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Patrick Taylor

Publications and source records attributed to Patrick Taylor.

Transient Effects in Atmosphere and Ionosphere Preceding the 2015 M7.8 and M7.3 Gorkha–Nepal Earthquakes

We analyze retrospectively/prospectively the transient variations of six different physical parameters in the atmosphere/ionosphere during the M7.8 and M7.3 earthquakes in Nepal, namely: 1) outgoing longwave radiation (OLR) at the top of the atmosphere (TOA); 2) GPS/TEC; 3) the very-low-frequency (VLF/LF) signals at the receiving stations in Bishkek (Kyrgyzstan) and Varanasi (India); 4) Radon observations; 5) Atmospheric chemical potential from assimilation models; and; 6) Air Temperature from NOAA ground stations. We found that in mid-March 2015, there was a rapid increase in the radiation from the atmosphere observed by satellites. This anomaly was located close to the future M7.8 epicenter and reached a maximum on April 21–22. The GPS/TEC data analysis indicated an increase and variation in electron density, reaching a maximum value during April 22–24. A strong negative TEC anomaly in the crest of EIA (Equatorial Ionospheric Anomaly) occurred on April 21, and a strong positive anomaly was recorded on April 24, 2015. The behavior of VLF-LF waves along NWC-Bishkek and JJY-Varanasi paths has shown abnormal behavior during April 21–23, several days before the first, stronger earthquake. Our continuous satellite OLR analysis revealed this new strong anomaly on May 3, which was why we anticipated another major event in the area. On May 12, 2015, an M7.3 earthquake occurred. Our results show coherence between the appearance of these pre-earthquake transient’s effects in the atmosphere and ionosphere (with a short time-lag, from hours up to a few days) and the occurrence of the 2015 M7.8 and M7.3 events. The spatial characteristics of the pre-earthquake anomalies were associated with a large area but inside the preparation region estimated by Dobrovolsky-Bowman. The preearthquake nature of the signals in the atmosphere and ionosphere was revealed by simultaneous analysis of satellite, GPS/TEC, and VLF/LF and suggest that they follow a general temporal-spatial evolution pattern that has been seen in other large earthquakes worldwide

Dimitar Ouzounov↗

TPSAS-NF1676L-30397-DND

Arctic low clouds strongly affect the Arctic surface energy budget, and through this impact influence rest of the Arctic climate system: namely surface and atmospheric temperature, sea ice extent and thickness, and the atmospheric circulation. Arctic clouds are in turn influenced by the Arctic climate system creating the potential for cloud-climate feedbacks. We quantify the influence of atmospheric state on the surface cloud radiative effect (CRE) and the covariability between surface CRE and sea ice concentration (SIC) using instantaneous, active remote sensing satellite footprint data from the NASA A-Train. First, the results indicate significant differences in the surface CRE when stratified by atmospheric state. Second, a statistically insignificant covariability is found between CRE and SIC for most atmospheric regimes. Third, we find a statistically significant increase in the surface longwave CRE at with decreased SIC in fall. Specifically, a +3-5 W m 2 larger longwave CRE is found over footprints with 0% versus 100% SIC. Because systematic changes of 1 W m 2 are sufficient to explain the observed reductions in Arctic sea ice, our results (1) indicate a potentially significant amplifying sea ice-cloud feedback that could delay fall freeze-up influencing sea ice variability under certain atmospheric conditions and (2) suggest that a small change in the frequency of atmosphere states may yield a larger Arctic cloud feedback than any cloud response to sea ice.

