Synergistic use of SMAP and OCO-2 data in assessing the responses of ecosystem productivity to the 2018 U.S. drought

Soil moisture and gross primary productivity (GPP) estimates from the Soil Moisture Active Passive (SMAP) and solar-induced chlorophyll fluorescence (SIF) from the Orbiting Carbon Observatory-2 (OCO-2) provide new opportunities for understanding the relationship between soil moisture and terrestrial photosynthesis over large regions. Here we explored the potential of the synergistic use of SMAP and OCO-2 based data for monitoring the responses of ecosystem productivity to drought. We used complementary observational information on root-zone soil moisture and GPP (9 km) from SMAP and fine-resolution SIF (0.05°; GOSIF) derived from OCO-2 SIF soundings. We compared the spatial pattern and temporal evolution of anomalies of these variables over the conterminous U.S. during the 2018 drought, and examined to what extent they could characterize the drought-induced variations of flux tower GPP and crop yield data. Our results showed that SMAP GPP and GOSIF, both freely available online, could well capture the spatial extent and dynamics of the impacts of drought indicated by the U.S. Drought Monitor maps and the SMAP root-zone soil moisture deficit. Over the U.S. Southwest, monthly anomalies of soil moisture showed significant positive correlations with those of SMAP GPP (R² = 0.44, p < 0.001) and GOSIF (R² = 0.76, p < 0.001), demonstrating strong water availability constraints on plant productivity across dryland ecosystems. We further found that SMAP GPP and GOSIF captured the impact of drought on tower GPP and crop yield. Our results suggest that synergistic use of SMAP and OCO-2 data products can reveal the drought evolution and its impact on ecosystem productivity and carbon uptake at multiple spatial and temporal scales, and demonstrate the value of SMAP and OCO-2 for studying ecosystem function, carbon cycling, and climate change

Synergistic use of SMAP and OCO-2 data in assessing the responses of ecosystem productivity to the 2018 U.S. drought

Soil moisture and gross primary productivity (GPP) estimates from the Soil Moisture Active Passive (SMAP) and solar-induced chlorophyll fluorescence (SIF) from the Orbiting Carbon Observatory-2 (OCO-2) provide new opportunities for understanding the relationship between soil moisture and terrestrial photosynthesis over large regions. Here we explored the potential of the synergistic use of SMAP and OCO-2 based data for monitoring the responses of ecosystem productivity to drought. We used complementary observational information on root-zone soil moisture and GPP (9 km) from SMAP and fine-resolution SIF (0.05°; GOSIF) derived from OCO-2 SIF soundings. We compared the spatial pattern and temporal evolution of anomalies of these variables over the conterminous U.S. during the 2018 drought, and examined to what extent they could characterize the drought-induced variations of flux tower GPP and crop yield data. Our results showed that SMAP GPP and GOSIF, both freely available online, could well capture the spatial extent and dynamics of the impacts of drought indicated by the U.S. Drought Monitor maps and the SMAP root-zone soil moisture deficit. Over the U.S. Southwest, monthly anomalies of soil moisture showed significant positive correlations with those of SMAP GPP (R² = 0.44, p < 0.001) and GOSIF (R² = 0.76, p < 0.001), demonstrating strong water availability constraints on plant productivity across dryland ecosystems. We further found that SMAP GPP and GOSIF captured the impact of drought on tower GPP and crop yield. Our results suggest that synergistic use of SMAP and OCO-2 data products can reveal the drought evolution and its impact on ecosystem productivity and carbon uptake at multiple spatial and temporal scales, and demonstrate the value of SMAP and OCO-2 for studying ecosystem function, carbon cycling, and climate change

Could operational hydrological models be made compatible with satellite soil moisture observations?

Soil moisture is a significant state variable in flood forecasting. Nowadays more and more satellite soil moisture products are available, yet their usage in the operational hydrology is still limited. This is because the soil moisture state variables in most operational hydrological models (mostly conceptual models) are over-simplified—resulting in poor compatibility with the satellite soil moisture observations. A case study is provided to discuss this in more detail, with the adoption of the XAJ model and the Soil Moisture and Ocean Salinity (SMOS) level-3 soil moisture observation to illustrate the relevant issues. It is found that there are three distinct deficiencies existed in the XAJ model that could cause the mismatch issues with the SMOS soil moisture observation: (i) it is based on runoff generation via the field capacity excess mechanism (interestingly, such a runoff mechanism is called the saturation excess in XAJ while in fact it is clearly a misnomer); (ii) evaporation occurs at the potential rate in its upper soil layer until the water storage in the upper layer is exhausted, and then the evapotranspiration process from the lower layers will commence – leading to an abrupt soil water depletion in the upper soil layer; (iii) it uses the multi-bucket concept at each soil layer – hence the model has varied soil layers. Therefore, it is a huge challenge to make an operational hydrological model compatible with the satellite soil moisture data. The paper argues that this is possible and some new ideas have been explored and discussed. Copyright © 2016 John Wiley & Sons, Ltd. Citing Literatur

Central/eastern North Pacific photochemical precursor distributions for fall/spring seasons as defined by airborne field studies

