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Verifying and assessing the performance of the perturbation strategy in polynomial chaos ensemble forecasts of the circulation in the Gulf of Mexico

Here we present an analysis of two recent efforts aimed at quantifying the uncertainties in a 30-day HYbrid Coordinate Ocean Model forecast of the circulation in the Gulf of Mexico, with particular emphasis on the separation of Loop Current Eddy Franklin, using Polynomial Chaos methods. The analysis herein explores whether the model perturbations lead to realistic representation of the uncertainty in the Gulf Circulation. Comparisons of model output with Sea Surface Height and current mooring data show that the observational data generally falls within the envelope of the ensemble and that the modal decomposition delivers “realistic” perturbations in the Loop Current region. We use information theory metrics to quantify the information gain and the computational trade-offs between different wind and initial conditions perturbation modes. The relative entropy measures indicate that two modes for initial condition perturbations are enough, in our model configuration, to represent the uncertainty in the Loop Current region; while two modes for wind forcing perturbations are necessary in order to estimate the uncertainty in the coastal zone. The ensemble statistics are then explored using the Polynomial Chaos surrogate and the newly developed contour boxplot methods.

54 ENVIRONMENTAL SCIENCES↗

The High-resolution Transmission Spectrum of HD 189733b Interpreted with Atmospheric Doppler Shifts from Three-dimensional General Circulation Models

The signature of wind patterns caused by the interplay of rotation and energy redistribution in hot Jupiters is detectable at high spectral resolution, yet no direct comparison has been attempted between predictions from general circulation models (GCMs) and observed high-resolution spectra. We present the first such comparison on near-infrared transmission spectra of the hot Jupiter HD 189733b. Exploring 12 rotation rates and two chemical regimes, we have created model spectra from 3D GCMs and cross-correlated them with the observed spectra. Comparing our models against those of HD 189733b, we obtain three key results: (1) we confirm CO and H{sub 2}O in the planet’s atmosphere at a detection significance of 8.2σ; (2) we recover the signature of day-to-night winds with speeds of several km s{sup −1} at pressures of several millibars; and (3) we constrain the rotation period of the planet to between 1.2 and 4.69 days (synchronous rotation (2.2 days) remains consistent with existing observations). Our results do not suffer from the shortcomings of 1D models as cross-correlation templates—these models mainly tend to overconstrain the slower rotation rates and show evidence for anomalous blueshifts. Our 3D models instead match the observed line-of-sight velocity of this planet by self-consistently including the effects of high-altitude day-to-night winds. Overall, we find a high degree of consistency between observations of HD 189733b and our GCM-based spectra, implying that the physics and chemistry are adequately described in current 3D forward models for the purpose of interpreting observations at high spectral resolution.

79 ASTRONOMY AND ASTROPHYSICS↗

Process-oriented evaluation of quasi-stationary Rossby waves and their impact on surface air temperature extremes in dynamical downscaling over North America

