Search

Non-technical summary Greenhouse gas emissions and land use change - from deforestation, forest degradation, and agricultural intensification - are contributing to climate change and biodiversity loss. Important land-based strategies such as planting trees or growing bioenergy crops (with carbon capture and storage) are needed to achieve the goals of the Paris Climate Agreement and to enhance biodiversity. The integrated Land Ecosystems Atmospheric Processes Study (iLEAPS) is an international knowledge-exchange and capacity-building network, specializing in ecosystems and their role in controlling the exchange of water, energy and chemical compounds between the land surface and the atmosphere. We outline priority directions for land-atmosphere interaction research and its contribution to the sustainable development agenda. Technical summary Greenhouse-gas emissions from human activities and land use change (from deforestation, forest degradation, and agricultural intensification) are contributing to climate change and biodiversity loss. Afforestation, reforestation, or growing bioenergy crops (with carbon capture and storage) are important land-based strategies to achieve the goals of the Paris Climate Agreement and to enhance biodiversity. The effectiveness of these actions depends on terrestrial ecosystems and their role in controlling or moderating the exchange of water, heat, and chemical compounds between the land surface and the atmosphere. The integrated Land Ecosystems Atmospheric Processes Study (iLEAPS), a global research network of Future Earth, enables the international community to communicate and remain up to date with developments and concepts about terrestrial ecosystems and their role in global water, energy, and biogeochemical cycles. Covering critically important topics such as fire, forestry, wetlands, methane emissions, urban areas, pollution, and climate change, the iLEAPS Global Research Programme sits center stage for some of the most importa

There is an immediate need to develop accurate and reliable global hydrological forecasts in light of the future vulnerability to hydrological hazards and water scarcity under a changing climate. As a part of the World Meteorological Organization’s (WMO) Global Hydrological Status and Outlook System (HydroSOS) initiative, we investigated different approaches to blending multi-model simulations for developing holistic operational global forecasts. The ULYSSES (mULti-model hYdrological SeaSonal prEdictionS system) dataset, to be published as “Global seasonal forecasts and reforecasts of river discharge and related hydrological variables ensemble from four state-of-the-art land surface and hydrological models” is used in this study. The first step for improving these forecasts is to investigate ways to improve the model simulations, as global models are not calibrated for local conditions. The analysis was performed over 119 different catchments worldwide for the baseline period of 1981–2019 for three variables: evapotranspiration, surface soil moisture and streamflow. This study evaluated blending approaches with a performance metric based (weighted) averaging of the multi-model simulations, using the catchment’s Kling-Gupta Efficiency (KGE) for the variable to define the weight. Hydrological model simulations were also bias-corrected to improve the multi-model blending output. Weighted blending in conjunction with bias-correction provided the best improvement in performance for the catchments investigated. Applying modelled weights during blending original simulations improved performance over ungauged catchments. The results indicate that there is potential to successfully and easily implement the bias-corrected weighted blending approach to improve operational forecasts globally. This work can be used to improve water resources management and hydrological hazard mitigation, especially in data-sparse regions.

Environmental science is primarily concerned with assessing the impacts of changing environmental conditions on the state of the natural world, whether affected by natural variability or by the impact of human activity. The Natural Environment Research Council (NERC) has recently published its digital strategy1, the first of its kind for NERC, which sets out a vision for digitally enabled environmental science for the next decade. This is echoed in the Met Office’s Research and Innovation Strategy that includes the vision of transforming the weather and climate research and services through deploying transformative technologies such as Digital Twins2. This strategy places data and digital technologies at the heart of UK environmental science. One such set of technologies are digital twins. A digital twin is a virtual representation of an object or system (for example the natural environment) updated as the system changes using observations. Observations may come from a range of sources, some traditionally used in the environmental science community such as satellite remote sensing or sensors on ships or weather stations, or through the emergence of sensors on everything from fridges to cars to large-scale built infrastructure. A digital twin then uses simulations or data-based methods such as machine learning to generate a replica (‘twin’) of the system that can be used to understand the system itself. Environmental digital twins therefore have the potential to significantly improve our understanding of the natural environment. The emergence of increasingly large, diverse, observed data sources and the development of digital twin technologies combined provides an opportunity for the environmental science community to make a step-change in our understanding of the environment. But to realise the value of environmental digital twins they need to be developed following agreed standards to make sure the information can be trusted by the user, and so that data from twins

