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NASA NTRS1995

A mesoscale modeling study of the atmospheric circulation of high southern latitudes

The meteorology of high southern latitudes during winter is simulated using a cloud-free version of The Pennsylvania State University-National Center for Atmospheric Research Mesoscale Model version 4 (MM4) with a 100-km horizontal resolution. Comparisons between idealized simulations of Antarctic with MM4 and with the mesoscale model of Parish and Waight reveal that both models produce similarly realistic velocity fields in the boundary layer. The latter model tends to produce slightly faster drainage winds over East Antarctica. The intensity of the katabatic winds produced by MM4 is sensitive to parameterizations of boundary layer fluxes. Two simulations performed with MM4 using analyses from the European Center for Medium-Range Weather Forecasts (ECMWF) for June 1988 as initial and boundary conditions. A simulation of the period from 000 UTC 2 June to 0000 UTC 8 June produces realistic synoptic phenomena including ridge development over East Antarctica, frontogenesis over the Amundsen Sea, and a katabatic surge over the Ross Ice Shelf. The simulated time-averaged fields for June 1988, particularly that of a 500-hPa height, are in good agreement with time-averaged fields analyzed by the ECMWF. The results of the simulations provide detailed features of the Antarctic winter boundary layer along the steeply sloping terrain. Highest boundary layer wind speeds averaged over the month-long simulation are approximately 20 m/s. The lack of latent heating in the simulations apparently results in some bias in the results. In particular, the cloud-free version of MM4 underpredicts the intensity of lows in the sea level pressure field.

Hines, K. M.↗

DOE OSTI2025

Comparative analysis of thermal management systems in electric vehicles at extreme weather conditions: Case study on Nissan Leaf 2019 Plus, Chevrolet Bolt 2020 and Tesla Model 3 2020

With the surge in electric vehicle (EV) adoption and the need for extended driving ranges, optimizing energy efficiency, particularly through thermal management, is critical, especially in extreme weather. Managing the substantial energy needed for cabin climate control and battery temperature regulation can increase energy demands by over 50 %, severely limiting range. This study conducts a comparative analysis of thermal management systems (TMS) in three popular EV vehicles, 2020 Chevrolet Bolt, 2019 Nissan Leaf Plus, and 2020 Tesla Model 3, evaluating their distinct TMS configurations and performance under varied weather conditions. Using both numerical simulations and experimental data collected on a controlled test bench at Argonne National Laboratory, we assess how TMS architecture and operational modes influence energy consumption and range. A comprehensive TMS model was developed, integrating cabin and battery thermal sub-models in the Autonomie software platform, to simulate temperature fluctuations and range impacts. Cabin climate was modeled using a mono-zonal approach, while battery cell temperature distribution was estimated through a 2D nodal structure. Each vehicle's distinct TMS setup was evaluated: the Chevrolet Bolt and Tesla Model 3 use a dual evaporator vapor compression cycle with a PTC heater for the cabin and a coolant loop for battery thermal management; the Nissan Leaf Plus employs a heat pump with a PTC heater for the cabin and air-cooling for the battery. Tests conducted at ambient temperatures of 35°C, 22°C, -7°C, and -18°C reveal significant differences in energy use and range reduction across both configurations and conditions. At 35°C, the Tesla Model 3, Chevrolet Bolt, and Nissan Leaf Plus have a range reduction of 8%, 9%, and 13%, respectively, due to air conditioning. In winter, heating technology is paramount; at -7°C, the Nissan Leaf's heat pump configuration achieves a lower range reduction (19.3%) compared to the Tesla and Chevrolet Bolt PTC heaters, which reduce range by 28.3% and 31%, respectively. Further, this study provides valuable insights for automotive engineers, EV technology researchers, and thermal management system designers aiming to enhance electric vehicle performance by understanding how different weather conditions and TMS architectures impact energy consumption and driving range.