Quasi-stationary Rossby waves are a crucial component of the general circulation and play a significant role in regional water and energy cycles, as well as in extreme events. However, process-oriented evaluation for Rossby waves is rarely performed for dynamical downscaling simulations. To close this gap, we evaluate three classes of dynamical downscaling approaches, with a focus on quasi-stationary Rossby waves and their impact on surface air temperature over North America during Northern Hemisphere summer. The three classes of models differ in the way large-scale forcing is provided: a limited-area model (LAM) constrained only by lateral boundary conditions, represented by RegCM4 from the North American branch of the Coordinated Regional Downscaling Experiment (NA-CORDEX), a LAM with spectral nudging to maintain consistency in large-scale dynamics with the forcing data, represented by the Weather Research and Forecasting (WRF) model simulation in NA-CORDEX, and a global variable-resolution model with smoothly varying grid spacings, represented by the Community Atmosphere Model version 5.4, with the Model for Prediction Across Scales (MPAS) as its dynamical core (CAM-MPAS). With no constraints on the atmospheric dynamics, CAM-MPAS exhibits several mean biases in the upper-level circulations over the Pacific Coast region: a weaker subtropical jet, a northward-shifted mid-latitude jet, and an overestimated southerly flow. With the lateral boundary constraint alone, RegCM4 also exhibits weaker jets and overestimated southerly winds off the West Coast. Rossby ray theory reveals that those wind biases direct incoming Rossby waves northward. The erroneously routed Rossby waves distort the relationship between the accumulation of wave activity over the US West Coast and surface temperature anomalies over the Southern Great Plains, which emerges approximately 4 d after the convergence of wave-activity flux in the ERA-Interim reanalysis. Furthermore, the response of heatwaves to the extreme wave activity flux is not reproduced by the two models, a serious drawback as a dynamical downscaling framework is expected to connect large-scale forcing to local-scale phenomena. The WRF model employing spectral nudging is largely free from the aforementioned problems. A pair of sensitivity simulations suggests that spectral nudging is the key to improving the dynamics of quasi-stationary Rossby waves and their impact on surface air temperature. Our results also demonstrate the effectiveness of Rossby wave diagnostics that allow for realistic background flows for assessing the credibility of dynamical downscaling over North America, where incoming Rossby waves propagate through complex circulation patterns before traveling across the continent.

54 ENVIRONMENTAL SCIENCES↗

A Time Series Sustainability Assessment of a Partial Energy Portfolio Transition

Energy portfolios are overwhelmingly dependent on fossil fuel resources that perpetuate the consequences associated with climate change. Therefore, it is imperative to transition to more renewable alternatives to limit further harm to the environment. This study presents a univariate time series prediction model that evaluates sustainability outcomes of partial energy transitions. Future electricity generation at the state-level is predicted using exponential smoothing and autoregressive integrated moving average (ARIMA). The best prediction results are then used as an input for a sustainability assessment of a proposed transition by calculating carbon, water, land, and cost footprints. Missouri, USA was selected as a model testbed due to its dependence on coal. Of the time series methods, ARIMA exhibited the best performance and was used to predict annual electricity generation over a 10-year period. The proposed transition consisted of a one-percent annual decrease of coal’s portfolio share to be replaced with an equal share of solar and wind supply. The sustainability outcomes of the transition demonstrate decreases in carbon and water footprints but increases in land and cost footprints. Decision makers can use the results presented here to better inform strategic provisioning of critical resources in the context of proposed energy transitions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Genesis of Hurricane Sandy (2012) Simulated with a Global Mesoscale Model

In this study, we investigate the formation predictability of Hurricane Sandy (2012) with a global mesoscale model. We first present five track and intensity forecasts of Sandy initialized at 00Z 22-26 October 2012, realistically producing its movement with a northwestward turn prior to its landfall. We then show that three experiments initialized at 00Z 16-18 October captured the genesis of Sandy with a lead time of up to 6 days and simulated reasonable evolution of Sandy's track and intensity in the next 2 day period of 18Z 21-23 October. Results suggest that the extended lead time of formation prediction is achieved by realistic simulations of multiscale processes, including (1) the interaction between an easterly wave and a low-level westerly wind belt (WWB) and (2) the appearance of the upper-level trough at 200 hPa to Sandy's northwest. The low-level WWB and upper-level trough are likely associated with a Madden-Julian Oscillation.

multiscale processes↗

Efficient Uncertainty Quantification in Stochastic Economic Dispatch

Stochastic economic dispatch models usually address uncertainties in forecasts of renewable generation output by considering a finite number of realizations drawn from a stochastic process model, typically via Monte Carlo sampling. Accurate evaluations of expectations or higher order moments for quantities of interest, e.g., generating cost, can require a prohibitively large number of samples. We propose an alternative to Monte Carlo sampling based on polynomial chaos expansions. These representations enable efficient and accurate propagation of uncertainties in model parameters, using sparse quadrature methods. Furthermore, we use Karhunen-Loève expansions for efficient representation of uncertain renewable energy generation that follows geographical and temporal correlations derived from historical data at each wind farm. Considering expected production cost, we show that the proposed approach can yield several orders of magnitude reduction in computational cost for solving stochastic economic dispatch relative to Monte Carlo sampling, for a given target error threshold.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Seesaw haze pollution in North China modulated by the sub-seasonal variability of atmospheric circulation

