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Effect of Baseline Period on Quantification of Climate Extremes Over the United States
Extreme climate events are societally harmful and have increased in frequency and intensity in recent decades. Indices based on temperature and precipitation are a valuable way to quantify climate extremes. Certain indices are defined relative to percentiles, which are dependent on a climatological baseline period. In this study, indices computed using temperature and precipitation from the Modern Era Retrospective Analysis for Research and Applications, Version 2 are calculated using percentiles from three baseline periods: 1981–2010, 1991–2020 and 1981–2020. Updating the baseline period from 1981 to 2010 to 1991–2020 leads to significant changes in the quantification of temperature and precipitation extremes over the United States over 1980–2021. Using the later baseline period indicates more cold extremes, fewer warm extremes, and fewer but more intense precipitation extremes throughout the US, with regional variation. Changing the baseline period can mislead the public and decision makers, potentially undermining the appropriate response to climate-related health risks.
Investigating the potential of a global precipitation forecast to inform landslide prediction
Extreme rainfall events within landslide-prone areas can be catastrophic, resulting in loss of property, infrastructure, and life. A global Landslide Hazard Assessment for Situational Awareness (LHASA) model provides routine near-real time estimates of landslide hazard using Integrated Multi-Satellite Precipitation Retrievals for the Global Precipitation Mission (IMERG). However, it does not provide information on potential landslide hazard in the future. Forecasting potential landslide events at a global scale presents an area of open research. This study compares a global precipitation forecast provided by NASA's Goddard Earth Observing System (GEOS) with near-real time satellite precipitation estimates. The Multi-Radar Multi-Sensor gauge corrected (MRMS-GC) reference is used to assess the performance of both satellite and model-based precipitation products over the contiguous United States (CONUS). The forecast lead time of 24hrs is considered, with a focus on extreme precipitation events. The performance of IMERG and GEOS-Forecast products is assessed in terms of the probability of detection, success ratio, critical success index and hit bias as well as continuous statistics. The results show that seasonality influences the performance of both satellite and model-based precipitation products. Comparison of IMERG and GEOS-Forecast globally as well as in several event case studies (Colombia, southeast Asia, and Tajikistan) reveals that GEOS-Forecast detects extreme rainfall more frequently relative to IMERG for these specific analyses. For recent landslide points across the globe, the 24hr accumulated precipitation forecast >100 mm corresponds well with near-real time daily accumulated IMERG precipitation estimates. GEOS-Forecast and IMERG precipitation match more closely for tropical cyclones than for other types of storms. The main intention of this study is to assess the viability of using a global forecast for landslide predictions and understand the extent of the variability between these products to inform where we would expect the landslide modeling results to most prominently diverge. Results of this study will be used to inform how forecasted precipitation estimates can be incorporated into the LHASA model to provide the first global predictive view of landslide hazards.
Investigating the Potential of A Global Precipitation Forecast to Inform Landslide Prediction
Extreme rainfall events within landslide-prone areas can be catastrophic, resulting in loss of property, infra-structure, and life. A global Landslide Hazard Assessment for Situational Awareness (LHASA) model provides routine near-real time estimates of landslide hazard using Integrated Multi-Satellite Precipitation Retrievals for the Global Precipitation Mission (IMERG). However, it does not provide information on potential landslide hazard in the future. Forecasting potential landslide events at a global scale presents an area of open research. This study compares a global precipitation forecast provided by NASA’s Goddard Earth Observing System (GEOS) with near-real time satellite precipitation estimates. The Multi-Radar Multi-Sensor gauge corrected (MRMS-GC) reference is used to assess the performance of both satellite and model-based precipitation products over the contiguous United States (CONUS). The forecast lead time of 24hrs is considered, with a focus on extreme precipitation events. The performance of IMERG and GEOS-Forecast products is assessed in terms of the probability of detection, success ratio, critical success index and hit bias as well as continuous statistics. The results show that seasonality influences the performance of both satellite and model-based precipitation products. Comparison of IMERG and GEOS-Forecast globally as well as in several event case studies (Colombia, southeast Asia, and Tajikistan) reveals that GEOS-Forecast detects extreme rainfall more frequently relative to IMERG for these specific analyses. For recent landslide points across the globe, the 24hr accumulated precipitation forecast >100 mm corresponds well with near-real time daily accumulated IMERG precipitation estimates. GEOS-Forecast and IMERG precipitation match more closely for tropical cyclones than for other types of storms. The main intention of this study is to assess the viability of using a global forecast for landslide predictions and understand the extent of the variability between these products to inform where we would expect the landslide modeling results to most prominently diverge. Results of this study will be used to inform how forecasted precipitation estimates can be incorporated into the LHASA model to provide the first global predictive view of landslide hazards.
