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91探花
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Dr Beena Balan Sarojini

Post-doctoral Researcher

Research theme

  • Climate physics

Sub department

  • Atmospheric, Oceanic and Planetary Physics

Research groups

  • Predictability of weather and climate
beena.balansarojini@physics.ox.ac.uk
Robert Hooke Building, room S40
  • About
  • Publications

Tropical cyclone-induced cold wakes in the northeast Indian Ocean

Environmental Science Atmospheres Royal Society of Chemistry (RSC) 2:3 (2022) 404-415

Authors:

J Kuttippurath, RS Akhila, MV Martin, MS Girishkumar, M Mohapatra, B Balan Sarojini, K Mogensen, N Sunanda, A Chakraborty

Seasonal Arctic sea ice forecasting with probabilistic deep learning

Nature Communications Springer Nature 12:1 (2021) 5124

Authors:

Tom R Andersson, J Scott Hosking, Mar铆a P茅rez-Ortiz, Brooks Paige, Andrew Elliott, Chris Russell, Stephen Law, Daniel C Jones, Jeremy Wilkinson, Tony Phillips, James Byrne, Steffen Tietsche, Beena Balan Sarojini, Eduardo Blanchard-Wrigglesworth, Yevgeny Aksenov, Rod Downie, Emily Shuckburgh

On the Treatment of Soil Water Stress in GCM Simulations of Vegetation Physiology

Frontiers in Environmental Science Frontiers 9 (2021) 689301

Authors:

PL Vidale, G Egea, PC McGuire, M Todt, W Peters, O M眉ller, B Balan-Sarojini, A Verhoef

A daily to seasonal Arctic sea ice forecasting AI

Copernicus Publications (2021)

Authors:

Tom R Andersson, J Scott Hosking, Eleanor Krige, Maria P茅rez-Ortiz, Brooks Paige, Andrew Elliott, Chris Russell, Stephen Law, Daniel C Jones, Jeremy Wilkinson, Tony Phillips, Steffen Tietsche, Beena Balan Sarojini, Ed Blanchard-Wrigglesworth, Yevgeny Aksenov, Rod Downie

Capability of the variogram to quantify the spatial patterns of surface fluxes and soil moisture simulated by land surface models

Progress in Physical Geography SAGE Publications 45:2 (2021) 279-293

Authors:

S Garrigues, A Verhoef, E Blyth, A Wright, B Balan-Sarojini, El Robinson, S Dadson, A Boone, S Boussetta, G Balsamo

Abstract:

Up to now, relatively little effort has been dedicated to the quantitative assessment of the differences in spatial patterns of model outputs. In this paper, we employed a variogram-based methodology to quantify the differences in the spatial patterns of root-zone soil moisture, net radiation, and latent and sensible heat fluxes simulated by three land surface models (SURFEX/ISBA, JULES and CHTESSEL) over three European geographic domains – namely, UK, France and Spain. The model output spatial patterns were quantified through two metrics derived from the variogram: i) the variogram sill, which quantifies the degree of spatial variability of the data; and ii) the variogram integral range, which represents the spatial length scale of the data. The higher seasonal variation of the spatial variability of sensible and latent heat fluxes over France and Spain, compared to the UK, is related to a more frequent occurrence of a soil-moisture-limited evapotranspiration regime during summer dry spells in the south of France and Spain. The small differences in spatial variability of net radiation between models indicate that the spatial patterns of net radiation are mostly driven by the climate forcing data set. However, the models exhibit larger differences in latent and sensible heat flux spatial variabilities, which are related to their differences in i) soil and vegetation ancillary datasets and ii) physical process representation. The highest discrepancies in spatial patterns between models are observed for soil moisture, which is mainly related to the type of soil hydraulic function implemented in the models. This work demonstrates the capability of the variogram to enhance our understanding of the spatiotemporal structure of the uncertainties in land surface model outputs. Therefore, we strongly encourage the implementation of the variogram metrics in model intercomparison exercises.

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