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At least 163 records · Page 9

The Global Distribution of Precipitation and Clouds

The water cycle is the key circuit moving water through the Earth's system. This large system, powered by energy from the sun, is a continuous exchange of moisture between the oceans, the atmosphere, and the land. Precipitation (including rain, snow, sleet, freezing rain, and hail), is the primary mechanism for transporting water from the atmosphere back to the Earth's surface and is the key physical process that links aspects of climate, weather, and the global water cycle. Global precipitation and associate cloud processes are critical for understanding the water cycle balance on a global scale and interactions with the Earth's climate system. However, unlike measurement of less dynamic and more homogenous meteorological fields such as pressure or even temperature, accurate assessment of global precipitation is particularly challenging due to its highly stochastic and rapidly changing nature. It is not uncommon to observe a broad spectrum of precipitation rates and distributions over very localized time scales. Furthermore, precipitating systems generally exhibit nonhomogeneous spatial distributions of rain rates over local to global domains.

Shepherd, J. Marshall↗

TAMDAR Sensor Validation in 2003 AIRS II

This study entails an assessment of TAMDAR in situ temperature, relative humidity and winds sensor data from seven flights of the UND Citation II. These data are undergoing rigorous assessment to determine their viability to significantly augment domestic Meteorological Data Communications Reporting System (MDCRS) and the international Aircraft Meteorological Data Reporting (AMDAR) system observational databases to improve the performance of regional and global numerical weather prediction models. NASA Langley Research Center participated in the Second Alliance Icing Research Study from November 17 to December 17, 2003. TAMDAR data taken during this period is compared with validation data from the UND Citation. The data indicate acceptable performance of the TAMDAR sensor when compared to measurements from the UND Citation research instruments.

Daniels, Taumi S.↗

Assessments of Total Lightning Data Utility in Weather Forecasting

National Weather Service forecasters in Huntsville, Alabama have had access to total lightning data from the North Alabama Lightning Mapping Array (LMA) since 2003. Forecasters can monitor real-time total lightning observations on their AWIPS (Advanced Weather Interactive Processing System (AWIPS) workstations. The lightning data is used to supplement other observations such as radar and satellite data. The lightning data is updated every 2 min, providing more timely evidence of storm growth or decay than is available from 5 min radar scans. Total lightning observations have been used to positively impact warning decisions in a number of instances. A number of approaches are being pursued to assess the usefulness of total lightning measurements to the operational forecasting community in the warning decision process. These approaches, which include both qualitative and quantitative assessment methods, will be discussed. submitted to the American Meteorological Society (AMS) Conference on Meteorological Applications of Lightning Data to be held in San Diego, CA January 9-13,2005. This will be a presentation and an extended abstract will be published on a CD available from the AMS.

Buechler, Dennis E.↗

Severe Weather Forecast Decision Aid

The Applied Meteorology Unit developed a forecast tool that provides an assessment of the likelihood of local convective severe weather for the day in order to enhance protection of personnel and material assets of the 45th Space Wing Cape Canaveral Air Force Station (CCAFS), and Kennedy Space Center (KSC).

Bauman, William H., III↗

Description and Status of the DC Lightning Mapping Array

The DC Lightning Mapping Array (DC LMA) centered on the Washington, DC metro region has been in operation since 2006. During that time the DC LMA has provided real time data to regional National Weather Service (NSF) Sterling, VA forecast office for operations support and the NOAA Meteorological Development Laboratory (MDL) for new product development and assessment. Data from this network (as well as other from other LMA systems) are now being used to create proxy Geostationary Lightning Mapper (GLM) data sets for GOES-R risk reduction and algorithm development activities. In addition, since spring 2009 data are provided to the Storm Prediction Center in support of Hazardous Weather Testbed and GOES-R Proving Ground activities during the Spring Program. Description, status and plans will be discussed.