Utilizing a recent observational dataset of particulate matter with diameters less than 2.5 µ m (PM 2.5 ) in North China, this study reveals adistinct seesaw feature of abnormally high and low PM 2.5 concentrationsin the adjacent two months of December 2015 and January 2016, accompanied bydistinct meteorological modulations. The seesaw pattern is postulated to belinked to a super El Niño and the Arctic Oscillation (AO). During themature phase of El Niño in December 2015, the weakened East Asian wintermonsoon (EAWM) and the associated low-level southerly wind anomaly reducedplanetary boundary layer (PBL) height, favoring strong haze formation. Thiscirculation pattern was completely reversed in the following month, in partdue to a sudden phase change of the AO from positive to negative and thebeginning of a decay of the El Niño, which enhanced the southward shiftof the upper tropospheric jet from December to January relative toclimatology, leading to an enhanced EAWM and substantially lower hazeformation. This sub-seasonal change in circulation is also robustly found in1982–1983 and 1997–1998, implicative of a general physical mechanismdynamically linked to El Niño and the AO. Numerical experiments using theWeather Research and Forecasting (WRF) Community Multiscale Air Quality(CMAQ) model were used to test the modulation of the meteorologicalconditions on haze formation. With the same emission, simulations for threesuper El Niño periods (1983, 1997 and 2015) robustly show higherPM 2.5 concentrations under the mature phase of the super El Niño,but substantially lower PM 2.5 concentrations during the decay phase ofEl Niño (and the sudden AO phase change), further verifying themodulation effect of the sub-seasonal circulation anomaly on PM 2.5 concentrations in North China

54 ENVIRONMENTAL SCIENCES↗

The formation of Hurricane Frederic of 1979

A high-resolution global model forecast of the formation of Hurricane Frederic of 1979 is analyzed by means of several diagnostic computations on the model's output history. The formation is addressed from an analysis of limited-area energetics where the growth of eddy kinetic energy is examined. The question on internal versus external forcing during the formative stage of the hurricane is explored by means of the Kuo-Eliassen framework for the radial-vertical circulation of the hurricane. The intensity of the predicted hurricane is diagnosed from a detailed angular momentum budget following the three-dimensional motion of parcels arriving at the maximum wind belt. Overall, the successful simulation of the hurricane has enabled us to make such a detailed diagnosis of the predicted hurricane at a high resolution. The principal findings of this study are that a north-south-oriented heating function maintained a zonal easterly flow that supplied energy barotropically during the growth of an African wave. The growth of eddy kinetic energy is somewhat monotonic and slow throughout the history of the computations. The initial development of the easterly wave appears to be related to the widespread weak convective heating that contributes to a covariance of heating and temperature and of temperature and vertical velocity. The hurricane development period is seen as one where both the barotropic and convective processes contribute to the growth of eddy kinetic energy.

Krishnamurti, T. N.↗

Combined Cycle Integrated Thermal Energy Storage “CiTES” (Final Scientific/Technical Report)