Environmental science is primarily concerned with assessing the impacts of changing environmental conditions on the state of the natural world. The UK Natural Environment Research Council (NERC) has recently published its digital strategy , the first of its kind for NERC, which sets out a vision for digitally enabled environmental science for the next decade. This is echoed in the UK Met Office’s Research and Innovation Strategy that includes the vision of transforming the weather and climate research and services through deploying transformative technologies such as Digital Twins . This strategy places data and digital technologies at the heart of UK environmental science. One such set of technologies are digital twins. Environmental digital twins have the potential to significantly improve our understanding of the natural environment. The emergence of increasingly large, diverse, observed data sources and the development of digital twin technologies combined provides an opportunity for the environmental science community to make a step-change in our understanding of the environment. But to realise the value of environmental digital twins they need to be developed following agreed standards where interoperability is required to make sure the information can be trusted by the user, and so that data from twins can be shared. To enable this, an information management framework (IMF) is needed that establishes the components for effective information management within and across the digital twin ecosystem. It must enable secure, resilient interoperability of data, and is a reference point to facilitate data use in line with security, legal, commercial, privacy and other relevant concerns. We present recommendations for the development of an IMF for Environmental digital twins (IMFe) including the application of concepts such as an asset commons and balanced approach to standards to facilitate minimum interoperability requirements between twins while iteratively impleme

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.

Soil moisture is an important component of the Earth system and plays a key role in land-atmosphere interactions. Remote sensing of soil moisture is of great scientific interest and the scientific community has made significant progress in soil moisture estimation using Earth observations. Currently, several satellite-based coarse spatial resolution soil moisture datasets have been produced and widely used for various applications in climate science, hydrology, ecosystem research and agriculture. Owing to the strong demand for soil moisture data with high spatial resolution for regional applications, much effort has recently been devoted to the generation of high spatial resolution soil moisture data from either high-resolution satellite observations or by downscaling existing coarse-resolution satellite-based soil moisture datasets. In addition, land surface models provide an alternative way to obtain consistent high-resolution soil moisture information when forced with high-resolution inputs. The aim of this study is to create and evaluate high-resolution soil moisture products derived from multiple sources including satellite observations and land surface model simulations. The JULES-CHESS simulated soil moisture and satellite-based soil moisture datasets including SMAP L3E, SMAP L4, SMOS L4, Sentinel 1, ASCAT, and Sentinel 1/SMAP combined products were first validated against observed soil moisture from COSMOS-UK, a network of in-situ cosmic-ray based sensors. Second, an approach based on triple collocation was applied to compare these satellite products in the absence of a known reference dataset. Third, a combined soil moisture product was generated to integrate the better-performing soil moisture estimates based on triple collocation error estimation and a least-squares merging scheme. From further evaluation, it is found that the merged soil moisture integrates the characteristics of model simulation and satellite observations and particularly improves the l

Objectives: Cytomegalovirus (CMV) is known to have a significant impact on immune recovery post-allogeneic haemopoietic stem cell transplant (HSCT). Adoptive therapy with donor-derived or third-party virus-specific T cells (VST) can restore CMV immunity leading to clinical benefit in prevention and treatment of post-HSCT infection. We developed a mass cytometry approach to study natural immune recovery post-HSCT and assess the mechanisms underlying the clinical benefits observed in recipients of VST. Methods: A mass cytometry panel of 38 antibodies was utilised for global immune assessment (72 canonical innate and adaptive immune subsets) in HSCT recipients undergoing natural post-HSCT recovery (n = 13) and HSCT recipients who received third-party donor-derived CMV-VST as salvage for unresponsive CMV reactivation (n = 8). Results: Mass cytometry identified distinct immune signatures associated with CMV characterised by a predominance of innate cells (monocytes and NK) seen early and an adaptive signature with activated CD8+ T cells seen later. All CMV-VST recipients had failed standard antiviral pharmacotherapy as a criterion for trial involvement; 5/8 had failed to develop the adaptive immune signature by study enrolment despite significant CMV antigen exposure. Of these, VST administration resulted in development of the adaptive signature in association with CMV control in three patients. Failure to respond to CMV-VST in one patient was associated with persistent absence of the adaptive immune signature. Conclusion: The clinical benefit of CMV-VST may be mediated by the recovery of an adaptive immune signature characterised by activated CD8+ T cells.