Blakeslee, Richard↗

Earth Energy Balance Assessment at the 2022 BIPM-WMO Metrology for Climate Action Workshop

The BIPM and WMO hosted a five-day workshop in Sept. 2022 to assess the state of current metrology and identify future meteorological needs regarding climate change for the upcoming decade. A resulting broad policy-oriented workshop summary report, written by the workshop’s ~70 international organizers and reviewed by meeting attendees, identifies the current issues in each of nine high-level topic areas and provides recommendations to address them, listing specific needs, pathways, timelines, and responsible agencies or organizations for each. One prominent Topic within the workshop, “Earth Energy Balance,” was organized by the authors of this presentation and resulted in a section of the workshop summary report using the contributions from the topic’s several pre-recorded oral and poster presentations and the outcomes of two interactive real-time community-wide discussion sessions. The Earth-energy-balance topic issues centered on three areas: Radiometric energy measurements, including needed accuracies and stabilities and the use of SI-Traceable Satellites (SITSats), such as CLARREO and TRUTHS, to achieve them; improved on-orbit calibration sources, including the Sun and the Moon, thermal-infrared and UV sources, and space-flight blackbodies; and the four primary Earth-heat storage reservoirs of the oceans, land, permafrost, and cryosphere, giving an inventory of where and how much of the Earth’s energy is stored and how much uptake there is of the incoming energy. This presentation will summarize the results of the Earth Energy Balance topic from the 2022 BIPM-WMO Metrology for Climate Action Workshop.

earth↗

Computer simulations of space-borne meteorological systems on the CYBER 205

Because of the extreme expense involved in developing and flight testing meteorological instruments, an extensive series of numerical modeling experiments to simulate the performance of meteorological observing systems were performed on CYBER 205. The studies compare the relative importance of different global measurements of individual and composite systems of the meteorological variables needed to determine the state of the atmosphere. The assessments are made in terms of the systems ability to improve 12 hour global forecasts. Each experiment involves the daily assimilation of simulated data that is obtained from a data set called nature. This data is obtained from two sources: first, a long two-month general circulation integration with the GLAS 4th Order Forecast Model and second, global analysis prepared by the National Meteorological Center, NOAA, from the current observing systems twice daily.

Halem, M.↗

Developing A Continuous Ozone Record Through the SAGE and Aura Missions With NASA Reanalysis Products

During the last quarter of the 20th century, the Stratospheric Aerosol and Gas Experiment (SAGE) missions were crucial in monitoring the loss and subsequent recovery of the stratospheric ozone layer. Due to the employed solar occultation and self-calibration method, the SAGE monitors have produced stable data throughout the lifetime of each instrument. However, over ten years passed between the end of the SAGE II and SAGE III/M3M missions in 2005 and the launch of SAGE III/ISS instrument in 2017, leaving a gap in the data that must be bridged in order to assess trends in the ozone record. The Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) reanalysis product, with output available starting in 1980, is an attractive candidate for trend analysis due to the statistically optimized combination of multiple observing systems and the regular temporal and spatial coverage. However, changes in the assimilated observation systems can introduce discontinuities within the MERRA-2 ozone record, such as in 2004 when the MERRA-2 system shifted from assimilating ozone retrievals collected by SBUV instruments to those collected by instruments onboard the Aura satellite. In this study, we explore using the SAGE II record as a transfer function to develop a stable reanalysis data product, suitable for trend analysis, from the start of the SAGE II record in 1984 through the present. We follow the procedure outlined by Wargan et al. (2018) to address discontinuities in the MERRA-2 ozone dataset at the 2004 transition and during the Aura record. SAGE II ozone profiles are used to correct discontinuities in upper stratospheric ozone associated with changes in the MERRA-2 meteorological observing system in 1998 and 1995. We will then assess the relative performance of the data from different SAGE sensors using the resulting bias-corrected MERRA-2 ozone fields.

