Editorial Type:
Article
Article Type:
Research Article

Improving the Representation of Low Clouds and Drizzle in the ECMWF Model Based on ARM Observations from the Azores

Maike Ahlgrimm European Centre for Medium-Range Weather Forecasts, Reading, United Kingdom

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Richard Forbes European Centre for Medium-Range Weather Forecasts, Reading, United Kingdom

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Print Publication:
01 Feb 2014
DOI:
https://doi.org/10.1175/MWR-D-13-00153.1
Page(s):
668–685
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Abstract

In this study, the representation of marine boundary layer clouds is investigated in the ECMWF model using observations from the Atmospheric Radiation Measurement (ARM) mobile facility deployment to Graciosa Island in the North Atlantic. Systematic errors in the occurrence of clouds, liquid water path, precipitation, and surface radiation are assessed in the operational model for a 19-month-long period. Boundary layer clouds were the most frequently observed cloud type but were underestimated by 10% in the model. Systematic but partially compensating surface radiation errors exist and can be linked to opposing cloud cover and liquid water path errors in broken (shallow cumulus) and overcast (stratocumulus) low-cloud regimes, consistent with previously reported results from the continental ARM Southern Great Plains (SGP) site. Occurrence of precipitation is overestimated by a factor of 1.5 at cloud base and by a factor of 2 at the surface, suggesting deficiencies in both the warm-rain formation and subcloud evaporation parameterizations. A single-column version of the ECMWF model is used to test combined changes to the parameterizations of boundary layer, autoconversion/accretion, and rain evaporation processes at Graciosa. Low-cloud occurrence, liquid water path, radiation biases, and precipitation occurrence are all significantly improved when compared to the ARM observations. Initial results from the modified parameterizations in the full model show improvement in the global top-of-the-atmosphere shortwave radiation, suggesting the reduced errors in the comparison at Graciosa are more widely applicable to boundary layer cloud around the globe.

Corresponding author address: Maike Ahlgrimm, European Centre for Medium-Range Weather Forecasts, Shinfield Park, Reading RG2 9AX, United Kingdom. E-mail: maike.ahlgrimm@ecmwf.int

Abstract

In this study, the representation of marine boundary layer clouds is investigated in the ECMWF model using observations from the Atmospheric Radiation Measurement (ARM) mobile facility deployment to Graciosa Island in the North Atlantic. Systematic errors in the occurrence of clouds, liquid water path, precipitation, and surface radiation are assessed in the operational model for a 19-month-long period. Boundary layer clouds were the most frequently observed cloud type but were underestimated by 10% in the model. Systematic but partially compensating surface radiation errors exist and can be linked to opposing cloud cover and liquid water path errors in broken (shallow cumulus) and overcast (stratocumulus) low-cloud regimes, consistent with previously reported results from the continental ARM Southern Great Plains (SGP) site. Occurrence of precipitation is overestimated by a factor of 1.5 at cloud base and by a factor of 2 at the surface, suggesting deficiencies in both the warm-rain formation and subcloud evaporation parameterizations. A single-column version of the ECMWF model is used to test combined changes to the parameterizations of boundary layer, autoconversion/accretion, and rain evaporation processes at Graciosa. Low-cloud occurrence, liquid water path, radiation biases, and precipitation occurrence are all significantly improved when compared to the ARM observations. Initial results from the modified parameterizations in the full model show improvement in the global top-of-the-atmosphere shortwave radiation, suggesting the reduced errors in the comparison at Graciosa are more widely applicable to boundary layer cloud around the globe.

Corresponding author address: Maike Ahlgrimm, European Centre for Medium-Range Weather Forecasts, Shinfield Park, Reading RG2 9AX, United Kingdom. E-mail: maike.ahlgrimm@ecmwf.int
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