Download or read book Large scale Snowpack Estimation Using Ensemble Data Assimilation Methodologies Satellite Observations and Synthetic Datasets written by Hua Su (Ph. D.) and published by . This book was released on 2009 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work focuses on a series of studies that contribute to the development and test of advanced large-scale snow data assimilation methodologies. Compared to the existing snow data assimilation methods and strategies, which are limited in the domain size and landscape coverage, the number of satellite sensors, and the accuracy and reliability of the product, the present work covers the continental domain, compares single- and multi-sensor data assimilations, and explores uncertainties in parameter and model structure. In the first study a continental-scale snow water equivalent (SWE) data assimilation experiment is presented, which incorporates Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover fraction (SCF) data to Community Land Model (CLM) estimates via the ensemble Kalman filter (EnKF). The greatest improvements of the EnKF approach are centered in the mountainous West, the northern Great Plains, and the west and east coast regions, with the magnitude of corrections (compared to the use of model only) greater than one standard deviation (calculated from SWE climatology) at given areas. Relatively poor performance of the EnKF, however, is found in the boreal forest region. In the second study, snowpack related parameter and model structure errors were explicitly considered through a group of synthetic EnKF simulations which integrate synthetic datasets with model estimates. The inclusion of a new parameter estimation scheme augments the EnKF performance, for example, increasing the Nash-Sutcliffe efficiency of season-long SWE estimates from 0.22 (without parameter estimation) to 0.96. In this study, the model structure error is found to significantly impact the robustness of parameter estimation. In the third study, a multi-sensor snow data assimilation system over North America was developed and evaluated. It integrates both Gravity Recovery and Climate Experiment (GRACE) Terrestrial water storage (TWS) and MODIS SCF information into CLM using the ensemble Kalman filter (EnKF) and smoother (EnKS). This GRACE/MODIS data assimilation run achieves a significantly better performance over the MODIS only run in Saint Lawrence, Fraser, Mackenzie, Churchill & Nelson, and Yukon river basins. These improvements demonstrate the value of integrating complementary information for continental-scale snow estimation.
Download or read book Feasibility of Snowpack Characterization Using Remote Sensing and Advanced Data Assimilation Techniques written by Steven A. Margulis and published by . This book was released on 2006 with total page 46 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Thriving on Our Changing Planet written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2019-01-20 with total page 717 pages. Available in PDF, EPUB and Kindle. Book excerpt: We live on a dynamic Earth shaped by both natural processes and the impacts of humans on their environment. It is in our collective interest to observe and understand our planet, and to predict future behavior to the extent possible, in order to effectively manage resources, successfully respond to threats from natural and human-induced environmental change, and capitalize on the opportunities â€" social, economic, security, and more â€" that such knowledge can bring. By continuously monitoring and exploring Earth, developing a deep understanding of its evolving behavior, and characterizing the processes that shape and reshape the environment in which we live, we not only advance knowledge and basic discovery about our planet, but we further develop the foundation upon which benefits to society are built. Thriving on Our Changing Planet presents prioritized science, applications, and observations, along with related strategic and programmatic guidance, to support the U.S. civil space Earth observation program over the coming decade.
Download or read book Land Surface Remote Sensing in Continental Hydrology written by Nicolas Baghdadi and published by Elsevier. This book was released on 2016-09-19 with total page 504 pages. Available in PDF, EPUB and Kindle. Book excerpt: The continental hydrological cycle is one of the least understood components of the climate system. The understanding of the different processes involved is important in the fields of hydrology and meteorology.In this volume the main applications for continental hydrology are presented, including the characterization of the states of continental surfaces (water state, snow cover, etc.) using active and passive remote sensing, monitoring the Antarctic ice sheet and land water surface heights using radar altimetry, the characterization of redistributions of water masses using the GRACE mission, the potential of GNSS-R technology in hydrology, and remote sensing data assimilation in hydrological models.This book, part of a set of six volumes, has been produced by scientists who are internationally renowned in their fields. It is addressed to students (engineers, Masters, PhD) , engineers and scientists, specialists in remote sensing applied to hydrology. Through this pedagogical work, the authors contribute to breaking down the barriers that hinder the use of Earth observation data. Provides clear and concise descriptions of modern remote sensing methods Explores the most current remote sensing techniques with physical aspects of the measurement (theory) and their applications Provides chapters on physical principles, measurement, and data processing for each technique described Describes optical remote sensing technology, including a description of acquisition systems and measurement corrections to be made
Download or read book Data Assimilation written by Geir Evensen and published by Springer Science & Business Media. This book was released on 2006-12-22 with total page 285 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reviews popular data-assimilation methods, such as weak and strong constraint variational methods, ensemble filters and smoothers. The author shows how different methods can be derived from a common theoretical basis, as well as how they differ or are related to each other, and which properties characterize them, using several examples. Readers will appreciate the included introductory material and detailed derivations in the text, and a supplemental web site.