The Phase I of this project confirmed the technical feasibility of a Combined Cycle integrated Thermal Energy Storage “CiTES” system, calculated the key performance parameters like power efficiency and costs, and proved its commercial value with full-year simulations for several US electricity markets with high degree of variable renewable generation and volatile hourly electricity prices. The core element of this project is the Electro Thermal Energy Storage (ETES) technology from Siemens Gamesa Renewable Energy GmbH, using thermally stable and inexpensive volcanic rocks as storage material and air as heat transfer medium. This technology is backed by more than 10 years of experience and a 440MMBTU (130MWh-th) pilot plant in Hamburg, Germany, which is in operation since 2019. The integration of this thermal storage in an existing combined cycle power plant (CCPP) is typical power plant technology without any major technology risks. It allows the storage of inexpensive renewable energy during times of surplus renewable generation and the discharge of this energy in times of high energy demand when the fossil plant is in operation. This supplements the fossil power generation with CO2-emission-free energy. The secondary effect of the CiTES system is that a small part of the stored thermal energy is used to keep the heat recovery steam generator (HRSG) and steam turbine (ST) of the combined cycle power plant in hot and ready-to-start condition. This enables the plant to start rapidly when fossil generation is required to satisfy demand as soon variable generation drops off in the evenings or during cloud cover and calm wind periods. Without pre-warming of the HRSG and ST, the CCPP would need several hours for a cold or warm start, burn a lot of gas and release high NOx emissions during start and wouldn’t be able to use the short times of high energy prices in an efficient or economical manner. The economic parameters of CiTES were determined by a full year “8760” simulation using a data set calculation for each of the hours of the year, and historical electricity and gas prices. For consistency, the simulations were focused on the pre-COVID year 2019. The financially most attractive markets were in the Energy Reliability Council of Texas (ERCOT) region, which allowed substantial value generation with arbitrage (charge with cheap energy during renewable surplus times and discharge when energy is needed and expensive). The improvement of flexibility with the CiTES system by pre-heating and warm-keeping of the CCPP allowed for additional power generation during short time periods when demand is high but renewable generation is down; when the hourly energy prices are highest in these markets. The simulations are based on 2019 data, when ERCOT had 27GW of installed photovoltaic (PV) and wind generation. They showed that the created revenue with the prototypically sized CiTES system of 1,000MMBTU (300MWh-th) falls a little bit short of what is expected from a commercially viable investment. The system has optimization opportunities for cost reduction and increased effectiveness which will be realized during a potential Phase II Pre-FEED study following this project. Furthermore, it is safe to assume that a lot of renewable generation capacity will be added all over the US in the coming years. As an example, ERCOT is predicting to more than double its renewable generation from 27GW in 2019 to a forecasted 63GW in 2023. This will increase the amount of renewable overproduction exponentially. This rapid increase of local overproduction and the need to curtail renewable generation is well documented by the California ISO (www.CAISO.com / managing oversupply). However, the simulations also revealed a weakness in the structure of the electricity markets in the US. More specifically, when electricity prices are very low and approaching negative levels, the owners of Variable Renewable Energy (VRE) will curtail a part of their facility to stabilize the price by reducing supply. This results in a situation in which storage facilities, which are integrated in existing fossil assets and don’t have the behind-the-meter benefit of a VRE, won’t be able to purchase low cost – otherwise curtailed – renewable energy off the grid. A special tariff, which motivates VRE owners to sell otherwise curtailed renewable energy to storage facilities (Hydrogen, thermal, pumped hydro, etc.) can solve this issue. The implementation of such a regulating tariff by Independent System Operators, thus avoiding renewable curtailment, is a pre condition for successful commercialization for renewable energy storage technologies. With this advancement of design and technology and improvements in the market environment, it can be expected that the Combined Cycle integrated Thermal Energy Storage proves itself as an important innovation to keep highly efficient, natural gas-based power generation economically successful and relevant for the power industry in the United States of America.

Wolf, Thorsten↗

Carbon Data Assimilation with a Coupled Ensemble Kalman Filter (Final Technical Report)