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95530/1/jgrd9190.pd

Towards fault-tolerant quantum computing with trapped ions

Today ion traps are among the most promising physical systems for constructing a quantum device harnessing the computing power inherent in the laws of quantum physics. The standard circuit model of quantum computing requires a universal set of quantum logic gates for the implementation of arbitrary quantum operations. As in classical models of computation, quantum error correction techniques enable rectification of small imperfections in gate operations, thus allowing for perfect computation in the presence of noise. For fault-tolerant computation, it is commonly believed that error thresholds ranging between 10^-4 and 10^-2 will be required depending on the noise model and the computational overhead for realizing the quantum gates. Up to now, all experimental implementations have fallen short of these requirements. Here, we report on a Molmer-Sorensen type gate operation entangling ions with a fidelity of 99.3(1)% which together with single-qubit operations forms a universal set of quantum gates. The gate operation is performed on a pair of qubits encoded in two trapped calcium ions using a single amplitude-modulated laser beam interacting with both ions at the same time. A robust gate operation, mapping separable states onto maximally entangled states is achieved by adiabatically switching the laser-ion coupling on and off. We analyse the performance of a single gate and concatenations of up to 21 gate operations. The gate mechanism holds great promise not only for two-qubit but also for multi-qubit operations.Comment: submitted to Nature Physic

A Randomized Phase II Trial Comparing the Efficacy and Safety of Pioglitazone, Clarithromycin and Metronomic Low-Dose Chemotherapy with Single-Agent Nivolumab Therapy in Patients with Advanced Non-small Cell Lung Cancer Treated in Second or Further Line (ModuLung)

Background: Most non-small cell lung cancers occur in elderly and frequently comorbid patients. Therefore, it is necessary to evaluate the efficacy of biomodulatory active therapy regimen, concertedly interfering with tumor-associated homeostatic pathways to achieve tumor control paralleled by modest toxicity profiles. Patients and Methods: The ModuLung trial is a national, multicentre, prospective, open-label, randomized phase II trial in patients with histologically confirmed stage IIIB/IV squamous (n = 11) and non-squamous non-small cell (n = 26) lung cancer who failed first-line platinum-based chemotherapy. Patients were randomly assigned on a 1:1 ratio to the biomodulatory or control group, treated with nivolumab. Patients randomized to the biomodulatory group received an all-oral therapy consisting of treosulfan 250 mg twice daily, pioglitazone 45 mg once daily, clarithromycin 250 mg twice daily, until disease progression or unacceptable toxicity. Results: The study had to be closed pre-maturely due to approval of immune checkpoint inhibitors (ICi) in first-line treatment. Thirty-seven patients, available for analysis, were treated in second to forth-line. Progression-free survival (PFS) was significantly inferior for biomodulation (N = 20) vs. nivolumab (N = 17) with a median PFS (95% confidence interval) of 1.4 (1.2–2.0) months vs. 1.6 (1.4–6.2), respectively; with a hazard ratio (95% confidence interval) of 1.908 [0.962; 3.788]; p = 0.0483. Objective response rate was 11.8% with nivolumab vs. 5% with biomodulation, median follow-up 8.25 months. The frequency of grade 3–5 treatment related adverse events was 29% with nivolumab and 10% with biomodulation. Overall survival (OS), the secondary endpoint, was comparable in both treatment arms; biomodulation with a median OS (95% confidence interval) of 9.4 (6.0–33.0) months vs. nivolumab 6.9 (4.6–24.0), respectively; hazard ratio (95% confidence interval) of 0.733 [0.334; 1.610]; p = 0.4368. Seventy-five percent of patients in the biomodulation arm received rescue therapy with checkpoint inhibitors. Conclusions: This trial shows that the biomodulatory therapy was inferior to nivolumab on PFS. However, the fact that OS was similar between groups gives rise to the hypothesis that the well-tolerable biomodulatory therapy may prime tumor tissues for efficacious checkpoint inhibitor therapy, even in very advanced treatment lines where poor response to ICi might be expected with increasing line of therapy

Perspective on satellite-based land data assimilation to estimate water cycle components in an era of advanced data availability and model sophistication

The beginning of the 21st century is marked by a rapid growth of land surface satellite data and model sophistication. This offers new opportunities to estimate multiple components of the water cycle via satellite-based land data assimilation (DA) across multiple scales. By resolving more processes in land surface models and by coupling the land, the atmosphere, and other Earth system compartments, the observed information can be propagated to constrain additional unobserved variables. Furthermore, access to more satellite observations enables the direct constraint of more and more components of the water cycle that are of interest to end users. However, the finer level of detail in models and data is also often accompanied by an increase in dimensions, with more state variables, parameters, or boundary conditions to estimate, and more observations to assimilate. This requires advanced DA methods and efficient solutions. One solution is to target specific observations for assimilation based on a sensitivity study or coupling strength analysis, because not all observations are equally effective in improving subsequent forecasts of hydrological variables, weather, agricultural production, or hazards through DA. This paper offers a perspective on current and future land DA development, and suggestions to optimally exploit advances in observing and modeling systems

Sorafenib or placebo in patients with newly diagnosed acute myeloid leukaemia: long-term follow-up of the randomized controlled SORAML trial

Abstract Early results of the randomized placebo-controlled SORAML trial showed that, in patients with newly diagnosed acute myeloid leukaemia (AML), sorafenib led to a significant improvement in event-free (EFS) and relapse-free survival (RFS). In order to describe second-line treatments and their implications on overall survival (OS), we performed a study after a median follow-up time of 78 months. Newly diagnosed fit AML patients aged ≤60 years received sorafenib (n = 134) or placebo (n = 133) in addition to standard chemotherapy and as maintenance treatment. The 5-year EFS was 41 versus 27% (HR 0.68; p = 0.011) and 5-year RFS was 53 versus 36% (HR 0.64; p = 0.035). Allogeneic stem cell transplantation (allo SCT) was performed in 88% of the relapsed patients. Four years after salvage allo SCT, the cumulative incidence of relapse was 54 versus 35%, and OS was 32 versus 50%. The 5-year OS from randomization in all study patients was 61 versus 53% (HR 0.82; p = 0.282). In conclusion, the addition of sorafenib to chemotherapy led to a significant prolongation of EFS and RFS. Although the OS benefit did not reach statistical significance, these results confirm the antileukaemic activity of sorafenib