33 ADVANCED PROPULSION SYSTEMS↗

NASA NTRS2017

Meteorological Inventory of Rain-On-Snow Events in the Canadian Arctic Archipelago and Satellite Detection Assessment Using Passive Microwave Data

The spatial and temporal distributions of rain-on-snow (ROS) events across the Canadian Arctic Archipelago (CAA) remain poorly understood owing to their sporadic nature in time and space. This situation motivated the development of remote sensing detection algorithms. This paper uses a large meteorological dataset across the CAA to adapt an existing ROS-detection algorithm developed in a previous study by our group. Results highlight the spatial distribution and evolution of ROS occurrences reported since 1985 at 14 weather stations across the CAA. Results show that >600 ROS events were inventoried since 1985, for which >70% were classified as pure rain (liquid form) and 30% as mixed precipitation (solid/liquid). Of the pure rain events, 75% occurred during spring, 14% during fall, 8% during summer and <1% during winter. Such events can have significant impacts on ungulate grazing conditions through the creation of ice layers, causing serious problems for caribou calf survival, especially during the migration period. This paper introduces an adaptation for larger scale Arctic application of a detection algorithm (sensitivity analysis on the detection threshold) with an error of ~5%. The validation, however, remains limited due to a short study period and limited number of sites.

Canadian Arctic Archipelago (CAA)↗

NASA NTRS2007

Alaska at the Crossroads of Migration: Space Based Ornithology

Understanding bird migration on a global scale is one of the most compelling and challenging problems of modern biology with major implications for human health and conservation biology. Revolutionary advances in remote sensing now provide us with near real-time measurements of atmospheric and land surface conditions at high spatial resolution over entire continents. We use spatially-explicit, individual based bird migration models driven by numerical weather prediction models of atmospheric conditions, dynamic habitat suitability maps derived from remotely sensed land surface conditions, biophysiological models, and biological field data to simulate migration routes, timing, energy budgets, and survival of individual birds and populations. Long-distance migratory birds travel annually between breeding grounds in Alaska and wintering grounds in Latin Amierica. Approximately 25% of these species are potential vectors of Avian Influenza. Alaska is at the crossroads of Asian and New World migratory flyways and is likely to be a point of introduction of Asian H5N1 AI into the western hemisphere. If/when an infected bird is detected, a pressing question will be where was this bird several days ago, and where is it likely to go after it was released from the survey site? Answers to such questions will increase effectiveness of AI surveillance and mitigation measures. From a conservation perspective, Alaska's diverse landscape provides breeding sites for many migrants, and climatic and land surface changes along migratory flyways in the western hemisphere may reduce bird survival and physical condition upon arrival at Alaskan breeding territories, success and migrant populations.

Deppe, Jill↗

NASA NTRSDate not supplied

Cubespark: A New Satellite-Based 3d Lightning Observing Concept

Legacy and current space-based optical lightning detectors are insensitive to small and dim pulses that make up much of the lightning activity produced by severe storms. Moreover, lightning flashes produced at low altitudes within optically thick clouds are severely under-detected by current optical detectors. Lastly, there is currently no capability to characterize the 3D structure of lightning both day and night at the global scale, yet this information is critical for identifying lightning produced in updraft regions, including lightning occurring in overshooting tops, which is a distinctive signature of severe weather. Global 3D lightning information is also critical for understanding the vertical distribution of NOx production and identifying anomalously electrified storms. Furthermore, the vertical distribution of lightning has implications for how microphysical (e.g., ice-based) and thermodynamical (e.g., latent heat release) processes vary regionally, as well as seasonally – e.g., winter lightning typically occurs at lower altitudes than summer lightning and is often associated with tall, man-made structures. Finally, global-scale 3D lightning observations would directly provide flash type (i.e., CG or IC) information that is very useful in all of the studies mentioned in this paragraph and is fundamental in identifying/documenting deleterious CG-caused impacts (e.g., wildfires, power-outages, crop and property damage, and associated insurance claims). A new, satellite mission concept called CubeSpark is being designed to address these shortcomings and fill this measurement gap by providing novel 3D observations of total lightning activity. CubeSpark will utilize a constellation of low-Earth orbiting small satellites that make radio frequency (RF) and bi-spectral optical measurements of lightning. Two options for combining these measurements to retrieve the 3D location of lightning are considered with corresponding measurement simulators built to understand the level of detail and viability of each approach. Although the level of detail varies for each combined measurement approach, results indicate that a 3D location accuracy of < 1-2 km in each dimension is feasible across 300-500 km wide swaths, which suggests that CubeSpark can resolve the charge structure of thunderclouds from the tropics to the mid- and high-latitudes.