Pamela Wales↗

Role of Temperature, Humidity and Rainfall on Influenza Transmission in Guatemala, El Salvador and Panama

Worldwide, seasonal influenza causes about 500,000 deaths and 5 million severe illnesses per year. The environmental drivers of influenza transmission are poorly understood especially in the tropics. We aimed to identify meteorological factors for influenza transmission in tropical Central America. We gathered laboratory-confirmed influenza case-counts by week from Guatemala City, San Salvador Department (El Salvador) and Panama Province from 2006 to 2010. The average total cases per year were: 390 (Guatemala), 99 (San Salvador) and 129 (Panama). Meteorological factors including daily air temperature, rainfall, relative and absolute humidity (RH, AH) were obtained from ground stations, NASA satellites and land models. For these factors, we computed weekly averages and their deviation from the 5-yr means. We assessed the relationship between the number of influenza case-counts and the meteorological factors, including effects lagged by 1 to 4 weeks, using Poisson regression for each site. Our results showed influenza in San Salvador would increase by 1 case within a week of every 1 day with RH>75% (Relative Risk (RR)= 1.32, p=.001) and every 1C increase in minimum temperature (RR=1.29, p=.007) but it would decrease by 1 case for every 1mm-above mean weekly rainfall (RR=0.93,p<.001) (model pseudo-R2=0.55). Within 2 weeks, influenza in Panama was increased by 1 case for every 1% increase in RH (RR=1.04, p=.003), and it was increased by 2 cases for every 1C increase of minimum temperature (RR=2.01, p<.001) (model pseudo-R2=0.4). Influenza counts in Guatemala had 1 case increase for every 1C increase in minimum temperature in the previous week (RR=1.21, p<.001), and for every 1mm/day-above normal increase of rainfall rate (RR=1.03, p=.03) (model pseudo-R2=0.54). Our findings that cases increase with temperature and humidity differ from some temperate-zone studies. But they indicate that climate parameters such as humidity and temperature could be predictive of influenza activity and should be incorporated into country-specific influenza transmission models

Soebiyanto, Radina P.↗

Statistical framework to assess long-term spatio-temporal climate changes: East River mountainous watershed case study

Abstract Evaluation of long-term temporal and spatial climatic change in mountainous regions is a critical challenge because of the interactive effects of multiple land and climatic factors and processes. Here we present the application of the statistical framework to the assessment of changes of climatic conditions, using data from 17 meteorological stations across the East River watershed near Crested Butte, Colorado, USA, and spanning the period from 1966 to 2021. The framework is developed based on (1) a time-series analysis of daily, monthly, and yearly averaged meteorological parameters (temperature, relative humidity, precipitation, wind speed, etc.), (2) evaluation and time series analysis of potential evapotranspiration (ET o ), actual evapotranspiration (ET), aridity index (AI), standard precipitation index (SPI) and standard precipitation-evapotranspiration index (SPEI), and (3) a temporal-spatial climatic zonation of the studied area based on the hierarchical clustering and PCA analysis of the SPEI, because the SPEI can be considered an integrative characteristic of the changes of climatic conditions. The Budyko model, with the application of the Penman–Monteith equation for the estimation of ET o , was used to determine the ET. The time series analysis of the AI is used to identify the periods with energy limited and water limited conditions. Hierarchical clustering of site locations for the three temporal segments of the SPEI showed a significant temporal-spatial shifts, indicating that dynamic climatic processes drive zonation patterns. Therefore, the watershed climatic zonation requires periodic re-evaluation based on the structural time series analysis of meteorological and water balance data.

54 ENVIRONMENTAL SCIENCES↗

A review of future weather data for assessing climate change impacts on buildings and energy systems

The effectiveness of climate change impact assessments and the development of adaptation strategies depend on the availability of high-quality future weather data. However, significant gaps exist between the needs of the energy research community and the focus of the climate modeling community, primarily due to a historical lack of communication and collaboration between the two groups. Here, to address this issue, this work provides a comprehensive overview of the critical aspects involved in creating future weather data for building and energy system modeling, including emissions scenarios, general circulation models, downscaling methods, categories of future weather data, and uncertainties in climate simulations. Moreover, it critically evaluates the applicability and suitability of various types of future weather data in five key application scenarios: energy use analysis, resilience analysis, HVAC design, utility-scale analysis, and renewable energy analysis. Finally, this work presents recommendations for high-level actions and research directions to foster collaboration between the energy research and climate modeling communities and to promote the integration of future weather data into energy codes and the design practices of buildings and energy systems.