Introduction to Special Collection ``The Exceptional Arctic Stratospheric Polar Vortex in 2019/2020: Causes and Consequences"
This paper introduces the special collection in Geophysical Research Letters and Journal of Geophysical Research: Atmospheres on the exceptional stratospheric polar vortex in 2019/2020. Papers in this collection show that the 2019/2020 stratospheric polar vortex was the strongest, most persistent, and coldest on record in the Arctic. The unprecedented Arctic chemical processing and ozone loss in spring 2020 have been studied using numerous satellite and ground-based data sets and chemistry-transport models. Quantitative estimates of chemical loss are broadly consistent among the studies and show profile loss of about the same magnitude as in the Arctic in 2011, but with most loss at lower altitudes; column loss was comparable to or larger than that in 2011. Several papers show evidence of dynamical coupling from the mesosphere down to the surface. Studies of tropospheric influence and impacts link the exceptionally strong vortex to reflection of upward propagating waves and show coupling to tropospheric anomalies, including extreme heat, precipitation, windstorms, and marine cold air outbreaks. Predictability of the exceptional stratospheric polar vortex in 2019/2020 and related predictability of surface conditions are explored. The exceptionally strong stratospheric polar vortex in 2019/2020 highlights the extreme interannual variability in the Arctic winter/spring stratosphere and the far-reaching consequences of such extremes.
Perspectives on Forced Predictability
This talk addresses the relationships between weather and El Nino/Southern Oscillation (ENSO) and various other low frequency atmospheric variations such as the Pacific/North American pattern. We focus, in particular, on the predictability of extreme wintertime precipitation events over the continental United States. We first examine fifty years of daily precipitation observations and quantify the leading patterns of winter weather variability. These weather systems, familiar to operational weather forecasters, account for many of the major flooding events on the west coast as well as the major winter snowstorms along the east coast. We next examine the statistics of these storm systems with a particular focus on the occurrence of extreme events. The leading weather systems show varying degrees of linkages to low frequency atmospheric variability. We show, for example, that on seasonal time scales the probability of occurrence of certain types of west coast storms is strongly enhanced by El Nino, while it is reduced during winters with an anomalous trough to the west of the dateline. ENSO also has a strong impact on storms that develop over the Gulf of Mexico and affect much of the eastern United States, with enhanced storminess during El Nino, and reduced storminess during La Nina conditions. We conclude with an example of how well current climate models are able to reproduce the basic linkages between weather and low frequency variability.
Global Monthly and Daily Precipitation Analysis for the Global Precipitation Climatology Project (GPCP): Global and Regional Variations and Trends
The 22 year, monthly, globally complete precipitation analysis of the World Climate Research Program's (WCRP/GEWEX) Global Precipitation Climatology Project (GPCP) and the four year (1997-present) daily GPCP analysis are described in terms of the data sets and analysis techniques used in their preparation. These analyses are then used to study global and regional variations and trends during the 22 years and the shorter-time scale events that constitute those variations. The GPCP monthly data set shows no significant trend in global precipitation over the twenty years, unlike the positive trend in global surface temperatures over the past century. The global trend analysis must be interpreted carefully, however, because the inhomogeneity of the data set makes detecting a small signal very difficult, especially over this relatively short period. The relation of global (and tropical) total precipitation and ENSO (El Nino and Southern Oscillation) events is quantified with no significant signal when land and ocean are combined. In terms of regional trends 1979 to 2000 the tropics have a distribution of regional rainfall trends that has an ENSO-like pattern with features of both the El Nino and La Nina. This feature is related to a possible trend in the frequency of ENSO events (either El Nino or La Nina) over the past 20 years. Monthly anomalies of precipitation are related to ENSO variations with clear signals extending into middle and high latitudes of both hemispheres. The El Nino and La Nina mean anomalies are near mirror images of each other and when combined produce an ENSO signal with significant spatial continuity over large distances. A number of the features are shown to extend into high latitudes. Positive anomalies extend in the Southern Hemisphere from the Pacific southeastward across Chile and Argentina into the south Atlantic Ocean. In the Northern Hemisphere the counterpart feature extends across the southern U.S. and Atlantic Ocean into Europe. In the Southern Hemisphere an anomaly feature is shown to spiral into the Antarctica land mass. The extremes of ENSO-related anomalies are also examined and indicate that globally, during both El Nino and La Nina, more extremes of precipitation (both wet and dry) occur than during the "neutral" regime, with the El Nino regime showing larger magnitudes. The distribution is different for the globe as a whole and when the area is restricted to just land. The recent (1998-present) Tropical Rainfall Measuring Mission (TRMM) observations are also compared with the GPCP analyses and are evaluated with regard to improving the long-term GPCP data set.
