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This presentation is for the National Association for State Community Services Programs (NASCSP) Annual Conference. The authors provide an overview of several tools and resources, including the Weatherization Assistant, Standard Work Specifications, Installer Badges Toolkit, Grantee Training and Continuous Improvement, and Instructional Systems Design (ISD) Training.
As weather-dependent renewable generation grows, it is important for power system planning to understand the broad trends and correlations between weather, renewable resources, and load. The traditional planning, performed by utilities and system operators, includes the study of system resource adequacy during peak load periods in the summer and winter to ensure the generation and transmission system is appropriate to meet load. But in a power grid with a high penetration of variable renewable energy (i.e., wind and solar), periods of high risk to system resource adequacy may no longer correspond only to hours of peak load. In particular, high shares of variable renewable energy, even when well-forecasted to inform system operations, can further complicate the stress extreme weather events already place on the grid. They also may lead to changes to the types of weather conditions that are most problematic to system operations and resource adequacy due to widespread and extended deficits of wind and solar generation. Accordingly, the focus of reliability assessments in long-term planning studies may need to evolve in the coming years to more fully incorporate weather events that lead to these deficits. This report seeks to identify these new weather events and understand the characteristics of the events that lead to system risk of future systems with higher penetrations variable renewable energy.
This study assessed the energy-saving and climate-adaptive potential of cool skin and ventilated cavity skin facade technologies in Seoul's high-rise apartment buildings. We created weather scenarios for historical, mid-term future, and long-term future conditions using Coordinated Regional Downscaling EXperiment (CORDEX) method. Building energy simulations were conducted on a South Korean high-rise apartment model to evaluate their performance under different weather conditions. The results indicate that cool skin and ventilated cavity skin technologies can save cooling energy during summers but lead to heating energy penalties in winters. Ventilated cavity skin outperforms cool skin, offering better cooling energy savings and reduced heating penalties. Combining both technologies yields the highest overall energy savings, with 7 %, 9 %, and 10 % cooling energy savings for cool skin, ventilated cavity skin, and the combined package, respectively. However, cool skin increases heating energy consumption by 5 %, while ventilated cavity skin has minimal impact on heating energy. These envelope technologies also reduce peak electricity demand by at least 5 %, 8 %, and 9 %, respectively. They contribute to heat stress reduction, enhance resilience, and decrease extreme heat risks for occupants during power outages by at least 18 % under various weather conditions. Considering the prevalence of aging high-rise apartments in South Korea, adopting these envelope renovation strategies can effectively reduce cooling loads, enhance thermal comfort, and boost resilience under future climates, while avoiding costly reconstruction.
Development of a zero energy community is more costly in northern cold climates than in moderate regions. Building energy loads are higher, thanks to the colder weather, and site solar photovoltaics (PV) are less productive due to lower solar incidence and misalignment with the buildings’ energy needs (summer production, winter demands). Geothermal energy production can support a zero energy community through application of energy efficiency (demand design), geothermal production (supply design), and asset dispatch as an integrated techno-economic package. This article presents the process used to explore geothermal system integration, our findings, and technical challenges for community-scale adoption of geothermal as an electric and thermal resource. We show that under a wide range of conditions, community-scale geothermal electric power and direct-use thermal energy is economically competitive with “business-as-usual” design and construction practices for zero energy communities. Furthermore, geothermal-produced energy will be self-consumed to a much greater extent than PV, resulting in significant reductions in site energy import and export. We conclude that under appropriate conditions, community-scale geothermal can be the most economically favorable energy resource for northern-climate zero energy community developments. Ongoing geothermal research and development to improve performance and reduce costs will further enhance the value proposition for community-scale geothermal technologies. We expect that including geothermal power and thermal energy in zero energy community design can improve its cost-effectiveness and therefore enhance the benefits of zero energy in more northern climates.
