ALBERT

Description: The CubeSat Constellation Cloud Winds (C3Winds) is a NASA Earth Venture Instrument (EV-I) concept with the primary objective to better understand mesoscale dynamics and their structures in severe weather systems. With potential catastrophic damage and loss of life, strong extratropical and tropical cyclones (ETCs and TCs) have profound three-dimensional impacts on the atmospheric dynamic and thermodynamic structures, producing complex cloud precipitation patterns, strong low-level winds, extensive tropopause folds, and intense stratosphere-troposphere exchange. Employing a compact, stereo IR-visible imaging technique from two formation-flying CubeSats, C3Winds seeks to measure and map high-resolution (2 km) cloud motion vectors (CMVs) and cloud geometric height (CGH) accurately by tracking cloud features within 5-15 min. Complementary to lidar wind observations from space, the high-resolution wind fields from C3Winds will allow detailed investigations on strong low-level wind formation in an occluded ETC development, structural variations of TC inner-core rotation, and impacts of tropopause folding events on tropospheric ozone and air quality. Together with scatterometer ocean surface winds, C3Winds will provide a more comprehensive depiction of atmosphere-boundary-layer dynamics and interactive processes. Built upon mature imaging technologies and long history of stereoscopic remote sensing, C3Winds provides an innovative, cost-effective solution to global wind observations with potential of increased diurnal sampling via CubeSat constellation.

Description: Hydroxyl radical (OH) is the main daytime oxidant in the troposphere and determines the atmospheric lifetimes of many compounds. We use aircraft measurements of O3, H2O, NO, and other species from the Convective Transport of Active Species in the Tropics (CONTRAST) field campaign, which occurred in the tropical western Pacific (TWP) during January-February 2014, to constrain a photochemical box model and estimate concentrations of OH throughout the troposphere. We find that tropospheric column OH (OHCOL) inferred from CONTRAST observations is 12 to 40% higher than found in chemical transport models (CTMs), including CAM-chem-SD run with 2014 meteorology as well as eight models that participated in POLMIP (2008 meteorology). Part of this discrepancy is due to a clear-sky sampling bias that affects CONTRAST observations; accounting for this bias and also for a small difference in chemical mechanism results in our empirically based value of OHCOL being 0 to 20% larger than found within global models. While these global models simulate observed O3 reasonably well, they underestimate NOx (NO +NO2) by a factor of 2, resulting in OHCOL approx.30% lower than box model simulations constrained by observed NO. Underestimations by CTMs of observed CH3CHO throughout the troposphere and of HCHO in the upper troposphere further contribute to differences between our constrained estimates of OH and those calculated by CTMs. Finally, our calculations do not support the prior suggestion of the existence of a tropospheric OH minimum in the TWP, because during January-February 2014 observed levels of O3 and NO were considerably larger than previously reported values in the TWP.

Description: Multi-Spectra, Multi-Species, Multi-Sensors (MUSES): Builds off of heritage from the Tropospheric Emission Spectrometer (TES) optimal estimation (OE) algorithm to combine a priori and satellite data, including rigorous error analysis diagnostics and observation operators needed for trend analysis, climate model evaluation, and data assimilation; has generic design to incorporate forward model radiances from hyperspectral measurements from multiple sensors into the joint retrieval algorithm.