Variations and Trends in Global and Regional Precipitation Based on the 22-Year GPCP (Global Precipitation Climatology Project) and Three-Year TRMM (Tropical Rainfall Measuring Mission) Data Sets
This paper gives an overview of the analysis of global precipitation over the last few decades and the impact of the new TRMM precipitation observations. The 20+ year, monthly, globally complete precipitation analysis of the World Climate Research Program's (WCRP/GEWEX) Global Precipitation Climatology Project (GPCP) is used to study global and regional variations and trends and is compared to the much shorter TRMM(Tropical Rainfall Measuring Mission) tropical data set. The GPCP data set shows no significant trend in global precipitation over the twenty years, unlike the positive trend in global surface temperatures over the past century. The global trend analysis must be interpreted carefully, however, because the inhomogeneity of the data set makes detecting a small signal very difficult, especially over this relatively short period. The relation of global (and tropical) total precipitation and ENSO events is quantified with no significant signal when land and ocean are combined. Identifying regional trends in precipitation may be more practical. From 1979 to 2000 the tropics have pattern of regional rainfall trends that has an ENSO-like pattern with features of both the El Nino and La Nina. This feature is related to a possible trend in the frequency of ENSO events (either El Nino or La Nina) over the past 20 years. Monthly anomalies of precipitation are related to ENSO variations with clear signals extending into middle and high latitudes of both hemispheres. The El Nino and La Nina mean anomalies are near mirror images of each other and when combined produce an ENSO signal with significant spatial continuity over large distances. A number of the features are shown to extend into high latitudes. Positive anomalies extend in the Southern Hemisphere (S.H.) from the Pacific southeastward across Chile and Argentina into the south Atlantic Ocean. In the Northern Hemisphere (N.H.) the counterpart feature extends across the southern U.S. and Atlantic Ocean into Europe. Further to the west a negative anomaly extends southeastward again from the Maritime Continent across the South Pacific and through the Drake Passage. In the Southern Hemisphere an anomaly feature is shown to spiral into the Antarctica land mass. The extremes of ENSO-related anomalies are also examined and indicate that globally, during both El Nino and La Nina, more extremes of precipitation (both wet and dry) occur than during the "neutral" regime, with the El Nino regime showing larger magnitudes. The distribution is different for the globe as a whole and when the area is restricted to just land. The recent (1998-present) TRMM observations are compared with the similar period of GPCP analyses with very good agreement in terms of pattern and generally good agreement with regard to magnitude. However, there still are differences among the individual TRMM products using passive and active microwave techniques and these need to be resolved before longer-term products such as the GPCP analyses can be validated.
