisabeth Rémy ◽

...

Keyword(s):

High Resolution ◽

Data Assimilation ◽

Companion Paper ◽

Ocean Model ◽

Data Assimilation Scheme ◽

High Resolution Analysis ◽

Resolution Analysis ◽

Forecasting System ◽

The Impact ◽

Assimilation Scheme

The future Surface Water Ocean Topography (SWOT) mission due to be launched in 2022 will extend the capability of existing nadir altimeters to enable two-dimensional mapping at a much higher effective resolution. A significant challenge will be to assimilate this kind of data in high-resolution models. In this context, Observing System Simulation Experiments (OSSEs) have been performed to assess the impact of SWOT on the Mercator Ocean and Copernicus Marine Environment Monitoring Service (CMEMS) global, high-resolution analysis and forecasting system. This paper focusses on the design of these OSSEs, in terms of simulated observations and assimilation systems (ocean model and data assimilation schemes). The main results are discussed in a companion paper. Two main updates of the current Mercator Ocean data assimilation scheme have been made to improve the assimilation of information from SWOT data. The first one is related to a different parametrisation of the model error covariance, and the second to the use of a four-dimensional (4D) version of the data assimilation scheme. These improvements are described in detail and their contribution is quantified. The Nature Run (NR) used to represent the “truth ocean” is validated by comparing it with altimeter observations, and is then used to simulate pseudo-observations required for the OSSEs. Finally, the design of the OSSEs is evaluated by ensuring that the differences between the assimilation system and the NR are statistically consistent with the misfits between real ocean observations and real-time operational systems.

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Effects of Spectral Nudging in WRF on Arctic Temperature and Precipitation Simulations

Journal of Climate ◽

10.1175/jcli-d-12-00318.1 ◽

2013 ◽

Vol 26 (12) ◽

pp. 3985-3999 ◽

Cited By ~ 42

Author(s):

Justin M. Glisan ◽

William J. Gutowski ◽

John J. Cassano ◽

Matthew E. Higgins

Keyword(s):

Extreme Events ◽

Large Scale ◽

Warm Season ◽

Cold Season ◽

Weather Research And Forecasting ◽

Spectral Nudging ◽

Temperature And Precipitation ◽

Climate Simulations ◽

Arctic Temperature ◽

Better Than

Abstract Spectral (interior) nudging is a way of constraining a model to be more consistent with observed behavior. However, such control over model behavior raises concerns over how much nudging may affect unforced variability and extremes. Strong nudging may reduce or filter out extreme events since nudging pushes the model toward a relatively smooth, large-scale state. The question then becomes: what is the minimum spectral nudging needed to correct biases while not limiting the simulation of extreme events? To determine this, case studies were performed using a six-member ensemble of the Pan-Arctic Weather Research and Forecasting model (WRF) with varying spectral nudging strength, using WRF’s standard nudging as a reference point. Two periods were simulated, one in a cold season (January 2007) and one in a warm season (July 2007). Precipitation and 2-m temperature were analyzed to determine how changing spectral nudging strength impacts temperature and precipitation extremes and selected percentiles. Results suggest that there is a marked lack of sensitivity to varying degrees of nudging. Moreover, given that nudging is an artificial forcing applied in the model, an outcome of this work is that nudging strength can be considerably smaller than the WRF standard strength and still produce climate simulations that are much better than using no nudging.

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