We proposed (and accomplished) the development of an Ensemble Kalman Filter (EnKF) approach for the estimation of surface carbon fluxes as if they were parameters, augmenting the model with them. Our system is quite different from previous approaches, such as carbon flux inversions, 4D-­Var, and EnKF with approximate background error covariance (Peters et al., 2008). We showed (using observing system simulation experiments, OSSEs) that these differences lead to a more accurate estimation of the evolving surface carbon fluxes at model grid-scale resolution. The main properties of the LETKF-­C are: a) The carbon cycle LETKF is coupled with the simultaneous assimilation of the standard atmospheric variables, so that the ensemble wind transport of the CO2 provides an estimation of the carbon transport uncertainty. b) The use of an assimilation window (6hr) much shorter than the months-long windows used in other methods. This avoids the inevitable “blurring” of the signal that takes place in long windows due to turbulent mixing since the CO2 does not have time to mix before the next window. In this development we introduced new, advanced techniques that have since been adopted by the EnKF community (Kang, 2009, Kang et al., 2011, Kang et al. 2012). These advances include “variable localization” that reduces sampling errors in the estimation of the forecast error covariance, more advanced adaptive multiplicative and additive inflations, and vertical localization based on the time scale of the processes. The main result has been obtained using the LETKF-­C with all these advances, and assimilating simulated atmospheric CO2 observations from different observing systems (surface flask observations of CO2 but no surface carbon fluxes observations, total column CO2 from GoSAT/OCO-­2, and upper troposphere AIRS retrievals). After a spin-­up of about one month, the LETKF-­C succeeded in reconstructing the true evolving surface fluxes of carbon at a model grid resolution. When applied to the CAM3.5 model, the LETKF gave very promising results as well, although only one month is available.

54 ENVIRONMENTAL SCIENCES↗

Final report on "Carbon Data Assimilation with a Coupled Ensemble Kalman Filter"

We proposed (and accomplished) the development of an Ensemble Kalman Filter (EnKF) approach for the estimation of surface carbon fluxes as if they were parameters, augmenting the model with them. Our system is quite different from previous approaches, such as carbon flux inversions, 4D-Var, and EnKF with approximate background error covariance (Peters et al., 2008). We showed (using observing system simulation experiments, OSSEs) that these differences lead to a more accurate estimation of the evolving surface carbon fluxes at model grid-scale resolution. The main properties of the LETKF-C are: a) The carbon cycle LETKF is coupled with the simultaneous assimilation of the standard atmospheric variables, so that the ensemble wind transport of the CO2 provides an estimation of the carbon transport uncertainty. b) The use of an assimilation window (6hr) much shorter than the months-long windows used in other methods. This avoids the inevitable “blurring” of the signal that takes place in long windows due to turbulent mixing since the CO2 does not have time to mix before the next window. In this development we introduced new, advanced techniques that have since been adopted by the EnKF community (Kang, 2009, Kang et al., 2011, Kang et al. 2012). These advances include “variable localization” that reduces sampling errors in the estimation of the forecast error covariance, more advanced adaptive multiplicative and additive inflations, and vertical localization based on the time scale of the processes. The main result has been obtained using the LETKF-C with all these advances, and assimilating simulated atmospheric CO2 observations from different observing systems (surface flask observations of CO2 but no surface carbon fluxes observations, total column CO2 from GoSAT/OCO-2, and upper troposphere AIRS retrievals). After a spin-up of about one month, the LETKF-C succeeded in reconstructing the true evolving surface fluxes of carbon at a model grid resolution. When applied to the CAM3.5 model, the LETKF gave very promising results as well, although only one month is available.

58 GEOSCIENCES↗

Methane emissions from dairies in the Los Angeles Basin

We estimate the amount of methane (CH 4 ) emitted by the largest dairies in the southern California region by combining measurements from four mobile solar-viewing ground-based spectrometers (EM27/SUN), in situ isotopic 13/12 CH 4 measurements from a CRDS analyzer (Picarro), and a high-resolution atmospheric transport simulation with a Weather Research and Forecasting model in large-eddy simulation mode (WRF-LES). The remote sensing spectrometers measure the total column-averaged dry-air mole fractions of CH 4 and CO 2 (X CH 4 and X CO 2 ) in the near infrared region, providing information on total emissions of the dairies at Chino. Differences measured between the four EM27/SUN ranged from 0.2 to 22ppb (part per billion) and from 0.7 to 3ppm (part per million) for X CH 4 and X CO 2 , respectively. To assess the fluxes of the dairies, these differential measurements are used in conjunction with the local atmospheric dynamics from wind measurements at two local airports and from the WRF-LES simulations at 111m resolution. Our top-down CH 4 emissions derived using the Fourier transform spectrometers (FTS) observations of 1.4 to 4.8ppts -1 are in the low end of previous top-down estimates, consistent with reductions of the dairy farms and urbanization in the domain. However, the wide range of inferred fluxes points to the challenges posed by the heterogeneity of the sources and meteorology. Inverse modeling from WRF-LES is utilized to resolve the spatial distribution of CH 4 emissions in the domain. Both the model and the measurements indicate heterogeneous emissions, with contributions from anthropogenic and biogenic sources at Chino. A Bayesian inversion and a Monte Carlo approach are used to provide the CH 4 emissions of 2.2 to 3.5ppts -1 at Chino.