The Magnitude and Variability of Global and Regional Precipitation Based on the 22-Year GPCP (Global Precipitation Climatology Project) and Three-Year TRMM (Tropical Rainfall Measuring Mission) Data Sets
This paper gives an overview of the analysis of global precipitation over the last few decades and the impact of the new TRMM precipitation observations. The 20+ year, monthly, globally complete precipitation analysis of the World Climate Research Program's (WCRP/GEWEX) Global Precipitation Climatology Project (GPCP) is used to study global and regional variations and trends and is compared to the much shorter TRMM (Tropical Rainfall Measuring Mission) tropical data set. The GPCP data set shows no significant trend in precipitation over the twenty years, unlike the positive trend in global surface temperatures over the past century. The global trend analysis must be interpreted carefully, however, because the inhomogeneity of the data set makes detecting a small signal very difficult, especially over this relatively short period. Identifying regional trends in precipitation may be more practical. From 1979 to 1999 the northern mid-latitudes appear to be drying, the southern mid-latitudes have gotten wetter, and there is a mixed signal in the tropics. The relation between this field of trends and the relation to the frequency of El Nino events during this time period is explored. Monthly anomalies of precipitation are related to ENSO variations with clear signals extending into middle and high latitudes of both hemispheres. The El Nino and La Nina mean anomalies are near mirror images of each other and when combined produce an ENSO signal with significant spatial continuity over large distances. These El Nino minus La Nina composites of normalized precipitation show the usual positive, or wet, anomaly over the central and eastern Pacific Ocean with the negative, or dry, anomaly over the maritime continent along with an additional negative anomaly over Brazil and the Atlantic Ocean extending into Africa and a positive anomaly over the Horn of Africa and the western Indian Ocean. A number of the features are shown to extend into high latitudes. Positive anomalies extend in the Southern Hemisphere (S.H.) from the Pacific southeastward across Chile and Argentina into the south Atlantic Ocean. In the Northern Hemisphere (N.H.) the counterpart feature extends across the southern US and Atlantic Ocean into Europe. Further to the west a negative anomaly extends southeastward again from the Maritime Continent across the South Pacific and through the Drake Passage. The N.H. counterpart crosses the North Pacific and southern Canada. In the Southern Hemisphere an anomaly feature is shown to spiral into the Antarctica land mass. The extremes of ENSO-related anomalies are also examined and indicate that globally, during both El Nino and La Nina, more extremes of precipitation ( both wet and dry) occur than during the "neutral" regime, with the El Nino regime showing larger magnitudes. The distribution is different for the globe as a whole and when the area is restricted to just land. The recent (1998-present) TRMM observations are compared with the similar period of GPCP analyses with very good agreement in terms of pattern and generally good agreement with regard to magnitude. However, there still are differences among the individual TRMM products using passive and active microwave techniques and these need to be resolved before longer-term products such as the GPCP analyses can be validated.
Physical nature of the climatic and biological effects of the Peru current
Surface and depth flow processes and their effects on the behavior of the Peru current are considered in relation to climatological and biological effects for the entire western coast of South America. The mean annual coastal air temperature is from 2 deg to 6 deg below the norm and precipitation is extremely rare. An upwelling effect brings up the cold deep waters with their rich content of organic material responsible for the huge biological productivity of the region.
Importance of the Natural Terrestrial Environment with Regard to Advanced Launch Vehicle Design and Development
The terrestrial environment is an important forcing function in the design and development of the launch vehicle. The scope of the terrestrial environment includes the following phenomena: Winds; Atmospheric Thermodynamic Models and Properties; Thermal Radiation; U.S. and World Surface Environment Extremes; Humidity; Precipitation, Fog, and Icing; Cloud Characteristics and Cloud Cover Models; Atmospheric Electricity; Atmospheric Constituents; Vehicle Engine Exhaust and Toxic Chemical Release; Occurrences of Tornadoes and Hurricanes; Geological Hazards, and Sea States. One must remember that the flight profile of any launch vehicle is in the terrestrial environment. Terrestrial environment definitions are usually limited to information below 90 km. Thus, a launch vehicle's operations will always be influenced to some degree by the terrestrial environment with which it interacts. As a result, the definition of the terrestrial environment and its interpretation is one of the key launch vehicle design and development inputs. This definition is a significant role, for example, in the areas of structures, control systems, trajectory shaping (performance), aerodynamic heating and take off/landing capabilities. The launch vehicle's capabilities which result from the design, in turn, determines the constraints and flight opportunities for tests and operations.