Traditional approaches for comparing global climate models and observational data products typically fail to account for the geographic location of the underlying weather station data. For modern global high-resolution models with a horizontal resolution of tens of kilometers, this is an oversight since there are likely grid cells where the physical output of a climate model is compared with a statistically interpolated quantity instead of actual measurements of the climate system. In this paper, we quantify the impact of geographic sampling on the relative performance of high-resolution climate model representations of precipitation extremes in boreal winter (December–January–February) over the contiguous United States (CONUS), comparing model output from five early submissions to the HighResMIP subproject of the CMIP6 experiment. We find that properly accounting for the geographic sampling of weather stations can significantly change the assessment of model performance. Across the models considered, failing to account for sampling impacts the different metrics (extreme bias, spatial pattern correlation, and spatial variability) in different ways (both increasing and decreasing). We argue that the geographic sampling of weather stations should be accounted for in order to yield a more straightforward and appropriate comparison between models and observational data sets, particularly for high-resolution models with a horizontal resolution of tens of kilometers. While we focus on the CONUS in this paper, our results have important implications for other global land regions where the sampling problem is more severe.
A reliable electric power supply is crucial for modern day life as well as national security, economic productivity, and life-and-death essentials. During the COVID pandemic, internet and cell communications became a “must-have” for government and business operations, education, and communicating COVID testing for vaccine information. Loss of electric power quickly leads to human health and national security emergencies. When a major winter storm hit Texas in mid-February 2021, the system was overwhelmed and over 4M people lost power. Although this crisis arose from an unprecedented weather event - not a cyberattack - it serves as a vivid illustration of the impact power disruption can have on our American way of life. The recent cyberattack on the Colonial Oil Pipeline also provides a stark reminder that infrastructure supporting our daily lives has vulnerabilities.
Abstract. In this study, the Noah land surface model used in conjunction with the Mellor–Yamada–Janjić surface layer scheme (hereafter, Noah-MYJ) and the Noah multiphysics scheme (Noah-MP) from the Weather Research and Forecasting (WRF) 4.5.1 mesoscale model are evaluated with regard to their performance in reproducing positive temperature gradients over forested areas in the Arctic winter. First, simplified versions of the WRF schemes, recoded in Python, are compared with conceptual models of the surface layer in order to gain insight into the dependence of the temperature gradient on the wind speed at the top of the surface layer. It is shown that the WRF schemes place strong limits on the turbulent collapse, leading to lower surface temperature gradient at low wind speeds than in the conceptual models. We implemented modifications to the WRF schemes to correct this effect. The original and modified versions of Noah-MYJ and Noah-MP are then evaluated compared to long-term measurements at the Ameriflux Poker Flat Research Range, a forest site in interior Alaska. Noah-MP is found to perform better than Noah-MYJ because the former is a two-layer model which explicitly takes into account the effect of the forest canopy. Indeed, a non-negligible temperature gradient is maintained below the canopy at high wind speeds, leading to overall larger gradients than in the absence of vegetation. Furthermore, the modified versions are found to perform better than the original versions of each scheme because they better reproduce strong temperature gradients at low wind speeds.
Midwestern U.S. extreme precipitation is associated with multiple storm types including mesoscale convective systems (MCSs) and/or training thunderstorms, tropical cyclone (TC) remnants, and winter storms. Anthropogenic warming is expected to increase climatological precipitation globally, however, there may be little correspondence with regional storm-based changes. Furthermore, uncertainty remains in precipitation-temperature scaling due to use of convective parameterization in most global models. In this study, we investigated historically impactful extreme precipitation events from multiple types of Midwest storms using the Weather Research and Forecasting model at convection-permitting resolution. We simulated five-member ensembles of historical hindcasts and experiments representing the storms in the future using the pseudo-global warming method. We found that future precipitation changes depend on storm type, with increases near Clausius-Clapeyron (CC) for winter storms, no consensus for MCSs and/or training thunderstorms, and sub-CC increases for TC remnants. This research highlights the importance of considering storm type in future extreme precipitation projections.
The Arctic surface energy budget (SEB) couples the atmosphere with the sea ice, making it useful for both studying surface processes as well as evaluating models. Improved understanding of atmosphere-ice interactions is required to improve models, requiring year-round observations to address seasonally dependent biases. This work uses novel observations from the MOSAiC expedition to quantify the responses of surface fluxes to radiative forcing over sea ice throughout a complete annual cycle. We identify two primary regimes of flux response: an ice growth regime in winter and an ice melt regime in summer. In the growth regime, changes in radiative forcing impact upwelling longwave, sensible heat, and subsurface heat fluxes, whereas in the melt regime changes in radiative forcing primarily alter the amount of melt and subsurface transmission because the surface temperature is fixed. These observed responses of surface fluxes to radiative forcing are used to evaluate seven weather forecast models during the ice growth regime. In most models, the responses of surface fluxes to radiative forcing do not match observations. Many models also have biased downwelling longwave. One model (the Coupled Arctic Forecast System; CAFS) adequately captures both the mean radiative forcing and the flux responses in winter. CAFS is further evaluated against observations spanning the full MOSAiC year, demonstrating sufficient agreement to provide a more generalized understanding of these SEB process relationships across the Arctic.
