To fill the gap in the observation system for humidity, the HIRLAM–ALADIN Research on Mesoscale Operational NWP in Euromed (HARMONIE) limited-area high-resolution kilometer-scale model has been prepared for assimilation of Global Navigation Satellite System (GNSS) zenith total delay (ZTD) observations. The observation-processing system includes data selection, bias correction, quality control, and a GNSS observation operator for data assimilation. A large part of the bias between observations and model equivalents comes from the relatively low model top used in the HARMONIE experiments. The functionality of the different observation-processing components was investigated in detail as was the overall performance of the GNSS ZTD data assimilation. This paper contains an extensive description of the GNSS ZTD observation-processing system and a comparison of a newly introduced variational bias correction for GNSS ZTD data with an alternative static bias correction, as well as a detailed analysis of the impact of GNSS ZTD data, both in terms of statistical evaluations over a longer period and in terms of individual case studies. Assimilation of the GNSS ZTD observations with a variational bias correction has improved the quality of short-range weather forecasts for the moisture-related parameters in particular, both in a statistical sense and in individual case studies. The paper also discusses further improvements in the HARMONIE variational data-assimilation system that are needed to fully utilize the potential of high-resolution GNSS ZTD observations.

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En Junio de 2016, HARMONIE- AROME sustituyó a HIRLAM como modelo operativo de área limitada de AEMET. Se integra con una resolución horizontal de 2.5 km. Un componente esencial del modelo es la asimilación de datos donde se usan observaciones convencionales y nuevas fuentes de observaciones como GNSS y ATOVS (Figura 1). Se utiliza el esquema 3DVAR , que es una esquema variacional de asimilación de datos, con ciclos de asimilación cada 3 horas.En este trabajo se describen las principales componentes del esquema, así como su importancia dentro del modelo y el impacto de las diferentes tipos de observaciones.