Download or read book Multivariate Land Snow Data Assimilation in the Northern Hemisphere written by Yongfei Zhang and published by . This book was released on 2015 with total page 116 pages. Available in PDF, EPUB and Kindle. Book excerpt: The past few decades have seen decreasing trends of snow-covered regions in the Northern Hemisphere. It remains unknown how these trends affect the spatial and temporal variability of snowpack water storage, a variable with significant implications for managing water resources to meet agricultural, municipal, and hydropower demands. To improve snowpack estimates, this dissertation developed a new snow data assimilation system (SNODAS) through multi-institutional collaborations. The new SNODAS consists of coupling of the Community Land Model version 4 (CLM4) and the Data Assimilation Research Testbed (DART), which is capable of assimilating multi-sensor satellite observations including the Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover fraction (SCF) and the Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage (TWS) anomalies. This dissertation describes the new SNODAS, presents the results of the data assimilation of MODIS SCF and GRACE TWS observations, and assesses the influence of uncertainties from multiple sources on the SNODAS performance. The first two studies compared the open loop run and the assimilation runs to evaluate the data assimilation (DA) performance. Data assimilation results were also evaluated against other independent observation-based snow data on daily and monthly timescales. Both assimilations can improve the snowpack simulations in CLM4; their strengths and drawbacks were discussed. When only MODIS SCF is assimilated, the innovation (i.e. the difference between analysis and forecast) is marginal in the regions where the snow cover extent reaches 100% regardless of snow mass changes. Further assimilation of GRACE TWS anomalies, however, can adjust the modeled snowpack, resulting in noteworthy improvements over the MODIS-only run in high-latitude regions. The effectiveness of the assimilation was analyzed over several Arctic river basins and various land covers. The third study discussed the influences of atmospheric forcing, model structure, DA technique, and satellite remote sensing product within the framework of SNODAS. The atmospheric forcing uncertainty is found to be the largest among the various uncertainty sources examined, especially over the Tibetan Plateau and most of the mid- and high-latitudes. The uncertainty of model structure as represented by two different parameterizations of SCF is the second largest. DA methods and products of GRACE TWS data have relatively less impacts. This study also showed that CLM4.5 produces better TWS anomalies than CLM4, which would have implications for improving the performance of GRACE TWS data assimilation.
Download or read book Data Assimilation for Atmospheric Oceanic and Hydrologic Applications Vol II written by Seon Ki Park and published by Springer Science & Business Media. This book was released on 2013-05-22 with total page 736 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains the most recent progress in data assimilation in meteorology, oceanography and hydrology including land surface. It spans both theoretical and applicative aspects with various methodologies such as variational, Kalman filter, ensemble, Monte Carlo and artificial intelligence methods. Besides data assimilation, other important topics are also covered including targeting observation, sensitivity analysis, and parameter estimation. The book will be useful to individual researchers as well as graduate students for a reference in the field of data assimilation.
