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"Dynamic meteorology."
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Understanding the earth system : global change science for application
\"Explaining the what, the how and the why of climate science, this multidisciplinary new book provides a review of research from the last decade, illustrated with cutting-edge data and observations. A key focus is the development of analysis tools that can be used to demonstrate options for mitigating and adapting to increasing climate risks. Emphasis is given to the importance of Earth system feedback mechanisms and the role of the biosphere. The book explains advances in modelling, process understanding and observations, and the development of consistent and coherent studies of past, present and 'possible' climates. This highly-illustrated, data-rich book is written by leading scientists involved in QUEST, a major UK-led research programme. It forms a concise and up-to-date reference for academic researchers or students in the fields of climatology, Earth system science and ecology, and also a vital resource for professionals and policymakers working on any aspect of global change\"-- Provided by publisher.
Book
Meteorological aspects associated with dust storms in the Sistan region, southeastern Iran
Dust storms are considered natural hazards that seriously affect atmospheric conditions, ecosystems and human health. A key requirement for investigating the dust life cycle is the analysis of the meteorological (synoptic and dynamic) processes that control dust emission, uplift and transport. The present work focuses on examining the synoptic and dynamic meteorological conditions associated with dust-storms in the Sistan region, southeastern Iran during the summer season (June–September) of the years 2001–2012. The dust-storm days (total number of 356) are related to visibility records below 1 km at Zabol meteorological station, located near to the dust source. RegCM4 model simulations indicate that the intense northern Levar wind, the high surface heating and the valley-like characteristics of the region strongly affect the meteorological dynamics and the formation of a low-level jet that are strongly linked with dust exposures. The intra-annual evolution of the dust storms does not seem to be significantly associated with El-Nino Southern Oscillation, despite the fact that most of the dust-storms are related to positive values of Oceanic Nino Index. National Center for Environmental Prediction/National Center for Atmospheric Research reanalysis suggests that the dust storms are associated with low sea-level pressure conditions over the whole south Asia, while at 700 hPa level a trough of low geopotential heights over India along with a ridge over Arabia and central Iran is the common scenario. A significant finding is that the dust storms over Sistan are found to be associated with a pronounced increase of the anticyclone over the Caspian Sea, enhancing the west-to-east pressure gradient and, therefore, the blowing of Levar. Infrared Difference Dust Index values highlight the intensity of the Sistan dust storms, while the SPRINTARS model simulates the dust loading and concentration reasonably well, since the dust storms are usually associated with peaks in model simulations.
Journal Article
A billion butterflies : a life in climate and chaos theory
\"The amazing true story of the man behind modern weather prediction. Consider a world without weather prediction. How would we know when to evacuate communities ahead of fires or floods, or figure out what to wear tomorrow? Until 40 years ago, we couldn't forecast weather conditions beyond ten days. Renowned climate scientist Dr. Jagadish Shukla is largely to thank for modern weather forecasting. Born in rural India with no electricity, plumbing, or formal schools, he attended classes that were held in a cow shed. Shukla grew up amid turmoil: overwhelming monsoons, devastating droughts, and unpredictable crop yields. His drive brought him to the Indian Institute of Tropical Meteorology, despite little experience. He then followed an unlikely path to MIT and Princeton, and the highest echelons of climate science. His work, which has enabled us to predict weather farther into the future than previously thought possible, allows us to feed more people, save lives, and hold on to hope in a warming world. Paired with his philanthropic endeavors and extreme dedication to the field, Dr. Shukla has been lauded internationally for his achievements, including a shared Nobel Peace Prize with Al Gore for his governmental research on climate change. A Billion Butterflies is a wondrous insider's account of climate science and an unbelievable memoir of his life. Understanding dynamical seasonal prediction will change the way you experience a thunderstorm or interpret a forecast; understanding its origins and the remarkable story of the man who discovered it will change the way you see our world\"-- Provided by publisher.
BOOK
mathematical theory of large-scale atmosphere/ocean flow
This book counteracts the current fashion for theories of \"chaos\" and unpredictability by describing a theory that underpins the surprising accuracy of current deterministic weather forecasts, and it suggests that further improvements are possible. The book does this by making a unique link between an exciting new branch of mathematics called \"optimal transportation\" and existing classical theories of the large-scale atmosphere and ocean circulation. It is then possible to solve a set of simple equations proposed many years ago by Hoskins which are asymptotically valid on large scales, and use them to derive quantitative predictions about many large-scale atmospheric and oceanic phenomena. A particular feature is that the simple equations used have highly predictable solutions, thus suggesting that the limits of deterministic predictability of the weather may not yet have been reached. It is also possible to make rigorous statements about the large-scale behaviour of the atmosphere and ocean by proving results using these simple equations and applying them to the real system allowing for the errors in the approximation. There are a number of other titles in this field, but they do not treat this large-scale regime.
eBook
Observation- and numerical-analysis-based dynamics of the Uttarkashi cloudburst
A Himalayan cloudburst event, which occurred on 3 August 2012 in the Uttarkashi (30.73° N, 78.45° E) region of Uttarakhand, India, was analyzed. The near-surface atmospheric variables were analyzed to study the formation, evolution, and triggering mechanisms of this cloudburst. In order to improve upon the understanding provided by the observations, numerical simulations were performed using the Weather Research and Forecasting (WRF) model, configured with a single domain at 18 km resolution. The model was tuned using variation of different parameterizations (convective, microphysical, boundary layer, radiation, and land surface), and different model options (number of vertical levels, and spin-up time), which resulted in a combination of parameters and options that best reproduced the observed diurnal characteristics of the near-surface atmospheric variables. Our study demonstrates the ability of WRF in forecasting precipitation, and resolving synoptic-scale and mesoscale interactions. In order to better understand the cloudburst, we configured WRF with multiply nested two-way-interacting domains (18, 6, 2 km) centered on the location of interest, and simulated the event with the best configuration derived earlier. The results indicate that two mesoscale convective systems originating from Madhya Pradesh and Tibet interacted over Uttarkashi and, under orographic uplifting and in the presence of favorable moisture condition, resulted in this cloudburst event.
