The Effects of Climate Change on Seasonal Snowpack and the Hydrology of the Northeastern and Upper Midwest United States

Permission to use figures, tables, and brief excerpts from this work in scientific and educational works is hereby granted provided that the source is acknowledged. Any use of material in this work that is determined to be “fair use” under Section 107 of the U.S. Copyright Act or that satisfies the conditions specified in Section 108 of the U.S. Copyright Act (17 USC §108) does not require the AMS’s permission. Republication, systematic reproduction, posting in electronic form, such as on a website or in a searchable database, or other uses of this material, except as exempted by the above statement, requires written permission or a license from the AMS. All AMS journals and monograph publications are registered with the Copyright Clearance Center (http://www.copyright.com). Questions about permission to use materials for which AMS holds the copyright can also be directed to the AMS Permissions Officer at [email protected]. Additional details are provided in the AMS Copyright Policy statement, available on the AMS website (http://www.ametsoc.org/CopyrightInformation).The potential effects of climate change on the snowpack of the northeastern and upper Midwest United States are assessed using statistically downscaled climate projections from an ensemble of 10 climate models and a macroscale hydrological model. Climate simulations for the region indicate warmer-than-normal temperatures and wetter conditions for the snow season (November–April) during the twenty-first century. However, despite projected increases in seasonal precipitation, statistically significant negative trends in snow water equivalent (SWE) are found for the region. Snow cover is likely to migrate northward in the future as a result of warmer-than-present air temperatures, with higher loss rates in northern latitudes and at high elevation. Decreases in future (2041–95) snow cover in early spring will likely affect the timing of maximum spring peak streamflow, with earlier peaks predicted in more than 80% of the 124 basins studied

Desarrollo de un sistema de monitoreo y alerta hidrometeorológico en la Región Pampeana

En la actualidad es necesario realizar simulaciones hidrológicas que permitan analizar el comportamiento del sistema durante periodos de excesos hídricos. En las últimas dos décadas la Región Pampeana ha experimentado una relevante expansión e intensificación de áreas cultivadas (Barral y Maceira, 2012) donde pasturas nativas han sido reemplazadas por cultivos agrícolas (Modernel et al., 2016). Este cambio en el uso del suelo, sumada la variabilidad climática en la región, ha incrementado las zonas anegables en un sistema hidrológico que se caracteriza por su baja capacidad hidráulica donde el agua precipitada antes de infiltrarse se traslada en forma mantiforme cubriendo grandes extensiones de terreno, movilizada por la suave pendiente local (Fuschini Mejía, 1994).A pesar de la importancia económica de la Región Pampeana, todavía no se cuentan con herramientas hidrológicas que permitan analizar los periodos de excesos hídricos que afectan la producción agrícola-ganadera, impactado en la biodiversidad del sistema, y generando grandes pérdidas económicas y de vidas (Modernel et al., 2016). En este trabajo se plantea una metodología que tiene como fin desarrollar aplicaciones científicas usando sensoramiento remoto que permitan el monitoreo y pronóstico de condiciones hidrológicas de excesos hídricos

Intensification of the North American Monsoon Rainfall as Observed From a Long‐Term High‐Density Gauge Network

As the atmosphere gets warmer, rainfall intensification is expected across the planet with anticipated impacts on ecological and human systems. In the southwestern United States and northwestern Mexico, the highly variable and localized nature of rainfall during the North American Monsoon makes it difficult to detect temporal changes in rainfall intensities in response to climatic change. This study addresses this challenge by using the dense, subdaily, and daily observations from 59 rain gauges located in southeastern Arizona. We find an intensification of monsoon subdaily rainfall intensities starting in the mid-1970s that has not been observed in previous studies or simulated with high-resolution climate models. Our results highlight the need for long-term, high spatiotemporal observations to detect environmental responses to a changing climate in highly variable environments and show that analyses based on limited observations or gridded data sets fail to capture temporal changes potentially leading to erroneous conclusions.Public domain articleThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Validation and correction of satellite-estimated precipitation using ground observations in the Pampean region of Argentina