Download or read book Towards Large scale Implementation of a High Resolution Snow Reanalysis Over Midlatitude Montane Ranges written by Elisabeth Baldo and published by . This book was released on 2017 with total page 137 pages. Available in PDF, EPUB and Kindle. Book excerpt: Accurately representing the spatial variability of montane snowpack is challenging due to the high degree of complexity in the terrain's topography, and the lack of good quality in-situ data. To explicitly resolve snow processes in montane environment while taking into account the uncertainties in the system's high spatial and temporal resolution snow reanalyses are required. Ensemble-based approaches assimilating Landsat VIS-NIR remote sensing data at spatial resolutions of 100 m or less are, however, prohibitively expensive to run at large scales, and sub-optimal given that only the most complex parts of a montane range require such fine resolution. In addition, the assimilation of remote sensing data from a single source can also be unsatisfactory due to a lack of global coverage, hardware malfunction etc. In order to optimize computational needs while preserving the accuracy of ~ 100 m reanalyses, a raster-based multi-resolution approach was first developed and successfully implemented for a headwater catchment in the Colorado River Basin over the full length of Landsat record (30+ years). The potential use of MODIS-derived snow cover information in addition to Landsat in snow reanalyses was then investigated over three different regions in the Western U.S. and High Mountain Asia in order to make up for Landsat's shortcomings over midlatitude snowpacks. The key findings of this dissertation can be summarized as follows: 1) The physiographic complexity of a terrain can be characterized by its standard deviations of elevation, northness index and forested fraction. Using such a complexity metric to discretize the terrain into different spatial resolutions via a multi-resolution approach can significantly reduce computational needs, while mitigating errors in snow processes representation. 2) The multi-resolution approach did not significantly impact the remote sensing observations assimilated, and the posterior snow water equivalent (SWE) ensemble median and standard deviation matched the 90 m reanalysis, thus leading to a robust implementation in the context of a data assimilation framework. 3) A MODIS-derived snow cover product was found to be a useful complementary source of remote sensing data to be simultaneously assimilated with Landsat. Off-nadir-looking observations first had to be screened out of the reanalysis due to the distorting and snow obscuring effects of the sensor viewing geometry at high zenith angles. Ultimately, the methods developed in this work can be applied to all midlatitude montane ranges over the full lengths of Landsat and MODIS records to generate a fine spatial resolution SWE reanalysis dataset that will be useful to snow hydrologists to solve many unanswered science questions over such challenging regions.
Download or read book Stochastic Processes and Filtering Theory written by Andrew H. Jazwinski and published by Courier Corporation. This book was released on 2013-04-15 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: This unified treatment of linear and nonlinear filtering theory presents material previously available only in journals, and in terms accessible to engineering students. Its sole prerequisites are advanced calculus, the theory of ordinary differential equations, and matrix analysis. Although theory is emphasized, the text discusses numerous practical applications as well. Taking the state-space approach to filtering, this text models dynamical systems by finite-dimensional Markov processes, outputs of stochastic difference, and differential equations. Starting with background material on probability theory and stochastic processes, the author introduces and defines the problems of filtering, prediction, and smoothing. He presents the mathematical solutions to nonlinear filtering problems, and he specializes the nonlinear theory to linear problems. The final chapters deal with applications, addressing the development of approximate nonlinear filters, and presenting a critical analysis of their performance.
Download or read book Attribution of Extreme Weather Events in the Context of Climate Change written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2016-07-28 with total page 187 pages. Available in PDF, EPUB and Kindle. Book excerpt: As climate has warmed over recent years, a new pattern of more frequent and more intense weather events has unfolded across the globe. Climate models simulate such changes in extreme events, and some of the reasons for the changes are well understood. Warming increases the likelihood of extremely hot days and nights, favors increased atmospheric moisture that may result in more frequent heavy rainfall and snowfall, and leads to evaporation that can exacerbate droughts. Even with evidence of these broad trends, scientists cautioned in the past that individual weather events couldn't be attributed to climate change. Now, with advances in understanding the climate science behind extreme events and the science of extreme event attribution, such blanket statements may not be accurate. The relatively young science of extreme event attribution seeks to tease out the influence of human-cause climate change from other factors, such as natural sources of variability like El Niño, as contributors to individual extreme events. Event attribution can answer questions about how much climate change influenced the probability or intensity of a specific type of weather event. As event attribution capabilities improve, they could help inform choices about assessing and managing risk, and in guiding climate adaptation strategies. This report examines the current state of science of extreme weather attribution, and identifies ways to move the science forward to improve attribution capabilities.