lightning↗

NASA NTRS2000

Accuracy of Modelled Stratospheric Temperatures in the Winter Arctic Vortex from Infra Red Montgolfier Long Duration Balloon Measurements

The temperature of the stratosphere has been measured in the Arctic vortex every 9-10 minutes along the trajectory of four Infra Red Montgolfier long duration balloons flown for 7 to 22 days during the winters of 1997 and 1999. From a number of comparisons to independent sensors, the accuracy of the measurements is demonstrated to be plus or minus 0.5 K during nighttime and at altitude below 28 km (10 hPa). The performances of the analyses of global meteorological models, European Center for Medium Range Weather Forecasts (ECMWF) 31 and 50 levels, United Kingdom Meteorological Office (UKMO), Data Assimilation Office (DAO), National Climatic Prediction Center (NCEP) and NCEP/NCAR reanalysis, used in photochemical simulations of ozone destruction and interpretation of satellite data, are evaluated by comparison to this large (3500 data points) and homogeneous experimental data set. Most of models, except ECMWF31 in 1999, do show a smal1 average warm bias of between 0 and 1.6 K, with deviations particularly large, up to 20 K at high altitude (5hPa) in stratospheric warming conditions in 1999. Particularly wrong was ECMWF 31 levels near its top level at 10 hPa in 1999 where temperature 25 K colder than the real atmosphere were reported. The average dispersion between models and measurements varies from plus or minus 1.0 to plus or minus 3.0 K depending on the model and the year. It is shown to be the result of three contributions. The largest is a long wave modulation likely caused by the displacement of the temperature field in the analyses compared to real atmosphere. The second is the overestimation of the vertical gradient of temperature particularly in warming conditions, which explains the increase of dispersion from 1997 to 1999. Unexpectedly, the third and smallest (plus or minus 0.6-0.7 K) is the contribution of meso and subgrid scale vertical and horizontal features associated to the vertical propagation of orographic or gravity waves. Compared to other models, the newly available ECMWF 50 levels version assimilating the high vertical resolution radiances of the space borne Advanced Microwave Sounding Unit, performs significantly better (0.03 plus or minus 1.12 K on average between 10 and 140 hPa in 1999) than other models.

Pommereau, J.-P.↗

NASA NTRS2001

Seasonal and Interannual Variations of Ice Sheet Surface Elevation at the Summit of Greenland: Observed and Modeled

Observed seasonal and interannual variations in the surface elevation over the summit of the Greenland ice sheet are modeled using a new temperature-dependent formulation of firn-densification and observed accumulation variations. The observed elevation variations are derived from ERS (European Remote Sensing)-1 and ERS-2 radar altimeter data for the period between April 1992 and April 1999. A multivariate linear/sine function is fitted to an elevation time series constructed from elevation differences measured by radar altimetry at orbital crossovers. The amplitude of the seasonal elevation cycle is 0.25 m peak-to-peak, with a maximum in winter and a minimum in summer. Inter-annually, the elevation decreases to a minimum in 1995, followed by an increase to 1999, with an overall average increase of 4.2 cm a(exp -1) for 1992 to 1999. Our densification formulation uses an initial field-density profile, the AWS (automatic weather station) surface temperature record, and a temperature-dependent constitutive relation for the densification that is based on laboratory measurements of crystal growth rates. The rate constant and the activation energy commonly used in the Arrhenius-type constitutive relation for firn densification are also temperature dependent, giving a stronger temperature and seasonal amplitudes about 10 times greater than previous densification formulations. Summer temperatures are most important, because of the strong non-linear dependence on temperature. Much of firn densification and consequent surface lowering occurs within about three months of the summer season, followed by a surface build-up from snow accumulation until spring. Modeled interannual changes of the surface elevation, using the AWS measurements of surface temperature and accumulation and results of atmospheric modeling of precipitation variations, are in good agreement with the altimeter observations. In the model, the surface elevation decreases about 20 cm over the seven years due to more compaction driven by increasing summer temperatures. The minimum elevation in 1995 is driven mainly by a temporary accumulation decrease and secondarily by warmer temperatures. However, the overall elevation increase over the seven years is dominated by the accumulation increase in the later years.