Las estimaciones de precipitación basadas en satélites representan una valiosa fuente de información alternativa para diferentes aplicaciones hidrológicas, por lo que entender la habilidad de los productos satelitales para capturar la variabilidad espacial y temporal de la precipitación es crucial para el desarrollo de sistemas de monitoreo y alerta hidrometeorológica. En este trabajo se evalúa la confiabilidad de tres productos de precipitación satelital (PPS) en la región pampeana argentina, antes y después de aplicarles el método de corrección de sesgo Quantile Mapping. Los PPS usados son TMPA, CMORPH e IMERG, todos en sus versiones en tiempo casi real. La evaluación se realizó mediante estadísticos categóricos y descriptivos a fin de conocer su capacidad en proporcionar estimaciones confiables y detectar correctamente la magnitud de los eventos. El análisis de los estadísticos categóricos se realizó a nivel diario; en este caso, los PPS estiman mejor las observaciones para intensidades bajas (menores a 5 mm) y medias (entre 5 y 20 mm) que para intensidades altas (mayores a 20 mm). La evaluación de estadísticos descriptivos a nivel mensual mostró que el CMORPH tiene mayor capacidad de detección en los trimestres EFM y AMJ, mientras que el IMERG obtuvo los menores errores para los trimestres JAS y OND. La incorporación de un método de remoción del sesgo en el proceso de validación de los PPS introdujo mejoras significativas en los estadísticos evaluados. Especialmente el CMORPH superó su rendimiento al compararlo con el IMERG, siendo el TMPA el que mayores errores presenta en la región.Satellite-estimated precipitation represent an alternative source of information for different hydrological applications, hence understanding the skill of satellite products to capture the spatial and temporal variability of precipitation is crucial for the development of hydrometeorological monitoring and early warning systems. This study evaluates the reliability of three satellite precipitation products (SPP) in the Pampean region of Argentina, before and after applying the Quantile Mapping bias correction method. The SPP used are TMPA, CMORPH and IMERG in their near real time versions. The evaluation was carried out using categorical and descriptive statistics in order to assess their skills to provide reliable estimates and correctly detect the magnitude of precipitation events. The categorical statistical analysis was carried out at a daily time step, in this case SPPs better estimate the observations for low intensities (less than 5 mm) and medium (between 5 and 20 mm) than for high intensities (greater than 20 mm). The evaluation of the descriptive statistics at the monthly level showed that the CMORPH has the highest detection skill in the EFM and AMJ quarters, while the IMERG obtained the lowest errors for the JAS and OND quarters. The incorporation of a bias removal method in the SPP validation process introduced significant improvements in the evaluated statistics. Especially the CMORPH which significantly improved its performance when compared with the IMERG, being the TMPA the one showing the larger errors in the region.Fil: Blanco Perez, Martin Alejandro. Comisión de Investigaciones Científicas de la Provincia de Buenos Aires. Instituto de Hidrología de Llanuras "Dr. Eduardo Jorge Usunoff". - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto de Hidrología de Llanuras "Dr. Eduardo Jorge Usunoff". - Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto de Hidrología de Llanuras "Dr. Eduardo Jorge Usunoff"; Argentina. Universidad Nacional de Rosario. Facultad de Ciencias Exactas, Ingeniería y Agrimensura; ArgentinaFil: Demaria, Eleonora. No especifíca;Fil: Cazenave, Georgina. Comisión de Investigaciones Científicas de la Provincia de Buenos Aires. Instituto de Hidrología de Llanuras "Dr. Eduardo Jorge Usunoff". - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto de Hidrología de Llanuras "Dr. Eduardo Jorge Usunoff". - Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto de Hidrología de Llanuras "Dr. Eduardo Jorge Usunoff"; ArgentinaFil: Zimmermann, Erik Daniel. Universidad Nacional de Rosario. Facultad de Ciencias Exactas, Ingeniería y Agrimensura; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

