ALBERT

Description: Precipitation, including rain and snow, is a critical part of the Earth's energy and hydrology cycles. Precipitation impacts latent heating profiles locally while global circulation patterns distribute precipitation and energy from the equator to the poles. For the hydrological cycle, falling snow is a primary contributor in northern latitudes during the winter seasons. Falling snow is the source of snow pack accumulations that provide fresh water resources for many communities in the world. Furthermore, falling snow impacts society by causing transportation disruptions during severe snow events. In order to collect information on the complete global precipitation cycle, both liquid and frozen precipitation must be collected. The challenges of estimating falling snow from space still exist though progress is being made. These challenges include weak falling snow signatures with respect to background (surface, water vapor) signatures for passive sensors over land surfaces, unknowns about the spherical and non-spherical shapes of the snowflakes, their particle size distributions (PSDs) and how the assumptions about the unknowns impact observed brightness temperatures or radar reflectivities, differences in near surface snowfall and total column snow amounts, and limited ground truth to validate against. While these challenges remain, knowledge of their impact on expected retrieval results is an important key for understanding falling snow retrieval estimations. Since falling snow from space is the next precipitation measurement challenge from space, information must be determined in order to guide retrieval algorithm development for these current and future missions. This information includes thresholds of detection for various sensor channel configurations, snow event system characteristics, snowflake particle assumptions, and surface types. For example, can a lake effect snow system with low (approx 2.5 km) cloud tops having an ice water content (IWC) at the surface of 0.25 g / cubic m and dendrite snowflakes be detected? If this information is known, we can focus retrieval efforts on detectable storms and concentrate advances on achievable results. Here, the focus is to determine thresholds of detection for falling snow for various snow conditions over land and lake surfaces. The results rely on simulated Weather Research Forecasting (WRF) simulations of falling snow cases since simulations provide all the information to determine the measurements from space and the ground truth. Sensitivity analyses were performed to better ascertain the relationships between multifrequency microwave and millimeter-wave sensor observations and the falling snow/underlying field of view. In addition, thresholds of detection for various sensor channel configurations, snow event system characteristics, snowflake particle assumptions, and surface types were studied. Results will be presented for active radar at Ku, Ka, and W-band and for passive radiometer channels from 10 to 183 GHz.

Description: A simplied framework is presented for assessing the qualitative sensitivities of computed microwave properties, satellite brightness temperatures, and radar reflectivities to assumptions concerning the physical properties of ice-phase hydrometeors. Properties considered included the shape parameter of a gamma size distribution andthe melted-equivalent mass median diameter D0, the particle density, dielectric mixing formula, and the choice of complex index of refraction for ice. We examine these properties at selected radiometer frequencies of 18.7, 36.5, 89.0, and 150.0 GHz; and radar frequencies at 2.8, 13.4, 35.6, and 94.0 GHz consistent with existing and planned remote sensing instruments. Passive and active microwave observables of ice particles arefound to be extremely sensitive to the melted-equivalent mass median diameter D0 ofthe size distribution. Similar large sensitivities are found for variations in the ice vol-ume fraction whenever the geometric mass median diameter exceeds approximately 1/8th of the wavelength. At 94 GHz the two-way path integrated attenuation is potentially large for dense compact particles. The distribution parameter mu has a relatively weak effect on any observable: less than 1-2 K in brightness temperature and up to 2.7 dB difference in the effective radar reflectivity. Reversal of the roles of ice and air in the MaxwellGarnett dielectric mixing formula leads to a signicant change in both microwave brightness temperature (10 K) and radar reflectivity (2 dB). The choice of Warren (1984) or Warren and Brandt (2008) for the complex index of refraction of ice can produce a 3%-4% change in the brightness temperature depression.

Description: The SABER instrument on board the TIMED satellite is a limb scanning infrared radiometer designed to measure temperature and minor constituent vertical profiles and energetics parameters in the mesosphere and lower thermosphere (MLT) The H2O concentrations are retrieved from 6.3 micron band radiances. The interpretation of this radiance requires developing a non-LTE H2O model that includes energy exchange processes with the system of O3 and O2 vibrational levels populated at the daytime through a number of photoabsorption and photodissociation processes. We developed a research model base on an extended H2O non-LTE model of Manuilova coupled with the novel model of the electronic kinetics of the O2 and O3 photolysis products suggested by Yankosvky and Manuilova. The performed study of this model helped u to develop and test an optimized operational model for interpretation of SABER 6.3 micron band radiances. The sensitivity of retrievals to the parameters of the model is discussed. The H2O retrievals are compared to other measurements for different seasons and locations.