Zwally, H. Jay↗

DOE OSTI2025

The Two Arctic Wintertime Boundary Layer States: Disentangling the Role of Cloud and Wind Regimes in Reanalysis and Observations During MOSAiC

The wintertime central Arctic atmosphere comprises a radiatively clear and a radiatively opaque state, which are linked to synoptic forcing and mixed-phase clouds. Weather and climate models often lack process representations surrounding these states, but prior work mostly treated the problem as an aggregate of synoptic conditions, resulting in partially overlapping biases. Here, we disaggregate the Arctic states and confront ERA5 reanalysis with observations from the MOSAiC campaign over the central Arctic sea ice during winter 2019/2020. Low-level winds and liquid water path (LWP) are combined to derive different synoptic classes. Results show that the clear state is primarily formed by weak/moderate winds and the absence of liquid-bearing clouds, while strong winds and enhanced LWP primarily form the radiatively opaque state. ERA5 struggles to reproduce these basic statistics, shows too weak sensitivity of thermal radiation to synoptic forcing, and overestimates thermal radiation for similar LWP amounts. The latter is caused by a warm bias, which has a pronounced inversion structure and is largest in clear and calm conditions. Under strong synoptic forcing, the warm bias is constant with height and discrepancies in mixed-phase cloud altitude appear. Separating synoptic conditions is regarded as useful for process-oriented evaluation of the Arctic troposphere in models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Using long‐term data from a whole ecosystem warming experiment to identify best spring and autumn phenology models

Abstract Predicting vegetation phenology in response to changing environmental factors is key in understanding feedbacks between the biosphere and the climate system. Experimental approaches extending the temperature range beyond historic climate variability provide a unique opportunity to identify model structures that are best suited to predicting phenological changes under future climate scenarios. Here, we model spring and autumn phenological transition dates obtained from digital repeat photography in a boreal Picea ‐ Sphagnum bog in response to a gradient of whole ecosystem warming manipulations of up to +9°C, using five years of observational data. In spring, seven equally best‐performing models for Larix utilized the accumulation of growing degree days as a common driver for temperature forcing. For Picea , the best two models were sequential models requiring winter chilling before spring forcing temperature is accumulated. In shrub, parallel models with chilling and forcing requirements occurring simultaneously were identified as the best models. Autumn models were substantially improved when a CO 2 parameter was included. Overall, the combination of experimental manipulations and multiple years of observations combined with variation in weather provided the framework to rule out a large number of candidate models and to identify best spring and autumn models for each plant functional type.

Schädel, Christina↗

NASA NTRS1998

Characterization of Mesoscale Convective Systems by Means of Composite Radar Reflectivity Data

A mesoscale convective system (MCS) is broadly defined as a cloud and precipitation system of mesoscale dimensions (often too large for most aircraft to circumnavigate) with deep-convective activity concentrated in at least part of the MCS, or present during part of its evolution. A large areal fraction of MCSs is stratiform in nature, yet estimates from MCSs over the Great Plains, the Southeast, and tropical waters indicate that at least half of the precipitation is of convective origin. The presence of localized convection is important, because within convective towers cloud particles and hydrometeors are carried upward towards the cloud top. Ice crystals then move over more stratiform regions, either laterally, or through in situ settling over decaying and spreading convection. These ice crystals then grow to precipitation-size particles in mid- to upper tropospheric mesoscale updrafts. The convective portion of a MCS is often a more or less continuous line of thunderstorms, and may be either short-lived or long-lived. Geerts (1997) presents a preliminary climatology of MCSs in the southeastern USA, using just one year of composite digital radar reflectivity data. In this study MCSs are identified and characterized by means of visual inspection of animated images. A total of 398 MCSs were identified. In the warm season MCSs were found to be about twice as frequent as in the cold season. The average lifetime and maximum length of MCSs are 9 hours, and 350 km, respectively, but some MCSs are much larger and more persistent. In the summer months small and short-lived MCSs are relatively more common, whereas in winter larger and longer-lived systems occur more frequently. MCSs occur more commonly in the afternoon, in phase with thunderstorm activity, but the amplitude of the diurnal cycle is small compared to that of observed thunderstorms. It is estimated that in the Southeast more than half of all precipitation and severe weather results from MCSs.