Evaluación de Modelos Climáticos Regionales para representar la precipitación en la provincia de Buenos Aires

El análisis del impacto del cambio climático en los ecosistemas acuáticos pampeanos requiere contar con modelos climáticos regionales (RCMs) que representen las características de la precipitación observada. El objetivo de este estudio es evaluar el desempeño de seis RCMs del Proyecto de Intercomparación de Modelos Acoplados Fase 5 para representar la distribución espacio-temporal de la precipitación en la provincia de Buenos aires. Para evaluar el desempeño de los distintos RCMs se comparó la intensidad de la precipitación y la probabilidad de día húmedo en quince estaciones meteorológicas por un periodo de 35 años (1970-2005). Se encontró que los RCMs CCSM4 y MRIC6CM3 obtuvieron mejores rendimientos para simular la precipitación observada. Se sugiere el uso de estos RCMs debido a que presentan menor incertidumbre para la evaluación futura del cambio climático en la región pampeana.Facultad de Ingenierí

Molecular mechanisms of cell death: recommendations of the Nomenclature Committee on Cell Death 2018.

Over the past decade, the Nomenclature Committee on Cell Death (NCCD) has formulated guidelines for the definition and interpretation of cell death from morphological, biochemical, and functional perspectives. Since the field continues to expand and novel mechanisms that orchestrate multiple cell death pathways are unveiled, we propose an updated classification of cell death subroutines focusing on mechanistic and essential (as opposed to correlative and dispensable) aspects of the process. As we provide molecularly oriented definitions of terms including intrinsic apoptosis, extrinsic apoptosis, mitochondrial permeability transition (MPT)-driven necrosis, necroptosis, ferroptosis, pyroptosis, parthanatos, entotic cell death, NETotic cell death, lysosome-dependent cell death, autophagy-dependent cell death, immunogenic cell death, cellular senescence, and mitotic catastrophe, we discuss the utility of neologisms that refer to highly specialized instances of these processes. The mission of the NCCD is to provide a widely accepted nomenclature on cell death in support of the continued development of the field

EVALUATING THE IMPACTS OF INPUT AND PARAMETER UNCERTAINTY ON STREAMFLOW SIMULATIONS IN LARGE UNDER-INSTRUMENTED BASINS

In data-poor regions around the world, particularly in less-privileged countries, hydrologists cannot always take advantage of available hydrological models to simulate a hydrological system due to the lack of reliable measurements of hydrological variables, in particular rainfall and streamflows, needed to implement and evaluate these models. Rainfall estimates obtained with remotely deployed sensors constitute an excellent source of precipitation for these basins, however they are prone to errors that can potentially affect hydrologic simulations. Concurrently, limited access to streamflow measurements does not allow a detailed representation of the system's structure through parameter estimation techniques. This dissertation presents multiple studies that evaluate the usefulness of remotely sensed products for different hydrological applications and the sensitivity of simulated streamflow to parameter uncertainty across basins with different hydroclimatic characteristics with the ultimate goal of increasing the applicability of land surface models in ungauged basins, particularly in South America. Paper 1 presents a sensitivity analysis of daily simulated streamflows to changes in model parameters along a hydroclimatic gradient. Parameters controlling the generation of surface and subsurface flow were targeted for the study. Results indicate that the sensitivity is strongly controlled by climate and that a more parsimonious version of the model could be implemented. Paper 2 explores how errors in satellite-estimated precipitation, due to infrequent satellite measurements, propagate through the simulation of a basin's hydrological cycle and impact the characteristics of peak streamflows within the basin. Findings indicate that nonlinearities in the hydrological cycle can introduce bias in simulated streamflows with error-corrupted precipitation. They also show that some characteristics of peak discharges are not conditioned by errors in satellite-estimated precipitation at a daily time step. Paper 3 evaluates the dominant sources of error in three satellite products when representing convective storms and how shifts in the location of the storm affect simulated peak streamflows in the basin. Results indicate that satellite products show some deficiencies retrieving convective processes and that a ground bias correction can mitigate these deficiencies but without sacrificing the potential for real-time hydrological applications. Finally, spatially shifted precipitation fields affect the magnitude of the peaks, however, its impact on the timing of the peaks is dampened out by the system's response at a daily time scale.Release after 2/16/201

