The Post-Wildfire Impact of Burn Severity and Age on Black Carbon Snow Deposition and Implications for Snow Water Resources, Cascade Range, Washington

Wildfires in the snow zone affect ablation by removing forest canopy, which enhances surface solar irradiance, and depositing light absorbing particles [LAPs, such as black carbon (BC)] on the snowpack, reducing snow albedo. How variations in BC deposition affects post-wildfire snowmelt timing is poorly known and highly relevant to water resources. We present a field-based analysis of BC variability across five sites of varying burn age and burn severity in the Cascade Range, Washington State, United States. Single particle soot photometer (SP2) analyses of BC snow concentrations were used to assess the impact of BC on snow albedo, and radiative transfer modeling was used to estimate the radiative effect of BC on snowmelt. Results were compared to Snowpack Telemetry (SNOTEL) data from one site that burned in 2012 and another in a proximal unburned forest. We show that post-wildfire forests provide a significant source of BC to the snowpack, and this effect increases by an order of magnitude in regions of high versus low burn severity, and decreased by two orders of magnitude over a decade. There is a shift in the timing of snowmelt, with snow disappearance occurring on average 19 ± 9 days earlier post-wildfire (2013–19) relative to pre-wildfire (1983–2012). This study improves understanding of the connection between wildfire activity and snowmelt, which is of high relevance as climate change models project further decreases in snowpack and increases in wildfire activity in the Washington Cascades

The spectral and chemical measurement of pollutants on snow near South Pole, Antarctica

Remote sensing of light-absorbing particles (LAPs), or dark colored impurities, such as black carbon (BC) and dust on snow, is a key remaining challenge in cryospheric surface characterization and application to snow, ice, and climate models. We present a quantitative data set of in situ snow reflectance, measured and modeled albedo, and BC and trace element concentrations from clean to heavily fossil fuel emission contaminated snow near South Pole, Antarctica. Over 380 snow reflectance spectra (350–2500 nm) and 28 surface snow samples were collected at seven distinct sites in the austral summer season of 2014–2015. Snow samples were analyzed for BC concentration via a single particle soot photometer and for trace element concentration via an inductively coupled plasma mass spectrometer. Snow impurity concentrations ranged from 0.14 to 7000 part per billion (ppb) BC, 9.5 to 1200 ppb sulfur, 0.19 to 660 ppb iron, 0.013 to 1.9 ppb chromium, 0.13 to 120 ppb copper, 0.63 to 6.3 ppb zinc, 0.45 to 82 parts per trillion (ppt) arsenic, 0.0028 to 6.1 ppb cadmium, 0.062 to 22 ppb barium, and 0.0044 to 6.2 ppb lead. Broadband visible to shortwave infrared albedo ranged from 0.85 in pristine snow to 0.62 in contaminated snow. LAP radiative forcing, the enhanced surface absorption due to BC and trace elements, spanned from \u3c1 W m­–2 for clean snow to ~70 W m­–2 for snow with high BC and trace element content. Measured snow reflectance differed from modeled snow albedo due to specific impurity-dependent absorption features, which we recommend be further studied and improved in snow albedo models

Global snow mass measurements and the effect of stratigraphic detail on inversion of microwave brightness temperatures

Snow provides large seasonal storage of freshwater, and information about the distribution of snow mass as Snow Water Equivalent (SWE) is important for hydrological planning and detecting climate change impacts. Large regional disagreements remain between estimates from reanalyses, remote sensing and modelling. Assimilating passive microwave information improves SWE estimates in many regions but the assimilation must account for how microwave scattering depends on snow stratigraphy. Physical snow models can estimate snow stratigraphy, but users must consider the computational expense of model complexity versus acceptable errors. Using data from the National Aeronautics and Space Administration Cold Land Processes Experiment (NASA CLPX) and the Helsinki University of Technology (HUT) microwave emission model of layered snowpacks, it is shown that simulations of the brightness temperature difference between 19 GHz and 37 GHz vertically polarised microwaves are consistent with Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) and Special Sensor Microwave Imager (SSM/I) retrievals once known stratigraphic information is used. Simulated brightness temperature differences for an individual snow profile depend on the provided stratigraphic detail. Relative to a profile defined at the 10 cm resolution of density and temperature measurements, the error introduced by simplification to a single layer of average properties increases approximately linearly with snow mass. If this brightness temperature error is converted into SWE using a traditional retrieval method then it is equivalent to ±13 mm SWE (7% of total) at a depth of 100 cm. This error is reduced to ±5.6 mm SWE (3 % of total) for a two-layer model

