Synthesis and evaluation of historical meridional heat transport from midlatitudes towards the Arctic

Liu, Yang; Attema, Jisk; Moat, Ben; Hazeleger, Wilco

doi:10.5194/esd-11-77-2020

Cited by 10 publications

(16 citation statements)

References 89 publications

(145 reference statements)

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“…The JRA55 data is an atmosphere reanalysis product which includes quantities such as humidity, pressure and temperature [34]. Recently, these quantities were used to determine the total meridional energy transport and latent heat, measures important to understand the global climate [35]. As an example of our reduction techniques for matrix products, we are using a Mercator projection of the energy transport and latent heat, recorded monthly from 1979 to 2015.…”

Section: Case Study Of a Product Svd Of Square Matricesmentioning

confidence: 99%

Dataset Reduction Techniques to Speed Up SVD Analyses on Big Geo-Datasets

Bogaardt

Gonçalves

Zurita-Milla

et al. 2019

IJGI

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The Singular Value Decomposition (SVD) is a mathematical procedure with multiple applications in the geosciences. For instance, it is used in dimensionality reduction and as a support operator for various analytical tasks applicable to spatio-temporal data. Performing SVD analyses on large datasets, however, can be computationally costly, time consuming, and sometimes practically infeasible. However, techniques exist to arrive at the same output, or at a close approximation, which requires far less effort. This article examines several such techniques in relation to the inherent scale of the structure within the data. When the values of a dataset vary slowly, e.g., in a spatial field of temperature over a country, there is autocorrelation and the field contains large scale structure. Datasets do not need a high resolution to describe such fields and their analysis can benefit from alternative SVD techniques based on rank deficiency, coarsening, or matrix factorization approaches. We use both simulated Gaussian Random Fields with various levels of autocorrelation and real-world geospatial datasets to illustrate our study while examining the accuracy of various SVD techniques. As the main result, this article provides researchers with a decision tree indicating which technique to use when and predicting the resulting level of accuracy based on the dataset's structure scale.

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Section: Case Study Of a Product Svd Of Square Matricesmentioning

confidence: 99%

Dataset Reduction Techniques to Speed Up SVD Analyses on Big Geo-Datasets

Bogaardt

Gonçalves

Zurita-Milla

et al. 2019

IJGI

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“…It can be noticed that ORAS4 resembles SODA3 but differs much from GLORYS2V3. It was explained in our previous work that the first 10 years in GLORYS2V3 are not reliable [Liu et al, 2020b]. Given the absolute value of OMET anomalies (∼ 0.01P W ), the standard deviations of OMET anomalies (∼ 0.01P W ) from these three oceanic reanalyses are large.…”

Section: Meridional Energy Transportmentioning

confidence: 79%

“…Note that the calculation suffers from mass imbalance reported by previous studies [e.g. Trenberth, 1991, Graversen, 2006, Liu et al, 2020b. We have examined the mass budget correction methods in a previous paper [Liu et al, 2020b].…”

Section: Energy Transport In the Atmosphere And Eddy Decompositionmentioning

confidence: 99%

“…Trenberth, 1991, Graversen, 2006, Liu et al, 2020b. We have examined the mass budget correction methods in a previous paper [Liu et al, 2020b]. In general, barotropic mass correction is the most practical method used by many studies to calculate mass residuals [Trenberth, 1991, Graversen, 2006, Mayer and Haimberger, 2012, Liu et al, 2020b.…”

Section: Energy Transport In the Atmosphere And Eddy Decompositionmentioning

confidence: 99%

“…This could be due to the difference in the model's capability of representing mesoscale eddies in the Gulf Streams among the chosen oceanic reanalyses. We have explored this in our previous work [Liu et al, 2020b]. Both GLORYS2V3 and SODA3 have a high spatial resolution, employ eddy-permitting models, and simulate the large scale eddy variability, but this is not the case for ORAS4 [Ferry et al, 2012b,a, Balmaseda et al, 2013.…”

Section: Meridional Energy Transportmentioning

confidence: 99%

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Arctic weather and climate: from mechanisms to forecasts

Liu

Self Cite

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Since the mid-20th Century, the Arctic is warming about two times faster than the rest of the world. This is widely known as Arctic Amplification (AA) and has drawn lots of attention recently. Apart from a dominant impact on the local weather and climate, its influence has been extended beyond the polar region through significant modification on the circulation in both the atmosphere and ocean. In order to identify the drivers of Arctic climate change and the connections between the Arctic and global climate system, it is important to understand the Arctic weather and climate. ix forecast and is promising to enhance weather forecasting capabilities at short to medium-range timescales.Finally, a synthesis of this thesis and an outlook for suggested future research are shown in chapter 6.

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Impacts of multi‐timescale circulations on meridional heat transport

Liu

Zhou

2021

Intl Journal of Climatology

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Relative contributions to the zonal mean meridional heat transport by the climatological annual mean, climatological annual variation, synoptic, intra‐seasonal and lower‐frequency motions were examined based on the ERA‐Interim reanalysis data for the period of 1981–2015. The meridional heat transport analysed in this study only includes the component related to meridional wind and temperature. In the tropics, the climatological annual mean circulations dominate the long‐term mean meridional heat transport, while the interaction between the climatological annual mean temperature and the seasonal anomalous flow largely contributes to the seasonal variation of the meridional heat transport. In the middle latitudes, the climatological annual mean circulations and transient eddies (mostly synoptic and intra‐seasonal eddies) are of roughly equal importance in the poleward heat transport, leading to the maximum poleward heat transport around 50°N/S. The upper‐ and lower‐tropospheric heat transports by the climatological annual mean circulations appear opposite, with the magnitude of the lower‐tropospheric transport being greater. The preferred maximum zonal mean heat transport at 50°N by the climatological mean flow is attributed to the maximum zonal mean low‐level southerly in situ. The preferred peak latitude of the mid‐latitude poleward heat transport by synoptic eddies near 50°N arises from the combined effect of the strong synoptic‐scale meridional wind and temperature variabilities in situ and their in‐phase relationship. The heat transport by tropical cyclones (TCs) was estimated by applying a statistical relationship between TC intensity and the vertically integrated temperature averaged over the TC core region derived from high‐resolution Weather Research and Forecasting (WRF) model simulations. For northern hemisphere summer, TCs contribute about 35% of the total heat transport in the active TC regions, suggesting that TCs play a critical role in the regional meridional heat transport.

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Synthesis and evaluation of historical meridional heat transport from midlatitudes towards the Arctic

Cited by 10 publications

References 89 publications

Dataset Reduction Techniques to Speed Up SVD Analyses on Big Geo-Datasets

Dataset Reduction Techniques to Speed Up SVD Analyses on Big Geo-Datasets

Arctic weather and climate: from mechanisms to forecasts

Impacts of multi‐timescale circulations on meridional heat transport

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