Data assimilation of satellite microwave measurements is one of the important keys to improving weather forecasting over the Arctic region. However, the use of surface-sensitive microwave-sounding channel measurements for data assimilation or retrieval has been limited, especially during winter, due to the poorly constrained sea ice emissivity. In this study, aiming at more use of those channel measurements in the data assimilation, we propose an explicit method for specifying the surface radiative boundary conditions (namely emissivity and emitting layer temperature of snow and ice). These were explicitly determined with a radiative transfer model for snow and ice and with snow/ice physical parameters (i.e., snow/ice depths and vertical distributions of temperature, density, salinity, and grain size) simulated from the thermodynamically-driven snow/ice growth model. Here we conducted 1-D Var experiments in order to examine whether this approach can help to use the surface-sensitive microwave temperature channel measurements over the Arctic sea ice region for data assimilation. Results show that (1) the surface-sensitive microwave channels can be used in the 1-D Var retrieval, and (2) the specification of the radiative boundary condition at the surface using the snow/sea ice emission model can significantly improve the atmospheric temperature retrieval, especially in the lower troposphere (500 hPa to surface). The successful retrieval suggests that useful information can be extracted from surface-sensitive microwave-sounding channel radiances over sea ice surfaces through the explicit determination of snow/ice emissivity and emitting layer temperature.
This dataset contains data from the CLAMPS 1 Halo Photonics StreamLine Doppler Lidar at the Rolling Meadows Golf Course site. CLAMPS 1 deployed during fall-winter 2022 (10/3/22-12/27/23) and summer-fall 2023 (6/16/23-10/1/23).
This project was part of an effort by ComEd's emerging technology program to evaluate the energy saving potential of new energy efficiency technologies. The focus of this technology assessment was to determine energy and peak demand savings potentials of a high efficiency variable speed, air-source, split system heat pump designed for cold climate applications. The results of this technology assessment will be used by CLEAResult to develop a new energy efficiency measure for Commonwealth Edison Company's incentive programs. The project utilized the National Renewable Energy Laboratory's (NREL) Thermal Test Facility to experimentally characterize cooling and heating performance of a high efficiency heat pump split system under varying outdoor climate conditions. The selected climate conditions represented summer and low temperature winter conditions in ComEd's service territory. The laboratory experimentation results were used to develop equipment performance curves required by EnergyPlus hourly simulation engine. Using typical meteorological year 3 weather data for the Chicago O'Hare airport, hourly building simulations (using the EnergyPlus engine) was utilized to estimate the annual energy savings of the high efficiency heat pump in comparison to a standard efficiency unit in the following U.S. Department of Energy (DOE) building codes program energy prototypes: Single-family residence; Strip mall; and Low-rise office.
Abstract Global kilometer‐scale models represent the future of Earth system modeling, enabling explicit simulation of organized convective storms and their associated extreme weather. Here, we comprehensively evaluate tropical mesoscale convective system (MCS) characteristics in the DYAMOND (DYnamics of the atmospheric general circulation modeled on non‐hydrostatic domains) simulations for both summer and winter phases. Using 10 different feature trackers applied to simulations and satellite observations, we assess MCS frequency, precipitation, and other key characteristics. Substantial differences (a factor of 2–3) arise among trackers in observed MCS frequency and their precipitation contribution, but model‐observation differences in MCS statistics are more consistent across trackers. DYAMOND models are generally skillful in simulating tropical mean MCS frequency, with multi‐model mean biases ranging from −2%–8% over land and −8%–8% over ocean (summer vs. winter). However, most DYAMOND models underestimate MCS precipitation amount (23%) and their contribution to total precipitation (17%). Biases in precipitation contributions are generally smaller over land (13%) than over ocean (21%), with moderate inter‐model variability. While models better simulate MCS diurnal cycles and cloud shield characteristics, they overestimate MCS precipitation intensity and underestimate stratiform rain contributions (up to a factor of 2), particularly over land, albeit observational uncertainties exist. Additionally, models exhibit a wide range of precipitable water in the tropics compared to reanalysis and satellite observations, with many models showing exaggerated sensitivity of MCS precipitation intensity to precipitable water. The MCS metrics developed here provide process‐oriented diagnostics to guide future model development.