Patrick Taylor↗

TPSAS-NF1676L-30053-DND

The 2016-17 Arctic sea ice growth season (October-March) exhibited one of the lowest end-of-season sea ice volume and extent of any year since 1979. An analysis of MERRA2 atmospheric reanalysis data and CERES radiative flux data reveals that a record warm and moist Arctic atmosphere supported the reduced sea ice growth through two pathways. First, numerous regional episodes of increased atmospheric temperature and moisture, transported from lower latitudes, increased the cumulative energy input from downwelling longwave surface fluxes. Second, in those same episodes, the efficiency that the atmosphere cooled radiatively to space was reduced, increasing the amount of energy retained in the Arctic atmosphere and reradiated back toward the surface. Overall, the Arctic radiative cooling efficiency shows a decreasing trend since 2000. The results presented highlight the increasing importance of atmospheric forcing on sea ice variability demonstrating that episodic Arctic atmospheric rivers, regions of elevated poleward water vapor transport, and the subsequent surface energy budget response is a critical mechanism actively contributing to the evolution of Arctic sea ice.

Bradley Hegyi↗

TPSAS-NF1676L-30631-DND

Arctic low clouds strongly affect the Arctic surface energy budget, and through this impact influence rest of the Arctic climate system: namely surface and atmospheric temperature, sea ice extent and thickness, and the atmospheric circulation. Arctic clouds are in turn influenced by the Arctic climate system creating the potential for cloud-climate feedbacks. We quantify the influence of atmospheric state on the surface cloud radiative effect (CRE) and the covariability between surface CRE and sea ice concentration (SIC) using instantaneous, active remote sensing satellite footprint data from the NASA A-Train. First, the results indicate significant differences in the surface CRE when stratified by atmospheric state. Second, a statistically insignificant covariability is found between CRE and SIC for most atmospheric regimes. Third, we find a statistically significant increase in the surface longwave CRE at with decreased SIC in fall. Specifically, a +3-5 W m^-2 larger longwave CRE is found over footprints with 0% versus 100% SIC. Because systematic changes of 1 W m^-2 are sufficient to explain the observed reductions in Arctic sea ice, our results (1) indicate a potentially significant amplifying sea ice-cloud feedback that could delay fall freeze-up influencing sea ice variability under certain atmospheric conditions and (2) suggest that a small change in the frequency of atmosphere states may yield a larger Arctic cloud feedback than any cloud response to sea ice.

Patrick Taylor↗

TPSAS-NF1676L-27659-DND

The Arctic is warming fast, a trend expected to continue. Rapid Arctic warming has far-reaching implications affecting the global energy budget, sea level rise, the global carbon cycle, and potentially the atmospheric and oceanic circulation. Our understanding of the forcing mechanisms driving Arctic climate change has rapidly evolved in the last decade. For 40 years, the melting of sea ice and snow has been implicated as the primary driver of amplified Arctic warming, however our results indicate a shift, whereby changes in the atmospheric temperature, humidity, and clouds have surpassed the warming effects of snow and sea ice loss in the latest CMIP5 model simulations. We examine the impacts of climate feedbacks on the Arctic surface energy budget: namely surface albedo, clouds, shortwave clear-sky feedbacks, longwave clear-sky feedbacks, ocean heat content, and surface turbulent fluxes. Simulations from 16 CMIP5 models running RCP8.5, a high-emission scenario are used. We employ the methodology used in Lu and Cai (2009) on a single CMIP3 model allowing an analysis of changes between CMIP3 and CMIP5.

Robyn C Boeke↗

TPSAS-NF1676L-29139-DND

The Arctic has been warming at a rate outpacing globally-averaged warming by 2-3 times, a phenomenon known as "Arctic Amplification" (AA). AA is evident in observations of Arctic surface temperature over the last century as well as in model predictions. The accuracy of model predictions is crucial to determine our response to climate change, as Arctic changes have consequences for the atmospheric circulation, sea level rise, and the carbon cycle. Unfortunately, models show a wide range of possible futures and intermodel spread in projections of Arctic temperature is larger than for any other region: a 2°C global temperature increase- the limit set by the Paris Climate Agreement- would lead to an Arctic temperature change between 3-7°C according to Coupled Model Intercomparison 5 (CMIP5) models. This intermodel spread represents a key deficiency in the understanding of Arctic feedback processes and how changes in various physical parameters (e.g. sea ice cover, clouds, heat transport and surface fluxes) affect the temperature response. Using a process-oriented decomposition of the simulate Arctic surface energy budget, we attribute the largest contribution to the CMIP5 intermodel spead in projected Arctic warming to the Barents-Kara Sea region. Our results reveal that the increasing seasonal fluxing of ocean heat content is a significant part of the intermodel spread in AA and relates strongly to change in surface turbulent fluxes. Our results indicate that if we are to significantly reduce the intermodel spread in projected AA we must focus on understanding the behavior and physical processes that drive surface energy flows in the B-K sea region.