Geerts, Bart↗

DOE OSTI2023

Evaluation of an open forecasting challenge to assess skill of West Nile virus neuroinvasive disease prediction

Abstract Background West Nile virus (WNV) is the leading cause of mosquito-borne illness in the continental USA. WNV occurrence has high spatiotemporal variation, and current approaches to targeted control of the virus are limited, making forecasting a public health priority. However, little research has been done to compare strengths and weaknesses of WNV disease forecasting approaches on the national scale. We used forecasts submitted to the 2020 WNV Forecasting Challenge, an open challenge organized by the Centers for Disease Control and Prevention, to assess the status of WNV neuroinvasive disease (WNND) prediction and identify avenues for improvement. Methods We performed a multi-model comparative assessment of probabilistic forecasts submitted by 15 teams for annual WNND cases in US counties for 2020 and assessed forecast accuracy, calibration, and discriminatory power. In the evaluation, we included forecasts produced by comparison models of varying complexity as benchmarks of forecast performance. We also used regression analysis to identify modeling approaches and contextual factors that were associated with forecast skill. Results Simple models based on historical WNND cases generally scored better than more complex models and combined higher discriminatory power with better calibration of uncertainty. Forecast skill improved across updated forecast submissions submitted during the 2020 season. Among models using additional data, inclusion of climate or human demographic data was associated with higher skill, while inclusion of mosquito or land use data was associated with lower skill. We also identified population size, extreme minimum winter temperature, and interannual variation in WNND cases as county-level characteristics associated with variation in forecast skill. Conclusions Historical WNND cases were strong predictors of future cases with minimal increase in skill achieved by models that included other factors. Although opportunities might exist to specifically improve predictions for areas with large populations and low or high winter temperatures, areas with high case-count variability are intrinsically more difficult to predict. Also, the prediction of outbreaks, which are outliers relative to typical case numbers, remains difficult. Further improvements to prediction could be obtained with improved calibration of forecast uncertainty and access to real-time data streams (e.g. current weather and preliminary human cases). Graphical Abstract

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2004

Thermal Structure of the TTL and Its Relation to Stratospheric-Tropospheric Exchange of Water

This document describes the annual cycle of the trajectory track line (TTL) fine scale thermal structure as captured by global positioning system (GPS) radio occultation and the pressure levels of the East Meets West Foundation (EMWF) weather analysis. This annual cycle is compared to the annual cycle in water concentrations measured by the HALogen Occultation Experiment (HALOE). A comparison between saturation mixing ratios at the temperatures captured by GPS radio occultation and HALOE concentrations of water vapor shows an annual cycle that is dominated by supersaturation in the boreal winter months, when the upward mass fluxes are larger, and subsaturation in the summer. The longitudinal dependence of these cycles is discussed as well as the possible implications for the seasonality of stratospheric-troposheric exchanges of water.

climates↗

NASA NTRSDate not supplied

Observing Ice Phase Clouds and Precipitation with Millimeter- and Submillimeter-wave Radiometry during the IMPACTS field campaign: Algorithm Development for the Emerging Class of Microwave Radiometers