54 ENVIRONMENTAL SCIENCES↗

An Analysis of Operational Total Lightning Data During Long-Track Tornadoes

The 27 April 2011 tornado outbreak brought three distinct waves of tornadic thunderstorms to portions of Mississippi, Alabama, Tennessee, and Georgia, striking the Tennessee Valley of north Alabama and southern Tennessee particularly hard. A total of 42 tornado paths were surveyed across the fourteen county area covered by the National Weather Service (NWS) forecast office in Huntsville, Alabama. Ten of these tornadoes were on the ground for at least 20 miles, two had total path lengths over 130 miles, and six tornadoes were classified as violent (EF-4 or EF-5 on the Enhanced Fujita Scale). Many of these tornadoes occurred within the domain of the North Alabama Lightning Mapping Array (NALMA), a ground-based total lightning detection network owned and operated by the NASA Marshall Space Flight Center. Since 2003, the NASA Short-term Prediction Research and Transition Center has supplied data from NALMA in real time to NWS forecast offices in Huntsville, Knoxville/Tri-Cities, Birmingham, and Nashville. Previous research has documented the utility of total lightning information in predicting tornadogenesis, particularly when combined with other remote sensing tools. Basic warning decision-making during events such as 27 April is not the most difficult part of the process; instead, the focus of warning meteorologists shifts to looking for changes in intensity or possible particularly dangerous situations, since doppler radar velocity data often cannot distinguish between weak and strong tornadoes. To that end, this research attempts to determine if any correlation exists between flash densities of the longest-tracked tornadoes over time, and the surveyed wind speeds of the tornadoes. The long-track EF-5 tornado which struck the Hackleburg, Phil Campbell, and Tanner communities in north Alabama was the primary focus of this research due to its intensity and extended life cycle. However, not all tornadoes were available for total lightning analysis due to widespread power outages which negatively affected the detection efficiency and operation of the NALMA. Therefore, additional storms from 2008-2010 with tracks of at least 20 miles were analyzed for comparison purposes.

Carcione, Brian C.↗

Impact of magnetic fields on ram pressure stripping in disk galaxies

Ram pressure stripping can remove significant amounts of gas from galaxies in clusters and massive groups and thus has a large impact on the evolution of cluster galaxies. Recent observations have shown that key properties of ram-pressure-stripped tails of galaxies, such as their width and structure, are in conflict with predictions by simulations. To increase the realism of existing simulations, we simulated for the first time a disk galaxy exposed to a uniformly magnetized wind including radiative cooling and self-gravity of the gas. We find that magnetic fields have a strong effect on the morphology of the gas in the tail of the galaxy. While in the purely hydrodynamical case the tail is very clumpy, the magnetohydrodynamical case shows very filamentary structures in the tail. The filaments can be strongly supported by magnetic pressure and, wherever this is the case, the magnetic fields vectors tend to be aligned with the filaments. The ram pressure stripping process may lead to the formation of magnetized density tails that appear as bifurcated in the plane of the sky and resemble the double tails observed in ESO 137-001 and ESO 137-002. Such tails can be formed under a variety of situations, both for the disks oriented face-on with respect to the intracluster medium (ICM) wind and for the tilted ones. While this bifurcation is the consequence of the generic tendency for the magnetic fields to produce very filamentary tail morphology, the tail properties are further shaped by the combination of the magnetic field orientation and the sliding of the field past the disk surface exposed to the wind. Despite the fact that the effect of the magnetic field on the morphology of the tail is strong, magnetic draping does not strongly change the rate of gas stripping. For a face-on galaxy, the field tends to reduce the amount of gas stripping compared to the pure hydrodynamical case, and is associated with the formation of a stable magnetic draping layer on the side of the galaxy exposed to the incoming ICM wind. For significantly tilted disks, the situation may be reversed and the stripping rate may be enhanced by the 'scraping' of the disk surface by the magnetic fields sliding past the ISM/ICM interface. Instabilities, such as gravitational instabilities, undo the protective effect of this layer and allow the gas to leak out of the galaxy.