Climate change↗

Arctic Observing Experiment (AOX) Field Campaign Report

Our ability to understand and predict weather and climate requires an accurate observing network. One of the pillars of this network is the observation of the fundamental meteorological parameters: temperature, air pressure, and wind. We plan to assess our ability to measure these parameters for the polar regions during the Arctic Observing Experiment (AOX, Figure 1) to support the International Arctic Buoy Programme (IABP), the Arctic Observing Network (AON), the International Program for Antarctic Buoys (IPAB), and the Southern Ocean Observing System (SOOS). Accurate temperature measurements are also necessary to validate and improve satellite measurements of surface temperature across the Arctic.

54 ENVIRONMENTAL SCIENCES↗

High-Resolution ESM Projections for Energy Applications Over the CONUS

Assessing energy resources under future scenarios requires high-resolution meteorological information that is physically consistent and suitable for regional-scale analysis. While Earth system model (ESM) projections provide valuable large-scale information, their coarse resolution and systematic biases limit direct applicability for energy system modeling and planning. In this study, we develop a high-resolution dynamical downscaling framework based on the Weather Research and Forecasting (WRF) model to translate global-scale ESM data into energy-relevant regional projections over the contiguous United States (CONUS). The framework identifies an optimized WRF configuration through numerical experiments and evaluates raw and bias-corrected ESM initial and boundary conditions, with soil moisture (SM) and soil temperature (ST) bias correction implemented as an integral part of the bias-corrected ESM forcing to improve land-atmosphere coupling prior to WRF dynamical downscaling. Using an optimized WRF configuration at 4-km resolution, we show that raw ESM forcing introduces systematic dry and cold soil biases that propagate into pronounced warm biases in near-surface air temperature and positive biases in solar irradiance, particularly during summer. Applying bias-corrected atmospheric forcing together with bias-corrected SM and ST substantially reduces these downstream biases and improves the surface energy balance and near-surface atmospheric fields. These results demonstrate that bias-aware treatment of initial conditions is critical for producing high-resolution downscaled projections suitable for energy system modeling and planning applications.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Wind profiler demonstration system

The National Oceanic and Atmospheric Administration (NOAA) has started procurement of a 30-station demonstration network of Doppler radar wind profilers to be deployed in the central United States by 1989. The purposes of this demonstration network are: (1) to assess the impact of a large wind profiler network on meteorological forecasting; (2) to test wind profiler hardware designed specifically for commercial production and widespread deployment; and (3) to provide wind data for research programs involving weather phenomena in the central United States.

Chadwick, R. B.↗

Mechanical and hydrologic basis for the rapid motion of a large tidewater glacier. 1: Observations

Measurements of glacier flow velocity and basal water pressure at two sites on Columbia Glacier, Alaska, are combined with meteorological and hydrologic data to provide an observational basis for assessing the role of water storage and basal water pressure in the rapid movement of this large glacier. During the period from July 5 to August 31, 1987, coordinated observations were made of glacier surface motion and of water level in five boreholes drilled to (or in one case near to) the glacier bed at two sites, 5 and 12 km from the terminus. Glacier velocities increased downglacier in this reach from about 4 m/d to about 7 m/d. Three types of time variation in velocity and other variables were revealed: (1) Diurnal fluctuation in water input/output, borehole water level, and ice velocity (fluctuation amplitude 5 to 8%); (2) Speed-up events in glacier motion (15-30% speed-up), lasting about three days, and ocurring at times of enhanced input of water, in some cases from rain and in others from ice ablation enhanced by strong, warm winds; (3) 'Extra-slowdown' events, in which, after a speed-up event, the ice velocity decreased in about 3 days to a level consistently lower than that prior to the speed-up event. All of the time variations were due, directly or indirectly, to variations in water input to the glacier.