Description: Physically-based passive microwave precipitation retrieval algorithms require a set of relationships between satellite observed brightness temperatures (TB) and the physical state of the underlying atmosphere and surface. These relationships are typically non-linear, such that inversions are ill-posed especially over variable land surfaces. In order to better understand these relationships, this work presents a theoretical analysis using brightness temperature weighting functions to quantify the percentage of the TB resulting from absorption/emission/reflection from the surface, absorption/emission/scattering by liquid and frozen hydrometeors in the cloud, the emission from atmospheric water vapor, and other contributors. The results are presented for frequencies from 10 to 874 GHz and for several individual precipitation profiles as well as for three cloud resolving model simulations of falling snow. As expected, low frequency channels (〈89 GHz) respond to liquid hydrometeors and the surface, while the higher frequency channels become increasingly sensitive to ice hydrometeors and the water vapor sounding channels react to water vapor in the atmosphere. Low emissivity surfaces (water and snow-covered land) permit energy downwelling from clouds to be reflected at the surface thereby increasing the percentage of the TB resulting from the hydrometeors. The slant path at a 53deg viewing angle increases the hydrometeor contributions relative to nadir viewing channels and show sensitivity to surface polarization effects. The TB percentage information presented in this paper answers questions about the relative contributions to the brightness temperatures and provides a key piece of information required to develop and improve precipitation retrievals over land surfaces.

Description: The vast set of near global and continuous atmospheric measurements made by the SABER instrument since 2002, including daytime and nighttime kinetic temperature (T(sub k)) from 20 to 105 km, is available to the scientific community. The temperature is retrieved from SABER measurements of the atmospheric 15 micron CO2 limb emission. This emission separates from local thermodynamic equilibrium (LTE) conditions in the rarefied mesosphere and thermosphere, making it necessary to consider the CO2 vibrational state non-LTE populations in the retrieval algorithm above 70 km. Those populations depend on kinetic parameters describing the rate at which energy exchange between atmospheric molecules take place, but some of these collisional rates are not well known. We consider current uncertainties in the rates of quenching of CO2 (v2 ) by N2 , O2 and O, and the CO2 (v2 ) vibrational-vibrational exchange to estimate their impact on SABER T(sub k) for different atmospheric conditions. The T(sub k) is more sensitive to the uncertainty in the latter two and their effects depend on altitude. The T(sub k) combined systematic error due to non-LTE kinetic parameters does not exceed +/- 1.5 K below 95 km and +/- 4-5 K at 100 km for most latitudes and seasons (except for polar summer) if the Tk profile does not have pronounced vertical structure. The error is +/- 3 K at 80 km, +/- 6 K at 84 km and +/- 18 K at 100 km under the less favourable polar summer conditions. For strong temperature inversion layers, the errors reach +/- 3 K at 82 km and +/- 8 K at 90 km. This particularly affects tide amplitude estimates, with errors of up to +/- 3 K.

Description: This research seeks to assess and improve the accuracy of microphysical assumptions used in satellite passive microwave radiative transfer models and retrieval algorithms by exploiting complementary observations from satellite radiometers, such as TRMM/AMSR-E/GPM, and coincident aircraft instruments, such as the next generation precipitation radar (PR-2). We focus in particular on aircraft data obtained during the Wakasa Bay field experiment, Japan 2003, pertaining to surface snowfall events. The observations of vertical profiles of reflectivity and Doppler-derived fall speeds are used in conjunction with the radiometric measurements to identify 1-D profiles of precipitation particle types, sizes, and concentrations that are consistent with the observations.

Description: © The Author(s), 2017. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Wildlife Society Bulletin 41 (2017): 666–677, doi:10.1002/wsb.820.

Description: Understanding patterns of habitat selection across a species’ geographic distribution can be critical for adequately managing populations and planning for habitat loss and related threats. However, studies of habitat selection can be time consuming and expensive over broad spatial scales, and a lack of standardized monitoring targets or methods can impede the generalization of site-based studies. Our objective was to collaborate with natural resource managers to define available nesting habitat for piping plovers (Charadrius melodus) throughout their U.S. Atlantic coast distribution from Maine to North Carolina, with a goal of providing science that could inform habitat management in response to sea-level rise. We characterized a data collection and analysis approach as being effective if it provided low-cost collection of standardized habitat-selection data across the species’ breeding range within 1–2 nesting seasons and accurate nesting location predictions. In the method developed, 〉30 managers and conservation practitioners from government agencies and private organizations used a smartphone application, “iPlover,” to collect data on landcover characteristics at piping plover nest locations and random points on 83 beaches and barrier islands in 2014 and 2015. We analyzed these data with a Bayesian network that predicted the probability a specific combination of landcover variables would be associated with a nesting site. Although we focused on a shorebird, our approach can be modified for other taxa. Results showed that the Bayesian network performed well in predicting habitat availability and confirmed predicted habitat preferences across the Atlantic coast breeding range of the piping plover. We used the Bayesian network to map areas with a high probability of containing nesting habitat on the Rockaway Peninsula in New York, USA, as an example application. Our approach facilitated the collation of evidence-based information on habitat selection from many locations and sources, which can be used in management and decision-making applications. © 2017 The Authors. Wildlife Society Bulletin published by Wiley Periodicals, Inc. on behalf of The Wildlife Society.

Description: U.S. Fish and Wildlife Service; U.S. Department of Interior Hurricane Sandy Recovery Program; North Atlantic Landscape Conservation Cooperative; U.S. Geological Survey Coastal and Marine Geology Program