skip to main content

Search for: All records

Creators/Authors contains: "Burke, Eleanor"

Note: When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher. Some full text articles may not yet be available without a charge during the embargo (administrative interval).
What is a DOI Number?

Some links on this page may take you to non-federal websites. Their policies may differ from this site.

  1. Abstract. Peatlands have often been neglected in Earth system models (ESMs).Where they are included, they are usually represented via a separate, prescribed grid cell fraction that is given the physical characteristics of a peat (highly organic) soil. However, in reality soils vary on a spectrum between purely mineral soil (no organic material) and purely organicsoil, typically with an organic layer of variable thickness overlying mineral soil below. They are also dynamic, with organic layer thickness and its properties changing over time. Neither the spectrumof soil types nor their dynamic nature can be captured by current ESMs. Here we present a new version of an ESM land surface scheme (Joint UK Land Environment Simulator, JULES) where soil organic matter accumulation – and thus peatland formation, degradation and stability – is integratedin the vertically resolved soil carbon scheme. We also introduce the capacity to track soil carbon age as a function of depth in JULES and compare this to measured peat age–depth profiles. The new scheme is tested and evaluated at northern and temperate sites. This scheme simulates dynamic feedbacks between the soil organic material and its thermal and hydraulic characteristics. We show that draining the peatlands can lead to significant carbonmore »loss, soil compaction and changes in peat properties. However, negative feedbacks can lead to the potential for peatlands to rewet themselves following drainage.These ecohydrological feedbacks can also lead to peatlands maintaining themselves in climates where peat formation would not otherwise initiate in the model, i.e. displaying some degree of resilience. The new model produces similar results to the original model for mineral soils and realistic profiles of soil organic carbon for peatlands.We evaluate the model against typical peat profiles based on 216 northern and temperate sites from a global dataset of peat cores.The root-mean-squared error (RMSE) in the soil carbon profile is reduced by 35 %–80 % in the best-performing JULES-Peat simulationscompared with the standard JULES configuration. The RMSE in these JULES-Peat simulations is 7.7–16.7 kg C m−3 depending on climate zone, which is considerably smaller than the soil carbon itself (around 30–60 kg C m−3). The RMSE at mineral soil sites is also reducedin JULES-Peat compared with the original JULES configuration (reduced by ∼ 30 %–50 %). Thus, JULES-Peat can be used as a complete scheme that simulates both organic and mineral soils. It does not requireany additional input data and introduces minimal additional variables to the model. This provides a new approach for improving the simulation of organic and peatland soils andassociated carbon-cycle feedbacks in ESMs.« less
    Free, publicly-accessible full text available January 1, 2023
  2. Abstract. This study investigates and compares soil moisture andhydrology projections of broadly used land models with permafrost processesand highlights the causes and impacts of permafrost zone soil moistureprojections. Climate models project warmer temperatures and increases inprecipitation (P) which will intensify evapotranspiration (ET) and runoff inland models. However, this study shows that most models project a long-termdrying of the surface soil (0–20 cm) for the permafrost region despiteincreases in the net air–surface water flux (P-ET). Drying is generallyexplained by infiltration of moisture to deeper soil layers as the activelayer deepens or permafrost thaws completely. Although most models agree ondrying, the projections vary strongly in magnitude and spatial pattern.Land models tend to agree with decadal runoff trends but underestimaterunoff volume when compared to gauge data across the major Arctic riverbasins, potentially indicating model structural limitations. Coordinatedefforts to address the ongoing challenges presented in this study will helpreduce uncertainty in our capability to predict the future Arctichydrological state and associated land–atmosphere biogeochemical processesacross spatial and temporal scales.