Patrick Taylor↗

Thermal radiation effects in the atmosphere initiated by pre-earthquake processes

The science community is still looking for pre-earthquake indicators of major seismic events in order to minimize the loss of human life. Recent advances in satellite technology have helped to increase the scientific understanding of the nature of pre-earthquake phenomena in the atmosphere and their relationship with transitional thermal anomalies. It was realized that the thermal heat fluxes over areas of earthquake preparation are a result of air ionization by Rn222, its isotopes and progenies and consequent water vapor condensation on newly formed ions. Latent heat (LH) is released as a result of this process and leads to the formation of local thermal radiation anomalies (TRA) known as outgoing longwave radiation (OLR). We recorded data from the most recent major earthquakes in California (2014) Nepal (2015) that allowed us to summaries TRA's main morphological features. It was also established that the TRA is part of a more complex chain of the short‐term earthquake precursors, which are explained within the framework of a Lithosphere-Atmosphere-Ionosphere Coupling (LAIC) model.

Dimitar Ouzounov↗

Concept for a Far-infrared Outgoing Radiation Closure Experiment – Antarctica (FORCE-A)

The next decade promises to be an incredibly exciting time in climate science. There are two new space flight missions, PREFIRE and FORUM, that will open the far-infrared spectrum to direct, accurate observations for the first time. PREFIRE is planned to operate between 2022 and 2024 and FORUM will launch in late 2025 or early 2026. The TICFIRE instrument is also a candidate for the NASA A-CCP mission to be launched in the 2028 timeframe. A key focus of these missions and instruments is improved understanding of polar climates. In support of these missions we present a concept for a radiative closure experiment to be conducted in Antarctica during the PREFIRE mission lifetime and then again during the operational FORUM and TICFIRE/A-CCP missions. The main component of the campaigns would be a long-duration balloon flight launched from McMurdo Station with the potential of 1-2 months aloft. Candidate balloon flight instrumentation includes a far-IR Fourier transform spectrometer and far-IR radiometers. Ground based instrumentation includes zenith viewing infrared and far-infrared spectrometers, lidars, and microwave radiometers. The objective of the FORCE-A campaign is to demonstrate radiative closure in the infrared with the multiple campaign instruments combined with the numerous relevant satellite instruments that pass overhead every 30 minutes (AIRS, CrIS, IASI, MODIS, VIIRS, CERES, BBR, Libera). The campaign will serve to advance radiation sciences as well as to provide the means for validation of the new far-infrared observations.

Martin G Mlynczak↗

Comparison of Observed Longwave, Shortwave Irradiance and Surface Temperature from “MOSAiC” to CERES Radiative Transfer Calculations and Inputs