Millimeter- and submillimeter-wave (mmWave, submm) radiometers provide significant information content on atmospheric water in liquid, ice, and vapor phases. Recent sensors, such as the Global Precipitation Measurement (GPM) or the Temporal Experiment for Storms and Tropical Systems Technology – Demonstration (TEMPEST-D), use mmWave bands to improve estimation of ice-phase precipitation, and future missions, such as the Atmosphere Observing System (AOS), will extend to submm to provide additional information on thinner ice clouds, linking clouds and precipitation and therefore elucidating the links between weather, climate, and the water cycle. To support the expanded use of mmWave/submm radiometry and exploit the available information content on condensed water mass, we demonstrate ice and liquid water path retrievals for NASA Goddard Space Flight Center's airborne radiometers the Conical Scanning Millimeter-wave Imaging Radiometer (CoSMIR) and the Configurable Scanning Submillimeter-wave Instrument/Radiometer (CoSSIR, formerly the Compact Scanning Submillimeter Imaging Radiometer). The analysis is based on data collected during the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Storms (IMPACTS) field campaign. A simulation study compares and contrasts retrievals for CoSMIR and CoSSIR, with CoSSIR demonstrating higher skill in ice retrievals, particularly for thin clouds, and the CoSMIR frequencies performing better for liquid. Additionally, we look at dual-polarized radiances observed by CoSMIR during the first two IMPACTS deployments to understand the polarization signatures induced by oriented hydrometeors. Results will be presented in the context of upcoming missions and sensors including AOS and the Ice Cloud Imager (ICI). We will describe the objectives for the expected first flight of the newly upgraded CoSSIR during the final IMPACTS deployment, and we will share novel science investigations we plan to undertake with CoSSIR's new capabilities. Popular Summary: Ice in clouds and falling snow is an important component of weather, climate, and water resources. To better use a new class of sensors that provide information on atmospheric ice, we developed an approach to measure ice clouds and falling snow using airborne data taken during the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Storms (IMPACTS), a field campaign to study winter storms. We look at the results for two similar instruments to understand how those differences affect these measurements of clouds and snow, and we further investigate the information the sensors can provide on properties of the clouds and snow.

Ian S Adams↗

NASA NTRSDate not supplied

Observing Ice Phase Clouds and Precipitation with Millimeter- and Submillimeter-wave Radiometry during the IMPACTS field campaign: Algorithm Development for the Emerging Class of Microwave Radiometers

Ian S Adams↗

DOE OSTI2022

Floating Island International PHASE I FINAL TECHNICAL REPORT (Advancing the Development of Floating Solar-Powered Nanobubble Aeration Systems for Use with Floating Treatment Wetlands in Natural and Man-Made Waterbodies)

More and more freshwater lakes are suffering from algae blooms, which deprive water of oxygen and lead to widespread loss of aquatic life and production of dangerous toxins. When oxygen is lacking, methane is generated in the sediments as algae is decomposed; it has been calculated that more than half of global methane emissions come from nutrient-impaired freshwater systems (Beaulieu, 2021). Nutrients, mainly from agricultural run-off, feed algae blooms and are exacerbated by warming related to climate change. Artificial aeration is frequently used to restore oxygen to a waterbody. But diffuser aeration is inefficient and expensive, needs on-site grid power, and is failing to keep pace with the demands of water as it gets warmer with climate change. In the last five years, nanobubble aeration has been introduced into freshwater applications and shows promise for rapidly increasing dissolved oxygen effectively throughout the water column. Nanobubbles deliver oxygen in bubbles that have no buoyancy, so they stay in water longer and release their oxygen more fully, compared to large bubbles that rise and burst at the surface. The prospect of this new technology answering the deficiencies of diffuser aeration drove us to initiate the current project. During our Phase I period, we have successfully tested a nanobubble aeration system that can super-saturate oxygen levels. It is operated on solar power, and both the nanobubbler and solar array are mounted on a proprietary floating island platform, that also performs biological nutrient recycling. A rudimentary system was assembled and tested on a 6.5-acre research lake at our headquarters in Montana, where it was subjected to a summer drought that reduced water levels significantly, periods of severe cold in winter, and spring conditions that included heavy rainfall and violent thunderstorms. Our twice-weekly sampling throughout the project showed that dissolved oxygen levels rose rapidly and were maintained throughout winter and spring, well into June. The nanobubbler was able to run on solar power for long periods. Methane levels were tested periodically and found to decrease as oxygen increased. The nanobubbles appeared to have no adverse impact on fish or other aquatic life exposed to them. The stability of the installation survived the weather conditions. The many problems we encountered taught us what we need to improve in the next iteration. Towards the end of our Phase I, we were awarded a supplementary state grant that enabled us to acquire a new nanobubble system for testing that runs on DC, is extremely efficient and has few moving parts. We plan to team this with low-profile solar panels, lithium batteries and a controller that provides real-time data. The ultimate goal of this project is to commercialize an affordable and scalable lake management system that will oxygenate water from the surface down to the sludge. It will enliven fisheries, prevent toxic algae blooms and – most importantly for the fate of our planet - inhibit the production and release of methane from the sediments. We anticipate that as carbon credits expand to include methane, the cost of remediating waterbodies that produce methane will be offset. We firmly believe that this is a practical technology that works and will make a big difference when fully implemented.