Evaluating the impacts of input and parameter uncertainty on streamflow simulations in large under-instrumented basins

In data-poor regions around the world, particularly in less-privileged countries, hydrologists cannot always take advantage of available hydrological models to simulate a hydrological system due to the lack of reliable measurements of hydrological variables, in particular rainfall and streamflows, needed to implement and evaluate these models. Rainfall estimates obtained with remotely deployed sensors constitute an excellent source of precipitation for these basins, however they are prone to errors that can potentially affect hydrologic simulations. Concurrently, limited access to streamflow measurements does not allow a detailed representation of the system’s structure through parameter estimation techniques. This dissertation presents multiple studies that evaluate the usefulness of remotely sensed products for different hydrological applications and the sensitivity of simulated streamflow to parameter uncertainty across basins with different hydroclimatic characteristics with the ultimate goal of increasing the applicability of land surface models in ungauged basins, particularly in South America. Paper 1 presents a sensitivity analysis of daily simulated streamflows to changes in model parameters along a hydroclimatic gradient. Parameters controlling the generation of surface and subsurface flow were targeted for the study. Results indicate that the sensitivity is strongly controlled by climate and that a more parsimonious version of the model could be implemented. Paper 2 explores how errors in satellite-estimated precipitation, due to infrequent satellite measurements, propagate through the simulation of a basin's hydrological cycle and impact the characteristics of peak streamflows within the basin. Findings indicate that nonlinearities in the hydrological cycle can introduce bias in simulated streamflows with error-corrupted precipitation. They also show that some characteristics of peak discharges are not conditioned by errors in satellite-estimated precipitation at a daily time step. Paper 3 evaluates the dominant sources of error in three satellite products when representing convective storms and how shifts in the location of the storm affect simulated peak streamflows in the basin. Results indicate that satellite products show some deficiencies retrieving convective processes and that a ground bias correction can mitigate these deficiencies but without sacrificing the potential for real-time hydrological applications. Finally, spatially shifted precipitation fields affect the magnitude of the peaks, however, its impact on the timing of the peaks is dampened out by the system's response at a daily time scale

Regional climate change projections of streamflow characteristics in the Northeast and Midwest U.S.

Study region: Northeast and Midwest, United States. Study focus: Assessing the climate change impacts on the basin scale is important for water and natural resource managers. Here, the presence of monotonic trends and changes in climate-driven simulated 3-day peak flows, 7-day low flows, and mean base flows are evaluated in the Northeast and Midwest U.S. during the 20th and the 21st centuries using climate projections from sixteen climate models. Proven statistical methods are used to spatially and temporally disaggregate precipitation and temperature fields to a finer resolution before being used as drivers for a hydrological model. New hydrological insights for the region: Changes in the annual cycle of precipitation are likely to occur during the 21st century as winter precipitation increases and warmer temperatures reduce snow coverage across the entire domain especially in the northern basins. Maximum precipitation intensities are projected to become more intense across the region by mid-century especially along the coast. Positive trends in 3-day peak flows are also projected in the region as a result of the more intense precipitation, whereas the magnitude of 7-day low flows and mean base flows are projected to decrease. The length of the low flows season will likely extend by mid-century despite the increased precipitation as the atmospheric demand increases. Keywords: Streamflow peaks, Low flows, Trend analysis, Intense precipitation, Base flow