Shock Re-equilibration of Fluid Inclusions
Fluid inclusions (microscopic volumes of fluid trapped within minerals as they precipitate) are extremely common in terrestrial minerals formed under a wide range of geological conditions from surface evaporite deposits to kimberlite pipes. While fluid inclusions in terrestrial rocks are nearly ubiquitous, only a few fluid inclusion-bearing meteorites have been documented. The scarcity of fluid inclusions in meteoritic materials may be a result of (a) the absence of fluids when the mineral was formed on the meteorite parent body or (b) the destruction of fluid inclusions originally contained in meteoritic materials by subsequent shock metamorphism. However, the effects of impact events on pre-existing fluid inclusions trapped in target and projectile rocks has received little study. Fluid inclusions trapped prior to the shock event may be altered (re-equilibrated) or destroyed due to the high pressures, temperatures, and strain rates associated with impact events. By examining the effects of shock deformation on fluid inclusion properties and textures we may be able to better constrain the pressure-temperature path experienced by terrestrial and meteoritic shocked materials and also gain a clearer understanding of why fluid inclusions are rarely found in meteorite samples.
Oxygen Ion Heat Rate within Alfvenic Turbulence in the Cusp
The role that the cleft/cusp has in ionosphere-magnetosphere coupling makes it a dynamic and important region. It is directly exposed to the solar wind, making it possible for the entry of electromagnetic energy and precipitating electrons and ions from dayside reconnection and other dayside events. It is also a significant source of ionospheric plasma, contributing largely to the mass loading of the magnetosphere with large fluxes of outflowing ions. Crossing the cusp/cleft near 5100 km, the Polar instruments observe the common correlation of downward Poynting flux, ion energization, soft electron precipitation, broadband extremely low-frequency (BB-ELF) emissions, and density depletions. The dominant power in the BB-ELF emissions is now identified to be from spatially broad, low frequency Alfv nic structures. For a cusp crossing, we determine using the Electric Field Investigation (EFI), that the electric and magnetic field fluctuations are Alfv nic and the electric field gradients satisfy the inequality for stochastic acceleration. With all the Polar 1996 horizontal crossings of the cusp, we determine the O+ heating rate using the Thermal Ion Dynamics Experiment (TIDE) and Plasma Wave Investigation (PWI). We then compare this heating rate to other heating rates assuming the electric field gradient criteria exceeds the limit for stochastic acceleration for the remaining crossings. The comparison suggests that a stochastic acceleration mechanism is operational and the heating is controlled by the transverse spatial scale of the Alfvenic waves.
An Overview of ARTMIP’s Tier 2 Reanalysis Intercomparison: Uncertainty in the Detection of Atmospheric Rivers and their Associated Precipitation
Atmospheric rivers, or long but narrow regions of enhanced water vapor transport, are an important component of the hydrologic cycle as they are responsible for much of the poleward transport of water vapor and result in precipitation, sometimes extreme in intensity. Despite their importance, much uncertainty remains in the detection of atmospheric rivers in large datasets such as reanalyses and century scale climate simulations. To understand this uncertainty, the Atmospheric River Tracking Method Intercomparison Project (ARTMIP) developed tiered experiments, including the Tier 2 Reanalysis Intercomparison that is presented here. Eleven detection algorithms submitted hourly tags--binary fields indicating the presence or absence of atmospheric rivers--of detected atmospheric rivers in the Modern Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) and European Centre for Medium-Range Weather Forecasts' Reanalysis Version 5 (ERA5) as well as six-hourly tags in the Japanese 55-year Reanalysis (JRA-55). Due to a higher climatological mean for integrated water vapor transport in MERRA-2, atmospheric rivers were detected more frequently relative to the other two reanalyses, particularly in algorithms that use a fixed threshold for water vapor transport. The finer horizontal resolution of ERA5 resulted in narrower atmospheric rivers and an ability to detect atmospheric rivers along resolved coastlines. The fraction of hemispheric area covered by ARs varies throughout the year in all three reanalyses, with different atmospheric river detection tools having different seasonal cycles.