Download or read book The GOES R Series written by Steven J. Goodman and published by Elsevier. This book was released on 2019-10-05 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: The GOES-R Series: A New Generation of Geostationary Environmental Satellites introduces the reader to the most significant advance in weather technology in a generation. The world’s new constellation of geostationary operational environmental satellites (GOES) are in the midst of a drastic revolution with their greatly improved capabilities that provide orders of magnitude improvements in spatial, temporal and spectral resolution. Never before have routine observations been possible over such a wide area. Imagine satellite images over the full disk every 10 or 15 minutes and monitoring of severe storms, cyclones, fires and volcanic eruptions on the scale of minutes. Introduces the GOES-R Series, with chapters on each of its new products Provides an overview of how to read new satellite images Includes full-color images and online animations that demonstrate the power of this new technology
Download or read book Remote Sensing of Drought written by Brian D. Wardlow and published by CRC Press. This book was released on 2012-04-24 with total page 487 pages. Available in PDF, EPUB and Kindle. Book excerpt: Remote Sensing of Drought: Innovative Monitoring Approaches presents emerging remote sensing-based tools and techniques that can be applied to operational drought monitoring and early warning around the world. The first book to focus on remote sensing and drought monitoring, it brings together a wealth of information that has been scattered throughout the literature and across many disciplines. Featuring contributions by leading scientists, it assembles a cross-section of globally applicable techniques that are currently operational or have potential to be operational in the near future. The book explores a range of applications for monitoring four critical components of the hydrological cycle related to drought: vegetation health, evapotranspiration, soil moisture and groundwater, and precipitation. These applications use remotely sensed optical, thermal, microwave, radar, and gravity data from instruments such as AMSR-E, GOES, GRACE, MERIS, MODIS, and Landsat and implement several advanced modeling and data assimilation techniques. Examples show how to integrate this information into routine drought products. The book also examines the role of satellite remote sensing within traditional drought monitoring, as well as current challenges and future prospects. Improving drought monitoring is becoming increasingly important in addressing a wide range of societal issues, from food security and water scarcity to human health, ecosystem services, and energy production. This unique book surveys innovative remote sensing approaches to provide you with new perspectives on large-area drought monitoring and early warning.
Download or read book Development and Evaluation of an Advanced Microwave Radiance Data Assimilation System for Estimating Snow Water Storage at the Continental Scale written by Yonghwan Kwon and published by . This book was released on 2016 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: Snow cover modulates the Earth’s surface energy and water fluxes, and snowmelt runoff is the principal source of water for humans and ecosystems in many of the middle to high latitudes in the Northern Hemisphere. Understanding spatial and temporal variation in snowpack is crucial for climate studies and water resource management and thus the climate and hydrological research communities have invested in improving large-scale snow estimates. This dissertation aims to develop an advanced snow radiance assimilation (RA) system to improve continental-scale snow water storage estimates. The RA system is comprised of the Community Land Model version 4 (CLM4) (for snow energy and mass balance modeling), radiative transfer models (RTMs) (for brightness temperature estimates), and the Data Assimilation Research Testbed (DART) (for ensemble-based data assimilation). Two snowpack RTMs, the Microwave Emission Model for Layered Snowpacks (MEMLS) and the Dense Media Radiative Transfer–Multi Layers model (DMRT-ML), are used to simulate T[subscript B] of a multi-layered snowpack. Through an error characterization study, this dissertation presents that the correlations between snow water equivalent (SWE) error and brightness temperature (T[subscript B]) error and subsequent RA performance in estimating snow are significantly affected by all physical properties of soil and snow involved in estimating T[subscript B]. Based on the error characterization results, it is hypothesized that the continental-scale RA performance in estimating snow water storage can be improved by simultaneously updating all model physical states and parameters determining T[subscript B] based on a rule, in which prior estimates are updated depending on their correlations with a prior T[subscript B]. The results of a series of RA experiments show that the improved continental-scale snow estimates are obtained by applying the hypothesis. This dissertation also shows that further improvement of the performance of the RA system can be achieved, especially for vegetated areas, by assimilating the best-performing frequency channels (i.e., 18.7 and 23.8 GHz) and by considering the vegetation single scattering albedo to represent the vegetation effect on T[subscript B] at the top of the atmosphere.