79 ASTRONOMY AND ASTROPHYSICS↗

X-Band Radar and Surface-Based Observations of Cold-Season Precipitation in Western Colorado’s Complex Terrain

Abstract Hydrologic processes associated with intermountain cold-season precipitation in the Upper Colorado River basin have important impacts on avalanche forecasting and water resource management. However, traditional weather radar networks struggle with observations in this complex terrain. Data collected during the Study of Precipitation, the Lower Atmosphere, and the Surface for Hydrometeorology (SPLASH) and its sister campaign, Surface Atmosphere Integrated Field Laboratory (SAIL) in the East River watershed of western Colorado, are used to examine a multistorm period from 23 December 2021 to 1 January 2022 that contributed 35% of the total winter precipitation in this watershed. Dual-polarization X-band radar and disdrometer measurements show ∼30-mm differences in precipitation amount at two sites in proximity over four distinct storm events within the period. Wind patterns, synoptic forcings, microphysical characteristics of precipitation, and surface meteorology are analyzed to explain the observed spatial variability of cold-season precipitation in complex mountainous terrain. Analysis shows that differences over time within this event are mainly accounted for by synoptic forcings, such as frontal passages; differences between sites are accounted for by the impact of variations in local wind patterns on precipitation microphysics. Patterns of surface precipitation intensity are compared and found to be correlated with X-band radar signatures; a relationship between a strong dendritic growth stage and intense low-density surface precipitation is reinforced by this study. This relationship demonstrates the importance of particle growth mechanisms on surface snowfall patterns in high-altitude complex terrain, underscoring the importance of realistic microphysical parameterizations. Significance Statement The amount and density of snowpack from western Colorado winter storms have significant impacts on water resources in the Upper Colorado River basin. Snowpack characteristics are affected by small-scale differences in how snow forms in the atmosphere. These differences are hard to study in the complex terrain of the Rockies, but data from the SPLASH and SAIL field campaigns allows us to investigate how snow crystal formation and mountain-driven wind patterns affect snow near the surface. Our study finds that snow crystal growth varies over small space and time scales and is likely controlled by the terrain beneath a given location and resultant local wind patterns. These results imply that predicting snowpack in the Rockies requires properly representing local wind patterns and crystal growth processes in models.

Heflin, Stella↗

Amazonian Moisture Recycling Revisited Using WRF With Water Vapor Tracers

Previous studies have estimated that 25%–35% of Amazonian precipitation comes from evapotranspiration (ET) within the basin. However, due to simplifying assumptions of traditional models, these studies primarily focus on large spatial and temporal scales. This study is the first to analyze the moisture of Amazonian origin at the annual to daily timescale in four different subregions of the Amazon. We analyze the sources, sinks and stores of moisture that originates as Amazonian ET. To do this, we use the Weather Research and Forecast (WRF) regional meteorological model with the added capability of water vapor tracers to track this moisture. Moisture of Amazonian origin shows strong annual and semi-annual signals, with contrasting behavior between the northern and southern parts of the basin. The tracers reveal a strong diurnal cycle of Amazonian water vapor which had not been previously reported. This signal is related to the diurnal cycle of ET, convective precipitation and advected moisture. ET's contribution to atmospheric moisture increases from early morning into the afternoon. Some of this moisture is rained out through convective storms in the early evening. Later in the night and following morning, strong winds associated with the South American Low Level Jet advect moisture downwind. Overall, the beating pattern becomes apparent when visualizing the Amazonian water vapor as an animation.