Outcomes of pediatric patients with therapy-related myeloid neoplasms

Long-term outcomes after allogeneic hematopoietic cell transplantation (HCT) for therapy-related myeloid neoplasms (tMNs) are dismal. There are few multicenter studies defining prognostic factors in pediatric patients with tMNs. We have accumulated the largest cohort of pediatric patients who have undergone HCT for a tMN to perform a multivariate analysis defining factors predictive of long-term survival. Sixty-eight percent of the 401 patients underwent HCT using a myeloablative conditioning (MAC) regimen, but there were no statistically significant differences in the overall survival (OS), event-free survival (EFS), or cumulative incidence of relapse and non-relapse mortality based on the conditioning intensity. Among the recipients of MAC regimens, 38.4% of deaths were from treatment-related causes, especially acute graft versus host disease (GVHD) and end-organ failure, as compared to only 20.9% of deaths in the reduced-intensity conditioning (RIC) cohort. Exposure to total body irradiation (TBI) during conditioning and experiencing grade III/IV acute GVHD was associated with worse OS. In addition, a diagnosis of therapy-related myelodysplastic syndrome and having a structurally complex karyotype at tMN diagnosis were associated with worse EFS. Reduced-toxicity (but not reduced-intensity) regimens might help to decrease relapse while limiting mortality associated with TBI-based HCT conditioning in pediatric patients with tMNs

Glacier algae accelerate melt rates on the western Greenland Ice Sheet

Melting of the Greenland Ice Sheet (GrIS) is the largest single contributor to eustatic sea level and is amplified by the growth of pigmented algae on the ice surface that increase solar radiation absorption. This biological albedo reducing effect and its impact upon sea level rise has not previously been quantified. Here, we combine field spectroscopy with a novel radiative transfer model, supervised classification of UAV and satellite remote sensing data and runoff modelling to calculate biologically-driven ice surface ablation and compare it to the albedo reducing effects of local mineral dust. We demonstrate that algal growth led to an additional 5.5–8.0 Gt of runoff from the western sector of the GrIS in summer 2016, representing 6–9 % of the total. Our analysis confirms the importance of the biological albedo feedback and that its omission from predictive models leads to the systematic underestimation of Greenland’s future sea level contribution, especially because both the bare ice zones available for algal colonization and the length of the active growth season are set to expand in the future

The effect of distance on maternal institutional delivery choice : Evidence from Malawi

In many low- and middle-income countries, geographical accessibility continues to be a barrier to health care utilization. In this paper, we aim to better understand the full relationship between distance to providers and utilization of maternal delivery services. We address three methodological challenges: non-linear effects between distance and utilization; unobserved heterogeneity through non-random distance “assignment”; and heterogeneous effects of distance. Linking Malawi Demographic Health Survey household data to Service Provision Assessment facility data, we consider distance as a continuous treatment variable, estimating a Dose-Response Function based on generalized propensity scores, allowing exploration of non-linearities in the effect of an increment in distance at different distance exposures. Using an instrumental variables approach, we examine the potential for unobserved differences between women residing at different distances to health facilities. Our results suggest distance significantly reduces the probability of having a facility delivery, with evidence of non-linearities in the effect. The negative relationship is shown to be particularly strong for women with poor health knowledge and lower socio-economic status, with important implications for equity. We also find evidence of potential unobserved confounding, suggesting that methods that ignore such confounding may underestimate the effect of distance on the utilization of health services