Download or read book Next Generation Earth System Prediction written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2016-08-22 with total page 351 pages. Available in PDF, EPUB and Kindle. Book excerpt: As the nation's economic activities, security concerns, and stewardship of natural resources become increasingly complex and globally interrelated, they become ever more sensitive to adverse impacts from weather, climate, and other natural phenomena. For several decades, forecasts with lead times of a few days for weather and other environmental phenomena have yielded valuable information to improve decision-making across all sectors of society. Developing the capability to forecast environmental conditions and disruptive events several weeks and months in advance could dramatically increase the value and benefit of environmental predictions, saving lives, protecting property, increasing economic vitality, protecting the environment, and informing policy choices. Over the past decade, the ability to forecast weather and climate conditions on subseasonal to seasonal (S2S) timescales, i.e., two to fifty-two weeks in advance, has improved substantially. Although significant progress has been made, much work remains to make S2S predictions skillful enough, as well as optimally tailored and communicated, to enable widespread use. Next Generation Earth System Predictions presents a ten-year U.S. research agenda that increases the nation's S2S research and modeling capability, advances S2S forecasting, and aids in decision making at medium and extended lead times.
Download or read book Calibration of Watershed Models written by Qingyun Duan and published by John Wiley & Sons. This book was released on 2003-01-10 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: Published by the American Geophysical Union as part of the Water Science and Application Series, Volume 6. During the past four decades, computer-based mathematical models of watershed hydrology have been widely used for a variety of applications including hydrologic forecasting, hydrologic design, and water resources management. These models are based on general mathematical descriptions of the watershed processes that transform natural forcing (e.g., rainfall over the landscape) into response (e.g., runoff in the rivers). The user of a watershed hydrology model must specify the model parameters before the model is able to properly simulate the watershed behavior.
Download or read book Estimating Snow Water Resources from Space written by Dongyue Li and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Improving the estimation of snow water equivalent (SWE) in the Sierra Nevada is critical for the water resources management in California. In this study, we carried out an experiment to estimate SWE in the Upper Kern Basin, Sierra Nevada, by assimilating AMSR-E observed brightness temperatures (Tb) into a coupled hydrology and radiative transfer model using an ensemble Kalman batch reanalysis. The data assimilation framework merges the complementary SWE information from modeling and observations to improve SWE estimates. The novelty of this assimilation study is that both the modeling and the radiance data processing were specifically improved to provide more information about SWE. With the enhanced SWE signals in both simulations and observations, the batch reanalysis stands a better chance of successfully improving the SWE estimates. The modeling was at a very high resolution (90m) and spanned a range of mountain environmental factors to better characterize the effects of the mountain environment on snow distribution and radiance emission. We have developed a dynamic snow grain size module to improve the radiance modeling during the intense snowfall events. The AMSR-E 37GHz V-pol observed Tb was processed at its native footprint resolution at ~100 square km. In the batch assimilation, the model predicted the prior SWE and Tb; the prior estimate of an entire year was then updated by the dry-season observations at one time. One advantage of this is that the prior SWE of a certain period is updated using the observations both before and after this period, which takes advantage of the temporally continuous signal of the seasonal snow accumulation in the observations. We found the posterior SWE estimates showed improved accuracy and robustness. During the study period of 2003 to 2008, at point-scale, the average bias of the six-year April 1st SWE was reduced from -0.17 m to -0.02m, the average temporal SWE RMSE of the snow accumulation season decreased by 51.2%. The basin-scale results showed that the April 1st SWE bias reduced from -0.17m to -0.11m, and the temporal SWE RMSE of the accumulation season decreased by 23.6%.
Download or read book Hydrometeorology written by Kevin Sene and published by Springer Science & Business Media. This book was released on 2009-12-12 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes recent developments in hydrometeorological forecasting techniques for a range of timescales, from short term to seasonal and longer terms. It conveniently brings together both meteorological and hydrological aspects in a single volume.