54 ENVIRONMENTAL SCIENCES↗

Lower Stratospheric Temperature Differences Between Meteorological Analyses in two cold Arctic Winters and their Impact on Polar Processing Studies

A quantitative intercomparison of six meteorological analyses is presented for the cold 1999-2000 and 1995-1996 Arctic winters. The impacts of using different analyzed temperatures in calculations of polar stratospheric cloud (PSC) formation potential, and of different winds in idealized trajectory-based temperature histories, are substantial. The area with temperatures below a PSC formation threshold commonly varies by approximately 25% among the analyses, with differences of over 50% at some times/locations. Freie University at Berlin analyses are often colder than others at T is less than or approximately 205 K. Biases between analyses vary from year to year; in January 2000. U.K. Met Office analyses were coldest and National Centers for Environmental Prediction (NCEP) analyses warmest. while NCEP analyses were usually coldest in 1995-1996 and Met Office or NCEP[National Center for Atmospheric Research Reanalysis (REAN) warmest. European Centre for Medium Range Weather Forecasting (ECMWF) temperatures agreed better with other analyses in 1999-2000, after improvements in the assimilation model. than in 1995-1996. Case-studies of temperature histories show substantial differences using Met Office, NCEP, REAN and NASA Data Assimilation Office (DAO) analyses. In January 2000 (when a large cold region was centered in the polar vortex), qualitatively similar results were obtained for all analyses. However, in February 2000 (a much warmer period) and in January and February 1996 (comparably cold to January 2000 but with large cold regions near the polar vortex edge), distributions of "potential PSC lifetimes" and total time spent below a PSC formation threshold varied significantly among the analyses. Largest peaks in "PSC lifetime" distributions in January 2000 were at 4-6 and 11-14 days. while in the 1996 periods, they were at 1-3 days. Thus different meteorological conditions in comparably cold winters had a large impact on expectations for PSC formation and on the discrepancies between different meteorological analyses. Met Office. NCEP, REAN, ECMWF and DAO analyses are commonly used for trajectory calculations and in chemical transport models; the choice of which analysis to use can strongly influence the results of such studies.

Manney, Gloria L.↗

The Antarctic Stratospheric Warming and its Impacts in 2019

We explore the mechanism, predictability and hemispheric-wide surface impacts of a rare stratospheric warming that occurred above Antarctica during austral spring (September to November) 2019, using the Japanese 55-year reanalysis set for the period 1979-2019. From late August to mid-September, the stratospheric polar vortex suddenly weakened, and the stratospheric temperatures dramatically rose over the Antarctic polar cap. The deceleration of the vortex observed at 10 hPa was as drastic as that of the first ever observed major sudden stratospheric warming in the SH during 2002, while the mean warming in the mid-stratosphere (~30hPa) over the course of spring 2019 broke the previous record of 2002 by ~50%. The key mechanism for this event was a poleward shift of the polar night jet near the stratopause during mid-winter and subsequent record strong planetary wavenumber-one activity propagating from the troposphere in August, which acted to dramatically weaken the polar vortex. The easterly wind anomalies and positive temperature anomalies moved downward to the surface during October to December, causing the index polarity of the Southern Annular Mode (SAM) to become record-negative for the season. The record negative SAM played a key role in inducing significant local climate extremes over eastern Australia, southern New Zealand, eastern South America and western Patagonia. Especially, the strong negative SAM was the key driver of the extreme hot and dry conditions over subtropical eastern Australia in late spring 2019 that, in turn, were conducive for the severe wildfires that occurred during that time. State-of-the-art dynamical sub-seasonal to seasonal forecast systems skilfully predicted the upward propagating wavenumber-one activity in August, the significant vortex weakening of austral spring 2019, and subsequent development of negative SAM from late July.

Eun-Pa Lim↗

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