Singular-Vector Perturbation Growth in a Primitive Equation Model with Moist Physics

To investigate the potential impact of various types of data on weather forecast over the Indian region, a set of data-denial experiments spanning the entire month of July 2012 is executed using the Weather Research and Forecasting (WRF) model and its three-dimensional variational (3DVAR) data assimilation system. The experiments are designed to allow the assessment of mass versus wind observations and terrestrial versus space-based instruments, to evaluate the relative importance of the classes of conventional instrument such as radiosonde, and finally to investigate the role of individual spaceborne instruments. The moist total energy norm is used for validation and forecast skill assessment. The results show that the contribution of wind observations toward error reduction is larger than mass observations in the short range (48 h) forecast. Terrestrial-based observations generally contribute more than space-based observations except for the moisture fields, where the role of the space-based instruments becomes more prevalent. Only about 50% of individual instruments are found to be beneficial in this experiment configuration, with the most important role played by radiosondes. Thereafter, Meteosat Atmospheric Motion Vectors (AMVs) (only for short range forecast) and Special Sensor Microwave Imager (SSM/I) are second and third, followed by surface observations, Sounder for Probing Vertical Profiles of Humidity (SAPHIR) radiances and pilot observations. Results of the additional experiments of comparative performance of SSM/I total precipitable water (TPW), Microwave Humidity Sounder (MHS), and SAPHIR radiances indicate that SSM/I is the most important instrument followed by SAPHIR and MHS for improving the quality of the forecast over the Indian region. Further, the impact of single SAPHIR instrument (onboard Megha-Tropiques) is significantly larger compared to three MHS instruments (onboard NOAA-18/19 and MetOp-A).

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“…The impact is evaluated using the moist total energy norm (equation (1)) described in Ehrendorfer et al [1999].…”

Section: Impact Evaluationmentioning

confidence: 99%

Impact of various observing systems on weather analysis and forecast over the Indian region

et al. 2014

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“…In this study, the dry total-energy norm (e.g. Ehrendorfer et al, 1999) is used at initial and final time: thus, humidity perturbations are not taken into account. The tangent linear model and its adjoint employ the same linearized physics as used by Mahfouf (1999), comprising vertical diffusion, large-scale condensation, long-wave radiation, deep-cumulus convection, and subgrid-scale orographic effects.…”

Section: Adjoint Sensitivity Of Forecast Error To Initial Conditionsmentioning

confidence: 99%

Performance of the ECMWF forecasting system in the Arctic during winter

Jung

Leutbecher

2007

Quart J Royal Meteoro Soc

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ABSTRACT:The performance of the ECMWF forecasting system in the Arctic during boreal winter is investigated. A comparison between different analysis products suggests that synoptic-scale features in the Arctic are relatively well represented by state-of-the-art analysis systems. Furthermore, it is shown that the improvement in deterministic forecast error in the Arctic since the early 1980s closely follows that reported in previous studies for the Northern Hemisphere as a whole. One of the biggest 'jumps' in deterministic forecast skill, both in the troposphere and in the stratosphere, occurred in autumn 2000 when the high-resolution deterministic system (T L 511, about 40 km) was introduced at ECMWF. Our results suggest that 10-day forecasts of the stratospheric circulation have been very skilful, particularly since the introduction of the high-resolution system. Adjoint computations reveal pronounced flow-dependence of the sensitivity of short-range forecast error to initial perturbations at high northern latitudes (north of 70°N); this highlights the importance of using ensemble prediction systems (EPSs) for weather forecasting in the Arctic. Verification of the ECMWF EPS in the Arctic reveals substantial improvements in probabilistic predictive skill since the mid-1990s. The most pronounced increase in probabilistic forecast skill, particularly on synoptic scales, occurred in autumn 2000 when the high-resolution EPS (T L 255, about 80 km) was introduced. Finally, it is shown that the observed stratosphere-troposphere link ('downward propagation' of stratospheric anomalies), which constitutes a potential source of extended-range predictability in high latitudes, is realistically represented in seasonal integrations with the ECMWF model -even at the relatively low horizontal resolution of T L 95 (about 180 km).

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“…The EFSO can be computed based on different error norms. In this study, we use both a dry total energy norm and a moist total energy norm (Ehrendorfer et al, 1999). The generic moist total energy norm is defined as…”

Section: Efso Formulationmentioning

confidence: 99%

Accelerating assimilation development for new observing systems using EFSO

Lien

Hotta

Kalnay

et al. 2018

Nonlin. Processes Geophys.

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Abstract. To successfully assimilate data from a new observing system, it is necessary to develop appropriate data selection strategies, assimilating only the generally useful data. This development work is usually done by trial and error using observing system experiments (OSEs), which are very time and resource consuming. This study proposes a new, efficient methodology to accelerate the development using ensemble forecast sensitivity to observations (EFSO). First, non-cycled assimilation of the new observation data is conducted to compute EFSO diagnostics for each observation within a large sample. Second, the average EFSO conditionally sampled in terms of various factors is computed. Third, potential data selection criteria are designed based on the non-cycled EFSO statistics, and tested in cycled OSEs to verify the actual assimilation impact. The usefulness of this method is demonstrated with the assimilation of satellite precipitation data. It is shown that the EFSO-based method can efficiently suggest data selection criteria that significantly improve the assimilation results.

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Singular-Vector Perturbation Growth in a Primitive Equation Model with Moist Physics

Cited by 142 publications

References 41 publications

Impact of various observing systems on weather analysis and forecast over the Indian region

Impact of various observing systems on weather analysis and forecast over the Indian region

Performance of the ECMWF forecasting system in the Arctic during winter

Accelerating assimilation development for new observing systems using EFSO

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