Description: The incidence of wildfires in the Arctic and subarctic is increasing; in boreal North America, for example, the burned area is expected to increase by 200-300 over the next 50-100 years, which previous studies suggest could have a large effect on cloud microphysics, lifetime, albedo, and precipitation. However, the interactions between smoke particles and clouds remain poorly quantified due to confounding meteorological influences and remote sensing limitations. Here, we use data from several aircraft campaigns in the Arctic and subarctic to explore cloud microphysics in liquid-phase clouds influenced by biomass burning. Median cloud droplet radii in smoky clouds were 50 smaller than in background clouds. Based on the relationship between cloud droplet number (N(liq))/ and various biomass burning tracers (BBt/ across the multi-campaign dataset, we calculated the magnitude of subarctic and Arctic smoke aerosol-cloud interactions (ACI, where ACI = (1/3) x dln(N(liq))/dln(BBt)) to be 0.12 out of a maximum possible value of 0.33 that would be obtained if all aerosols were to nucleate cloud droplets. Interestingly, in a separate subarctic case study with low liquid water content (0.02 gm/ cu m) and very high aerosol concentrations (2000-3000 cu m) in the most polluted clouds, the estimated ACI value was only 0.06. In this case, competition for water vapor by the high concentration of CCN strongly limited the formation of droplets and reduced the cloud albedo effect, which highlights the importance of cloud feedbacks across scales. Using our calculated ACI values, we estimate that the smoke-driven cloud albedo effect may decrease shortwave radiative flux by 2 and 4 W/sq or more under some low and homogeneous cloud cover conditions in the subarctic, although the changes should be smaller in high surface albedo regions of the Arctic. We lastly show evidence to suggest that numerous northern latitude background Aitken particles can interact with combustion particles, perhaps impacting their properties as cloud condensation and ice nuclei. However, the influence of background particles on smoke-driven indirect effects is currently unclear.

Description: No abstract available

Description: No abstract available

Description: No abstract available

Description: Ethane is the second most abundant atmospheric hydrocarbon, exerts a strong influence on tropospheric ozone, and reduces the atmosphere's oxidative capacity. Global observations showed declining ethane abundances from 1984 to 2010, while a regional measurement indicated increasing levels since 2009, with the reason for this subject to speculation. The Bakken shale is an oil and gas-producing formation centered in North Dakota that experienced a rapid increase in production beginning in 2010. We use airborne data collected over the North Dakota portion of the Bakken shale in 2014 to calculate ethane emissions of 0.23 +/- 0.07 (2 sigma) Tg/yr, equivalent to 1-3% of total global sources. Emissions of this magnitude impact air quality via concurrent increases in tropospheric ozone. This recently developed large ethane source from one location illustrates the key role of shale oil and gas production in rising global ethane levels.

Description: The NASA Severe Storm Thunderstorm Observations and Regional Modeling(NASA STORM) project enhanced NASAs severe weather research capabilities, building upon existing Earth Science expertise at NASA Marshall Space Flight Center (MSFC). During this project, MSFC extended NASAs ground-based lightning detection capacity to include a readily deployable lightning mapping array (LMA). NASA STORM also enabled NASAs Short-term Prediction and Research Transition (SPoRT) to add convection allowing ensemble modeling to its portfolio of regional numerical weather prediction (NWP) capabilities. As a part of NASA STORM, MSFC developed new open-source capabilities for analyzing and displaying weather radar observations integrated from both research and operational networks. These accomplishments enabled by NASA STORM are a step towards enhancing NASAs capabilities for studying severe weather and positions them for any future NASA related severe storm field campaigns.

Description: The Soil Moisture and Ocean Salinity (SMOS) satellite provides retrievals of soil moisture in the upper 5 cm with a 30-50 km resolution and a mission accuracy requirement of 0.04 cm(sub 3 cm(sub -3). These observations can be used to improve land surface model soil moisture states through data assimilation. In this paper, SMOS soil moisture retrievals are assimilated into the Noah land surface model via an Ensemble Kalman Filter within the NASA Land Information System. Bias correction is implemented using Cumulative Distribution Function (CDF) matching, with points aggregated by either land cover or soil type to reduce sampling error in generating the CDFs. An experiment was run for the warm season of 2011 to test SMOS data assimilation and to compare assimilation methods. Verification of soil moisture analyses in the 0-10 cm upper layer and root zone (0-1 m) was conducted using in situ measurements from several observing networks in the central and southeastern United States. This experiment showed that SMOS data assimilation significantly increased the anomaly correlation of Noah soil moisture with station measurements from 0.45 to 0.57 in the 0-10 cm layer. Time series at specific stations demonstrate the ability of SMOS DA to increase the dynamic range of soil moisture in a manner consistent with station measurements. Among the bias correction methods, the correction based on soil type performed best at bias reduction but also reduced correlations. The vegetation-based correction did not produce any significant differences compared to using a simple uniform correction curve.