As atmospheric temperatures rise due to increased anthropogenic forcing, the effect is expected to be larger over the arctic than midlatitude and tropics, known as polar amplification. A multi-national program, the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) was ran between Sept 2019 and Oct 2020. The project deployed scientific instruments on board the German research vessel Polarstern with the ship remaining across a year to observe all aspects of polar climate. The US DOE deployed the ARM AMF2 aboard the ship along with several off-ship sites for extended spatial observations. Of particular importance was the measurement of the energetics of the ice/ocean/atmosphere interactions through observations of surface irradiance and surface temperatures. NASA’s Clouds and the Earth’s Radiant Energy System (CERES) project produces the SYN1deg Edition 4 data product. This product provides high quality, hourly, globally gridded and temporally complete maps of top of atmosphere (TOA), in atmosphere, and surface irradiances. TOA fluxes are derived from CERES instruments and geostationary satellites. In addition, TOA, in atmosphere, and surface irradiances are computed using the Langley Fu and Liou radiative transfer model. The radiative transfer model is run hourly at 1 degree ~equal area spatial resolution. Meteorological profiles are provided by Global Modeling and Assimilation Office’s GEOS-541 reanalysis product. Cloud properties are derived solely from Terra and Aqua MODIS imagers northward of 60°. Here we compare SYN1deg hourly calculations of surface irradiance to observations from the AMF2 to validate the products estimates of surface irradiance in this challenging area. Along with the irradiance comparisons we take a close look at the surface temperature record in the GEOS-541 product and compare it over both time and space to several surface observations provided by MOSAiC. Along with the comparison to the re-analysis record we will compare these observed surface temperatures to those derived from the AIRS product, which is known to have some difficulty in extreme high latitude areas. The goals of this study are 1) understand computed surface downward irradiance and temperature error separated by surface type (e.g. sea ice or open water) and by season, and 2) error covariance in spatial and temporal space. We seek to use this information to extrapolate the error from the MOSAiC domain to a larger arctic region.

David A Rutan↗

Changes in Characteristics of Future Climate Across the U.S.: Time Series Analysis of Climate Model Data by NASA POWER

NASA’s Prediction of Worldwide Energy Resource (POWER) project facilitates the use of NASA Earth Science data holdings within the energy, agricultural, and building heating/cooling design industries. POWER packages solar and meteorological data at various temporal levels from several NASA projects in a user friendly GIS-enabled web services system (https://power.larc.nasa.gov). Data users can access these data either through an intuitive data viewer, image services fully integrable with GIS analysis, connections in the cloud through an Amazon Web Services S3 Bucket, or fully customizable access through an API. Data provided by POWER has been used to remotely monitor solar array fields and integrated in a sizing tool for off-grid solar and storage systems. POWER data has also been coupled with key building decision tools to support design and retrofitting of building energy systems for energy efficiency and reduction of greenhouse gases. POWER is now developing capabilities to provide time series of the projected future evolution of surface quantities important to future energy production and use, such as heating/cooling degree days, temperature, wind speed, and downwelling solar flux. We present here a range of possible future changes in these quantities at locations throughout the continental United States. We show how both average and extreme values of the quantities will evolve from present-day to future climate conditions. We plan to provide these projections for users in the energy and sustainable energy communities.

Bradley M. Hegyi↗

A LaGrangian Perspective of the Surface Energy Budget Contributions to Sea Ice Evolution in the ‘New Arctic’

Recent Arctic warming outpaces global warming and is characterized by dramatic changes in sea ice (record sea ice loss, thinner and more seasonal ice cover), warming SSTs, and a lengthening melt season. These changes impact the surface energy budget and the sensitivity of sea ice to radiative forcing, namely an increased sensitivity of thinner ice to local radiative forcings and a weaker buffering of surface-atmosphere exchanges of heat and moisture. However, these processes are a large source of uncertainty in global climate models with prior studies finding that poor representations of downwelling longwave radiation and sea ice albedo lead to model spread in sea ice conditions. A limitation of prior work is examining sea ice-atmosphere interactions through an Eulerian framework. This study utilizes a sea ice parcel dataset in a LaGrangian framework, allowing for tracking of surface energy budget-sea ice interactions over the lifespan of individual sea ice parcels; this framework also allows for the quantification of the sea ice response to episodic weather events along with seasonal drivers, including the drivers of rapid growth and melt events. First, lag-lead relationships between relevant surface energy budget terms and sea ice thickness changes are explored to understand the atmospheric conditions preceding rapid growth and melt. The impact of episodic events- moisture intrusion, warm air outbreaks, cyclones- on sea ice growth are also investigated by stratifying first-year parcels by sea ice thickness at the end of the growth season and analyzing the effect of atmospheric variability (number and intensity of episodic events) on parcel thickness change. Lastly, parcel growth and melt and the associated radiative anomalies are compared to snowfall events/snow thickness to determine how snowfall modifies the interaction between the local surface energy budget and sea ice mass balance.