14 SOLAR ENERGY↗

NASA NTRS1975

Remote profiling of lake ice using an S-band short-pulse radar aboard an all-terrain vehicle

The airborne short-pulse radar system described was developed to measure ice thickness in an attempt to extend the winter navigation system as a means of reducing coal and ore shipping costs. Experimental studies of the accuracy and limitations of the system are discussed, and measurements made at 25 sites are compared. The radar system was found to provide accurate lake ice thickness measurements that were not affected by snow cover or adverse weather conditions. Surface melting and rain, however, preclude measurements.

Cooper, D. W.↗

NASA NTRS1992

Joint NASA/USAF Airborne Field Mill Program - Operation and safety considerations during flights of a Lear 28 airplane in adverse weather

A NASA Langley Research Center Learjet 28 research airplane was flown in various adverse weather conditions in the vicinity of the NASA Kennedy Space Center from 1990-1992 to measure airborne electric fields during the Joint NASA/USAF Airborne Field Mill Program. The objective of this program was to characterize the electrical activity in various weather phenomena common to the NASA-Kennedy area in order to refine Launch Commit Criteria for natural and triggered lightning. The purpose of the program was to safely relax the existing launch commit criteria, thereby increasing launch availability and reducing the chance for weather holds and delays. This paper discusses the operational conduct of the flight test, including environmental/safety considerations, aircraft instrumentation and modification, test limitations, flight procedures, and the procedures and responsibilities of the personnel in the ground station. Airborne field mill data were collected for all the Launch Commit Criteria during two summer and two winter deployments. These data are now being analyzed.

Fisher, Bruce D.↗

NASA NTRS1994

Global surface-based cloud observation for ISCCP

Visual observations of cloud cover are hindered at night due to inadequate illumination of the clouds. This usually leads to an underestimation of the average cloud cover at night, especially for the amounts of middle and high clouds, in climatologies on surface observations. The diurnal cycles of cloud amounts, if based on all the surface observations, are therefore in error, but they can be obtained more accurately if the nighttime observations are screened to select those made under sufficient moonlight. Ten years of nighttime weather observations from the northern hemisphere in December were classified according to the illuminance of moonlight or twilight on the cloud tops, and a threshold level of illuminance was determined, above which the clouds are apparently detected adequately. This threshold corresponds to light from a full moon at an elevation angle of 6 degrees or from a partial moon at higher elevation, or twilight from the sun less than 9 degrees below the horizon. It permits the use of about 38% of the observations made with the sun below the horizon. The computed diurnal cycles of total cloud cover are altered considerably when this moonlight criterion is imposed. Maximum cloud cover over much of the ocean is now found to be at night or in the morning, whereas computations obtained without benefit of the moonlight criterion, as in our published atlases, showed the time of maximum to be noon or early afternoon in many regions. Cloud cover is greater at night than during the day over the open oceans far from the continents, particularly in summer. However, near noon maxima are still evident in the coastal regions, so that the global annual average oceanic cloud cover is still slightly greater during the day than at night, by 0.3%. Over land, where daytime maxima are still obtained but with reduced amplitude, average cloud cover is 3.3% greater during the daytime. The diurnal cycles of total cloud cover we obtain are compared with those of ISCCP for a few regions; they are generally in better agreement if the moonlight criterion is imposed on the surface observations. Using the moonlight criterion, we have analyzed ten years (1982-1991) of surface weather observations over land and ocean, worldwide, for total cloud cover and for the frequency of occurrence of clear sky, fog and precipitation The global average cloud cover (average of day and night) is about 2% higher if we impose the moonlight criterion than if we use all observations. The difference is greater in winter than in summer, because of the fewer hours of darkness in the summer. The amplitude of the annual cycle of total cloud cover over the Arctic Ocean and at the South Pole is diminished by a few percent when the moonlight criterion is imposed. The average cloud cover for 1982-1991 is found to be 55% for northern hemisphere land, 53% for southern hemisphere land, 66% for northern hemisphere ocean, and 70% for southern hemisphere ocean, giving a global average of 64%. The global average for daytime is 64.6% for nighttime 63.3%.

Source record↗