Meier, Mark↗

The Implementation and Evaluation of the Emergency Response Dose Assessment System (ERDAS) at Cape Canaveral Air Station/Kennedy Space Center

The Emergency Response Dose Assessment System (ERDAS) is a system which combines the mesoscale meteorological prediction model RAMS with the diffusion models REEDM and HYPACT. Operators use a graphical user interface to run the models for emergency response and toxic hazard planning at CCAS/KCS. The Applied Meteorology Unit has been evaluating the ERDAS meteorological and diffusion models and obtained the following results: (1) RAMS adequately predicts the occurrence of the daily sea breeze during non-cloudy conditions for several cases. (2) RAMS shows a tendency to predict the sea breeze to occur slightly earlier and to move it further inland than observed. The sea breeze predictions could most likely be improved by better parameterizing the soil moisture and/or sea surface temperatures. (3) The HYPACT/REEDM/RAMS models accurately predict launch plume locations when RAMS winds are accurate and when the correct plume layer is modeled. (4) HYPACT does not adequately handle plume buoyancy for heated plumes since all plumes are presently treated as passive tracers. Enhancements should be incorporated into the ERDAS as it moves toward being a fully operational system and as computer workstations continue to increase in power and decrease in cost. These enhancements include the following: activate RAMS moisture physics; use finer RAMS grid resolution; add RAMS input parameters (e.g. soil moisture, radar, and/or satellite data); automate data quality control; implement four-dimensional data assimilation; modify HYPACT plume rise and deposition physics; and add cumulative dosage calculations in HYPACT.

Evans, Randolph J.↗

Forecasting the Northern African Dust Outbreak Towards Europe in April 2011: A Model Intercomparison

In the framework of the World Meteorological Organisation's Sand and Dust Storm Warning Advisory and Assessment System, we evaluated the predictions of five state-of-the-art dust forecast models during an intense Saharan dust outbreak affecting western and northern Europe in April 2011. We assessed the capacity of the models to predict the evolution of the dust cloud with lead times of up to 72 hours using observations of aerosol optical depth (AOD) from the AErosol RObotic NETwork (AERONET) and the Moderate Resolution Imaging Spectroradiometer (MODIS) and dust surface concentrations from a ground-based measurement network. In addition, the predicted vertical dust distribution was evaluated with vertical extinction profiles from the Cloud and Aerosol Lidar with Orthogonal Polarization (CALIOP). To assess the diversity in forecast capability among the models, the analysis was extended to wind field (both surface and profile), synoptic conditions, emissions and deposition fluxes. Models predict the onset and evolution of the AOD for all analysed lead times. On average, differences among the models are larger than differences among lead times for each individual model. In spite of large differences in emission and deposition, the models present comparable skill for AOD. In general, models are better in predicting AOD than near-surface dust concentration over the Iberian Peninsula. Models tend to underestimate the long-range transport towards northern Europe. Our analysis suggests that this is partly due to difficulties in simulating the vertical distribution dust and horizontal wind. Differences in the size distribution and wet scavenging efficiency may also account for model diversity in long-range transport.

dust storms↗

Bhutan Water Resources Tech Paper: Comparing Precipitation, Temperature, and Phenology Data Trends in Bhutan to Assist the Himalayan Environmental Rhythm Observation and Evaluation System (HEROES) Project

Himalayan countries, including Bhutan, have become vulnerable to warming trends which result in increasing temperature and variable rainfall and snowfall. By combining phenological and meteorological data, Earth observation platforms and sensors were used to assess trends in precipitation, temperature, and vegetation phenology in Bhutan from 1996 through 2017. This project studied precipitation using Climate Hazards Center Infrared Precipitation with Station data, analyzed temperature using the Famine Early Warning System Network Land Data Assimilation System, incorporated elevation data from the Shuttle Radar Topography Mission, and assessed vegetation phenology using Aqua and Terra Moderate Resolution Imaging Spectroradiometer (MODIS) to evaluate climate variability and its effects on Bhutan. In situ temperature and precipitation data were also collected from the Himalayan Environmental Rhythm Observation and Evaluation System (HEROES) project and Bhutan’s National Center for Hydrology and Meterology. Modeled and in situ data showed similar trends in precipitation and temperature for the Thimpu, Chhukha, and Gasa regions. Aqua and Terra MODIS phenology data were variable from year to year. However, the data suggested a late onset of spring green up. Partners at the Bhutan Foundation and locally in Bhutan can use this information to better understand and monitor climate variability and replicate these methods for future analysis.

Kinley Dorji↗