The purpose of this report is to determine the effects that extreme cold temperatures have on electric vehicles (EVs) and electric vehicle supply equipment (EVSE). The adoption of EVs in extreme cold weather presents challenges that require careful analysis of efficiency and charging infrastructure. This report, "Electric Vehicle and Charging Infrastructure Assessment in Cold-Weather Climates: A Case Study of Fairbanks, Alaska," explores how EVs and EVSE perform in temperatures as low as -40 degrees C (-40 degrees F), focusing on real-world data from Teslas in Alaskan winter conditions. The findings indicate that EVs can successfully function in extreme cold, though efficiency is significantly affected. Vehicles stored in heated environments outperformed those stored outdoors, with efficiency dropping by up to 69% for outdoor storage. Despite these challenges, none of the vehicles experienced failures that prevented travel. Storing EVs indoors led to benefits such as faster preconditioning and improved efficiency, while charging in extreme cold, though slower, remained functional. Ultimately, the report concludes that with proper precautions and best practices, EVs are viable transportation solutions in cold climates. Investing in enclosed, heated storage is recommended to maximize efficiency and minimize battery strain. As advancements in battery chemistry and thermal management progress, EV adoption in extreme climates is expected to become even more feasible.
Humidity profiles retrieved from a ground-based millimeter-wave radiometer located at McMurdo Station, Antarctica and the West Antarctica Ice Sheet Divide are presented and their suitability to study the humidity of the polar climate is assessed. The dry conditions of the Antarctic winter and spring are ideal for ground-based millimeter-wave measurements and the retrievals appear to realistically reproduce the spatial and temporal variability of humidity at both sites. Furthermore, the radiometer has the ability to capture daily variability of very low humidity (0.5 to 4 g/kg) in the low-to-mid troposphere with an uncertainty of 10-20% during the Antarctic winter, spring, and summer. Despite the coarse vertical resolution (200-600 m in the first 4 km), the retrievals provide additional information with respect to the European Centre for Medium Range Weather Forecasts (ECMWF) profiles used as background information. The radiometer is also able to realistically identify the location and frequency of supersaturated layers with respect to ice in the mid troposphere. The occurrence of supersaturated layers is correlated with the occurrence of ice clouds identified by a cloud mask. Overall, results show that ground-based microwave and millimeter-wave radiometry is a viable complement to satellite observations to provide continuous information on the thermodynamic state of the low-to-mid troposphere at high latitudes.
Oscillations in global modes of variability (MoVs) form global teleconnections that affect regional climate variability and modify the potential for severe and damaging weather conditions. Understanding the link between certain MoVs and regional climate can improve the ability to more accurately predict environmental conditions that impact human life and health. In this study, we explore the connection between different MoVs, including the Arctic oscillation (AO), Eurasian teleconnection, Indian Ocean dipole (IOD), North Atlantic oscillation (NAO), and El Niño southern oscillation (Nino34), with winter and summer climates in the High Mountain Asia (HMA) region, including geopotential height at 250 hPa (z250), 2 m air temperature (T2M), total precipitation (PRECTOT), and fractional snow cover area (fSCA). Relationships are explored for the same monthly period between the MoVs and the climate variables, and a lagged correlation analysis is used to investigate whether any relationship exists at different time lags. We find that T2M has a negative correlation with the Eurasian teleconnection in the Inner Tibetan Plateau and central China in both winter and summer and a positive correlation in western China in summer. PRECTOT has a positive correlation with all MoVs in most regions in winter, especially with the IOD, and a negative correlation in summer, especially with the Eurasian teleconnection. Snow cover in winter is positively correlated with most indices throughout many regions in HMA, likely due to wintertime precipitation also being positively correlated with most indices. Generally, the AO and NAO show similar correlation patterns with all climate variables, especially in the winter, possibly due to their oscillations being so similar. Furthermore, the AO and NAO are shown to be less significant in explaining the variation in HMA climate compared to other MoVs such as the Eurasian teleconnection. Overall, our results identify different time windows and specific regions within HMA that exhibit high correlations between climate and MoVs, which might offer additional predictability of the MoVs as well as of climate and weather patterns in HMA and throughout the globe.