Human cytomegalovirus (HCMV) is the most frequent cause of opportunistic viral infection following transplantation. Viral factors of potential clinical importance include the selection of mutants resistant to antiviral drugs and the occurrence of infections involving multiple HCMV strains. These factors are typically addressed by analyzing relevant HCMV genes by PCR and Sanger sequencing, which involves independent assays of limited sensitivity. To assess the dynamics of viral populations with high sensitivity, we applied high-throughput sequencing coupled with HCMV-adapted target enrichment to samples collected longitudinally from 11 transplant recipients (solid organ, n = 9, and allogeneic hematopoietic stem cell, n = 2). Only the latter presented multiple-strain infections. Four cases presented resistance mutations (n = 6), two (A594V and L595S) at high (100%) and four (V715M, V781I, A809V, and T838A) at low (<25%) frequency. One allogeneic hematopoietic stem cell transplant recipient presented up to four resistance mutations, each at low frequency. The use of high-throughput sequencing to monitor mutations and strain composition in people at risk of HCMV disease is of potential value in helping clinicians implement the most appropriate therapy.

Introduction: A pandemic coronavirus, SARS-CoV-2, causes COVID-19, a potentially life-threatening respiratory disease. Patients with cancer may have compromised immunity due to their malignancy and/or treatment, and may be at elevated risk of severe COVID-19. Community transmission of COVID-19 could overwhelm health care services, compromising delivery of cancer care. This interim consensus guidance provides advice for clinicians managing patients with cancer during the pandemic. Main recommendations: During the COVID-19 pandemic:. In patients with cancer with fever and/or respiratory symptoms, consider causes in addition to COVID-19, including other infections and therapy-related pneumonitis. For suspected or confirmed COVID-19, discuss temporary cessation of cancer therapy with a relevant specialist. Provide information on COVID-19 for patients and carers. Adopt measures within cancer centres to reduce risk of nosocomial SARS-CoV-2 acquisition; support population-wide social distancing; reduce demand on acute services; ensure adequate staffing; and provide culturally safe care. Measures should be equitable, transparent and proportionate to the COVID-19 threat. Consider the risks and benefits of modifying cancer therapies due to COVID-19. Communicate treatment modifications, and review once health service capacity allows. Consider potential impacts of COVID-19 on the blood supply and availability of stem cell donors. Discuss and document goals of care, and involve palliative care services in contingency planning. Changes in management as a result of this statement: This interim consensus guidance provides a framework for clinicians managing patients with cancer during the COVID-19 pandemic. In view of the rapidly changing situation, clinicians must also monitor national, state, local and institutional policies, which will take precedence. Endorsed by: Australasian Leukaemia and Lymphoma Group; Australasian Lung Cancer Trials Group; Australian and New Zealand Childr

INTRODUCTION: A pandemic coronavirus, SARS-CoV-2, causes COVID-19, a potentially life-threatening respiratory disease. Patients with cancer may have compromised immunity due to their malignancy and/or treatment, and may be at elevated risk of severe COVID-19. Community transmission of COVID-19 could overwhelm health care services, compromising delivery of cancer care. This interim consensus guidance provides advice for clinicians managing patients with cancer during the pandemic. MAIN RECOMMENDATIONS: During the COVID-19 pandemic: In patients with cancer with fever and/or respiratory symptoms, consider causes in addition to COVID-19, including other infections and therapy-related pneumonitis. For suspected or confirmed COVID-19, discuss temporary cessation of cancer therapy with a relevant specialist. Provide information on COVID-19 for patients and carers. Adopt measures within cancer centres to reduce risk of nosocomial SARS-CoV-2 acquisition; support population-wide social distancing; reduce demand on acute services; ensure adequate staffing; and provide culturally safe care. Measures should be equitable, transparent and proportionate to the COVID-19 threat. Consider the risks and benefits of modifying cancer therapies due to COVID-19. Communicate treatment modifications, and review once health service capacity allows. Consider potential impacts of COVID-19 on the blood supply and availability of stem cell donors. Discuss and document goals of care, and involve palliative care services in contingency planning. CHANGES IN MANAGEMENT AS A RESULT OF THIS STATEMENT: This interim consensus guidance provides a framework for clinicians managing patients with cancer during the COVID-19 pandemic. In view of the rapidly changing situation, clinicians must also monitor national, state, local and institutional policies, which will take precedence. ENDORSED BY: Australasian Leukaemia and Lymphoma Group; Australasian Lung Cancer Trials Group; Australian and New Zealand Childre