Patrick Taylor↗

NASA POWER: Providing Present and Future Climate Services Based on NASA Data for the Energy, Agricultural, and Sustainable Buildings Communities

NASA’s Prediction of Worldwide Energy Resource (POWER) project facilitates the use of NASA Earth Science data holdings within the renewable energy, agricultural, and building heating/cooling design industries. POWER packages solar and meteorological data at various temporal levels from several NASA projects in a user friendly GIS-enabled web services system (https://power.larc.nasa.gov). Data users can access these data either through an intuitive data viewer, image services fully integrable with GIS analysis, connections in the cloud through an Amazon Web Services S3 Bucket, or fully customizable access through an API. Data provided by POWER has been successfully used by decision makers to support actions that address climate change. For example, POWER data has been used to remotely monitor solar array fields and integrated in a sizing tool for off-grid solar and storage systems. POWER data has also been coupled with key building decision tools to support design and retrofitting of building energy systems for energy efficiency and reduction of greenhouse gases. POWER is now developing climate services to provide time series of the projected future evolution of key quantities that interest our users, such as heating/cooling degree days, temperature, wind speed, and downwelling solar flux. We demonstrate the potential of the new climate services by presenting here a range of possible future changes in these quantities at different NASA centers across the continental United States. These data services are based on downscaled climate model data from the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) data set. We highlight the important insights that new climate services can provide. Our climate services will help our user communities quantify the impacts of climate change to support their key decisions in planning for the future, both inside and outside the Federal Government, especially for decisions in renewable energy and in building heating and cooling.

Bradley Hegyi↗

Arctic Radiation-Cloud-Aerosol-Surface Interaction eXperiment (ARCSIX)

The Arctic climate system is amidst a transition. Over the last 40 years, the Arctic sea ice pack has transformed from a predominantly thick, multi-year sea ice to a predominantly thin, seasonal sea ice, termed the “New Arctic”. The observed rapid changes in the Arctic sea ice pack are an integral part of the Arctic Amplification phenomenon and represent a response to and a feedback on global climate change. As a result, the role of the Arctic within the global climate system is changing. Substantial uncertainty exists in our understanding of the atmosphere-surface interactions within the Arctic system, limiting our knowledge of the Arctic’s role in the future climate. Advancing our understanding of the Arctic climate system requires (1) measurements of the coupling between radiative processes and sea ice surface properties during summer sea ice melt; (2) measurements of the processes controlling the predominant Arctic cloud regimes and their properties (Fig. 1); and (3) improvements in the ability to monitor Arctic cloud, radiation, and sea ice processes from space. A key challenge is that thin, low clouds that are radiatively important to the Arctic surface energy budget can go undetected (Fig. 1). The Arctic Radiation-Cloud-Aerosol-Surface-Interaction eXperiment (ARCSIX) is an airborne campaign based at the Pituffik Space Base in Greenland from May-August 2024 sponsored by the National Aeronautics and Space Administration (NASA) to address these needs. ARCSIX consists of two airborne measurement campaigns taking place in two 3-week intervals during the early and late sea ice melt season: late May through early June and late July through early August, respectively. ARCSIX science is guided by three broad science questions that encapsulate the key influences of radiation-cloud-aerosol-sea ice coupling and a remote sensing and modeling objective: Science Question 1 (Radiation): What is the impact of the predominant summer Arctic cloud types on the radiative surface energy budget? Science Question 2 (Cloud Life Cycle): What processes control the evolution and maintenance of the predominant cloud regimes in the summertime Arctic? Science Question 3 (Sea Ice): How do the two-way interactions between surface properties and atmospheric forcings affect the sea ice evolution? Remote Sensing and Modeling Objective: Enhance our long-term space-based monitoring and predictive capabilities of Arctic sea ice, clouds, and aerosols.

Patrick Taylor↗