During the 42-year period (1979–2020) of satellite measurements, four major winter (December–March) polynyas have been observed north of Greenland: one in December 1986 and three in the last decade, i.e., February of 2011, 2017, and 2018. The 2018 polynya was unparalleled in its magnitude and duration compared to the three previous events. Given the apparent recent increase in the occurrence of these extreme events, this study aims to examine their evolution and causality, in terms of forced versus natural variability. The limited weather station and remotely sensed sea ice data are analyzed combining with output from the fully coupled Regional Arctic System Model (RASM), including one hindcast and two ensemble simulations. We found that neither the accompanying anomalous warm surface air intrusion nor the ocean below had an impact (i.e., no significant ice melting) on the evolution of the observed winter open-water episodes in the region. Instead, the extreme atmospheric wind forcing resulted in greater sea ice deformation and transport offshore, accounting for the majority of sea ice loss in all four polynyas. Our analysis suggests that strong southerly winds (i.e., northward wind with speeds greater than 10 m s –1 ) blowing persistently over the study region for at least 2 d or more were required over the study region to mechanically redistribute some of the thickest Arctic sea ice out of the region and thus to create open-water areas (i.e., a latent heat polynya). To assess the role of internal variability versus external forcing of such events, we carried out and examined results from the two RASM ensembles dynamically downscaled with output from the Community Earth System Model (CESM) Decadal Prediction Large Ensemble (DPLE) simulations. Out of 100 winters in each of the two ensembles (initialized 30 years apart: one in December 1985 and another in December 2015), 17 and 16 winter polynyas were produced north of Greenland, respectively. The frequency of polynya occurrence had no apparent sensitivity to the initial sea ice thickness in the study area pointing to internal variability of atmospheric forcing as a dominant cause of winter polynyas north of Greenland. We assert that dynamical downscaling using a high-resolution regional climate model offers a robust tool for process-level examination in space and time, synthesis with limited observations, and probabilistic forecasts of Arctic events, such as the ones being investigated here and elsewhere.
Abstract. Recent studies suggested significant impacts of boreal cryosphere changes on wintertime air stagnation and haze pollution extremes in China. However, the underlying mechanisms of such a teleconnection relationship remains unclear. Here we use the Whole Atmosphere Community Climate Model (WACCM) to investigate dynamic processes leading to atmospheric circulation and air stagnation responses to Arctic sea ice changes. We conduct four climate sensitivity experiments by perturbing sea ice concentrations (SIC) and corresponding sea surface temperature (SST) in autumn and early winter over the whole Arctic and three subregions in the climate model. The results indicate distinct responses in circulation patterns and regional ventilation to the region-specific Arctic changes, with the largest increase of both the probability (by 132 %) and the intensity (by 30 %) of monthly air stagnation extremes being found in the experiment driven by SIC and SST changes over the Pacific sector of the Arctic (the East Siberian and Chukchi seas). The increased air stagnation extremes are mainly driven by an amplified planetary-scale atmospheric teleconnection pattern that resembles the negative phase of the Eurasian (EU) pattern. Dynamical diagnostics suggest that convergence of transient eddy forcing in the vicinity of Scandinavia in winter is largely responsible for the amplification of the teleconnection pattern. Transient eddy vorticity fluxes dominate the transient eddy forcing and produce a barotropic anticyclonic anomaly near Scandinavia and wave train propagation across Eurasia to the downstream regions in East Asia. The piecewise potential vorticity inversion analysis reveals that this long-range atmospheric teleconnection of Arctic origin takes place primarily via the middle and upper troposphere. The anomalous ridge over East Asia in the middle and upper troposphere worsens regional ventilation conditions by weakening monsoon northwesterlies and enhancing temperature inversions near the surface, leading to more and stronger air stagnation and pollution extremes over eastern China in winter. Ensemble projections based on state-of-the-art climate models in the Coupled Model Intercomparison Project Phase 6 (CMIP6) corroborate this teleconnection relationship between high-latitude environmental changes and midlatitude weather extremes, though the tendency and magnitude vary considerably among each participating model.