Vegetation Greening Mitigates the Impacts of Increasing Extreme Rainfall on Runoff Events
Future flood risk assessment has primarily focused on heavy rainfall as the main driver, with the assumption that projected increases in extreme rain events will lead to subsequent flooding. However, the presence of and changes in vegetation have long been known to influence the relationship between rainfall and runoff. Here, we extract historical (1850–1880) and projected (2070–2100) daily extreme rainfall events, the corresponding runoff, and antecedent conditions simulated in a prominent large Earth system model ensemble to examine the shifting extreme rainfall and runoff relationship. Even with widespread projected increases in the magnitude (78% of the land surface) and number (72%) of extreme rainfall events, we find projected declines in event-based runoff ratio (runoff/rainfall) for a majority (57%) of the Earth surface. Runoff ratio declines are linked with decreases in antecedent soil water driven by greater transpiration and canopy evaporation (both linked to vegetation greening) compared to areas with runoff ratio increases. Using a machine learning regression tree approach, we find that changes in canopy evaporation is the most important variable related to changes in antecedent soil water content in areas of decreased runoff ratios (with minimal changes in antecedent rainfall) while antecedent ground evaporation is the most important variable in areas of increased runoff ratios. Our results suggest that simulated interactions between vegetation greening, increasing evaporative demand, and antecedent soil drying are projected to diminish runoff associated with extreme rainfall events, with important implications for society.
Coordinated spectral and temporal H-alpha observations of a solar flare
We report simultaneous observations of a flare (1991 January 11 18:25 UT) with a combination of spectra and high time resolution images in H-alpha. The Mees Solar Observatory CCD Imaging Spectrograph obtains spectra and spectroheliograms with a repetition rate of 14 s. These data permit the identification of sites of nonthermal electron precipitation or of high coronal pressure. We observe extremely strong electron precipitation in this flare; we find reasonable agreement between the observed profiles and theoretical precipitation spectra. We discuss the possibility that the spectra classed as precipitation signatures are in fact the result of a projection effect, and we indicate limitations of the one-dimensional theoretical models.
Extreme Lake-Effect Snow from a GPM Microwave Imager Perspective: Observational Analysis and Precipitation Retrieval Evaluation
This study focuses on the ability of the Global Precipitation Measurement (GPM) passive microwave sensors to detect and provide quantitative precipitation estimates (QPE) for extreme lake-effect snowfall events over the United States lower Great Lakes region. GPM Microwave Imager (GMI) high frequency channels can clearly detect intense shallow convective snowfall events. However, GMI Goddard PROfiling (GPROF) QPE retrievals produce inconsistent results when compared against the Multi-Radar/Multi-Sensor (MRMS) ground-based radar reference dataset. While GPROF retrievals adequately capture intense snowfall rates and spatial patterns of one event, GPROF systematically underestimates intense snowfall rates in another event. Furthermore, GPROF produces abundant light snowfall rates that do not conform with MRMS observations. Ad-hoc precipitation rate thresholds are suggested to partially mitigate GPROF’s overproduction of light snowfall rates. The sensitivity and retrieval efficiency of GPROF to key parameters (2-meter temperature, total precipitable water, and background surface type) used to constrain the GPROF a-priori retrieval database are investigated. Results demonstrate that typical lake-effect snow environmental and surface conditions, especially coastal surfaces, are underpopulated in the database and adversely affect GPROF retrievals. For the two presented case studies, using snow cover a-priori database in the locations of originally deemed as coastline improves retrieval. This study suggests that it is particularly important to have more accurate GPROF surface classifications and better representativeness of the a-priori databases to improve intense lake-effect snow detection and retrieval performance.
Precipitation over the U.S. Coastal Land/Water Using Gauge-Corrected Multi-Radar/Multi-Sensor System and Three Satellite Products
The weather and climate over the coastal regions have received increasing attention because of substantial population growth, the rising sea level, and extreme weather. Satellite remote sensing provides global precipitation estimates (including coastal land/ocean). While these datasets have been extensively evaluated over land, they have rarely been assessed over coastal ocean. As precipitation radars cover both coastal land and ocean, we used the Multi-Radar/Multi-Sensor System (MRMS) gauge-corrected precipitation product from 2018 to 2020 to evaluate three widely used satellite-based precipitation products over the U.S. coastal land versus the ocean (and the water over the Great Lakes). These products included the Integrated Multi-satellite Retrievals for GPM (IMERG), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), and Climate Prediction Center Morphing technique (CMORPH). The MRMS data showed a precipitation climatology difference between the coastal land and the ocean that was higher in the winter and lower in the summer and autumn. IMERG and CMORPH performed best over land and water, respectively, while PERSIANN was the most consistent in its performance over land versus water. Heavy precipitation was overestimated by the three products, with larger overestimates over water than over land. These results were not affected by the MRMS uncertainties due to the gauge correction or by the use of different versions.