The Value of Surface-based Meteorological Observation Data

Kull, Daniel Werner; Riishøjgaard, Lars Peter; Eyre, J. R.; Varley, Robert

doi:10.1596/35178

Cited by 9 publications

(11 citation statements)

References 21 publications

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“…Furthermore, we use a global dataset of radiosondes and a global dataset of drifting sea buoys (see Methods). We choose these three types of in-situ, surface-based meteorological observations because of their relative importance for forecast accuracy (Kull et al, 2021). From all three datasets, we extract the locations as well as the frequencies of observations between 2011 and 2020.…”

Section: Resultsmentioning

confidence: 99%

Global inequalities in weather forecasts

Linsenmeier,

Shrader

2023

Preprint

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Global weather forecasts are of great economic value for society, but geographical differences in forecast accuracy can create new - and potentially exacerbate existing - economic inequalities. Regional differences in forecast accuracy are particularly relevant if weather forecasts are considered as an important tool to help reduce the negative effects of future climate change such as mortality from extreme temperature events. In this paper, we provide a comprehensive global analysis of the accuracy of short-term numerical weather predictions of temperature and relate our findings to both existing economic inequalities and inequities in global weather monitoring infrastructure. We report three main results: First, temperature forecasts are currently substantially more accurate in high income countries than in low income countries. A seven-day-ahead forecast in a high-income country is on average more accurate than a one-day-ahead forecast in a low income country. Second, while forecast accuracy has improved steadily between 1985 and the present - with the largest increases in the 1990s - there is a persistent gap between high income and low income countries. Third, the infrastructure for weather observations is highly unequally distributed across countries, with fewer land-based weather stations and radiosondes in poorer countries. These inequalities grow even larger when lower reporting rates are taken into account. Remedying these differences in infrastructure would help close the forecast accuracy gap.

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Section: Resultsmentioning

confidence: 99%

Global inequalities in weather forecasts

Linsenmeier,

Shrader

2023

Preprint

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“…The continuous development of Earth system modeling frameworks for weather forecasting has enabled remarkable increases in predictive ability with major social and economic consequences (Kull et al, 2021). This forecast skill is often attributed to a combination of improved model accuracy and observation utilization (Kalnay, 2002).…”

Section: Introductionmentioning

confidence: 99%

Ensemble-Based Data Assimilation of Significant Wave Height from Sofar Spotters and Satellite Altimeters with a Global Operational Wave Model

Houghton¹,

Penny

Hegermiller

et al. 2023

Preprint

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An ensemble-based method for wave data assimilation is implemented using significant wave height observations from the globally distributed network of Sofar Spotter buoys and satellite altimeters. The Local Ensemble Transform Kalman Filter (LETKF) method generates skillful analysis fields resulting in reduced forecast errors out to 2.5 days when used as initial conditions in a cycled wave data assimilation system. The LETKF method provides more physically realistic model state updates that better reflect the underlying sea state dynamics and uncertainty compared to methods such as optimal interpolation. Skill assessment far from any included observations and inspection of specific storm events highlight the advantages of LETKF over an optimal interpolation method for data assimilation. This advancement has immediate value in improving predictions of the sea state and, more broadly, enabling future coupled data assimilation and utilization of global surface observations across domains (atmosphere-wave-ocean).

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“…Monitoring of precipitation in the territory is gaining a paramount importance in many fields of applications, including public safety, business-oriented services (e.g., agriculture), and personal services (e.g., leisure activities) [1]. As an example, accurate precipitation maps allow the agricultural sector to make strategic decisions to improve the quality of production and manage risks [2].…”

Section: Introductionmentioning

confidence: 99%

A Feasibility Study on Opportunistic Rainfall Measurement From Satellite TV Broadcasts

Sapienza¹,

Bacci²,

Giannetti³

et al. 2023

RSL

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Rainfall precipitation maps are usually derived based on the measurements collected by classical weather devices, such as rain gauges and weather stations. This article aims to show the benefits obtained by opportunistic rainfall measurements based on signal strength measurements provided by commercial-grade satellite terminals (e.g., used in TV broadcasting). To assess not only the feasibility of this approach, with significant advantages in terms of capital and operational expenditure, but also improvements in terms of accuracy, we focus on a case study for agricultural applications using a Gaussian-modeled synthetic rain over a specific, real-world test area.

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The Value of Surface-based Meteorological Observation Data

Cited by 9 publications

References 21 publications

Global inequalities in weather forecasts

Global inequalities in weather forecasts

Ensemble-Based Data Assimilation of Significant Wave Height from Sofar Spotters and Satellite Altimeters with a Global Operational Wave Model

A Feasibility Study on Opportunistic Rainfall Measurement From Satellite TV Broadcasts

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