Journal Article
REANALYSES AND OBSERVATIONS
Are there important differences between reanalysis data and familiar observations and measurements? If so, what are they? This essay evaluates four possible answers that relate to: the role of inference, reliance on forecasts, the need to solve an ill-posed inverse problem, and understanding of errors and uncertainties. The last of these is argued to be most significant. The importance of characterizing uncertainties associated with results—whether those results are observations or measurements, analyses or reanalyses, or forecasts—is emphasized.
Journal Article
The relationship between PM.sub.2.5 and anticyclonic wave activity during summer over the United States
To better understand the role of atmospheric dynamics in modulating surface concentrations of fine particulate matter (PM.sub.2.5 ), we relate the anticyclonic wave activity (AWA) metric and PM.sub.2.5 data from the Interagency Monitoring of Protected Visual Environment (IMPROVE) data for the period of 1988-2014 over the US. The observational results are compared with hindcast simulations over the past 2 decades using the National Center for Atmospheric Research-Community Earth System Model (NCAR CESM). We find that PM.sub.2.5 is positively correlated (up to R=0.65) with AWA changes close to the observing sites using regression analysis. The composite AWA for high-aerosol days (all daily PM.sub.2.5 above the 90th percentile) shows a similarly strong correlation between PM.sub.2.5 and AWA. The most prominent correlation occurs in the Midwestern US. Furthermore, the higher quantiles of PM.sub.2.5 levels are more sensitive to the changes in AWA. For example, we find that the averaged sensitivity of the 90th-percentile PM.sub.2.5 to changes in AWA is approximately 3 times as strong as the sensitivity of 10th-percentile PM.sub.2.5 at one site (Arendtsville, Pennsylvania; 39.92.sup.\" N, 77.31.sup.\" W). The higher values of the 90th percentile compared to the 50th percentile in quantile regression slopes are most prominent over the northeastern US. In addition, future changes in US PM.sub.2.5 based only on changes in climate are estimated to increase PM.sub.2.5 concentrations due to increased AWA in summer over areas where PM.sub.2.5 variations are dominated by meteorological changes, especially over the western US. Changes between current and future climates in AWA can explain up to 75 % of PM.sub.2.5 variability using a linear regression model. Our analysis indicates that higher PM.sub.2.5 concentrations occur when a positive AWA anomaly is prominent, which could be critical for understanding how pollutants respond to changing atmospheric circulation as well as for developing robust pollution projections.
Journal Article
Enhanced net CO.sub.2 exchange of a semideciduous forest in the southern Amazon due to diffuse radiation from biomass burning
Carbon cycling in the Amazon fundamentally depends on the functioning of ecosystems and atmospheric dynamics, which are highly intricate. Few studies have hitherto investigated or measured the radiative effects of aerosols on the Amazon and Cerrado. This study examines the effects of atmospheric aerosols on solar radiation and their effects on net ecosystem exchange (NEE) in an area of semideciduous tropical forest in the north of Mato Grosso. Our results show that for a relative irradiance (f) 1.10-0.67, a decrease in incident solar radiation is associated with a reduction in the NEE. However, an average increase of 25 %-110 % in NEE was observed when pollution levels and aerosol optical depth (AOD) were above â 1.25 and f 0.5. The increase NEE was attributed to the increase of up to 60 % in the diffuse fraction of photosynthetically active radiation. The change in AOD and f was mainly attributable to biomass burning organic aerosols from fires. Important influences on vapor pressure deficit (VPD) as well as air temperature (T.sub.air) and canopy (LC.sub.T ), induced by the interaction between solar radiation and high aerosol load in the observation area, were also noticed. On average, a cooling of about 3-4 .sup.\" C was observed for T.sub.air and LC.sub.T, and a decrease of up to 2-3 hPa was observed for VPD. Given the long-distance transport of aerosols emitted by burning biomass, significant changes in atmospheric optical properties and irradiance will impact the CO.sub.2 flux of semideciduous forests distributed in the region.
Journal Article
Testing ground-based observations of wave activity in the indicators of streamer events
For a better understanding of atmospheric dynamics, it is very important to know the general conditions (dynamics and chemistry) of the atmosphere. Planetary waves (PWs) are global-scale waves, which are well-known as main drivers of the large-scale weather patterns in mid-latitudes on timescales from several days up to weeks in the troposphere. When PWs break, they often cut pressure cells off the jet stream. A specific example is so-called streamer events, which occur predominantly in the lower stratosphere at mid-latitudes and high latitudes. For streamer events, we check whether there are any changes in gravity wave (GW) or infrasound characteristics related to these events in ionospheric and surface measurements (continuous Doppler soundings, two arrays of microbarometers) in the Czech Republic.
Journal Article
North American extreme precipitation events and related large-scale meteorological patterns: a review of statistical methods, dynamics, modeling, and trends
This paper surveys the current state of knowledge regarding large-scale meteorological patterns (LSMPs) associated with short-duration (less than 1 week) extreme precipitation events over North America. In contrast to teleconnections, which are typically defined based on the characteristic spatial variations of a meteorological field or on the remote circulation response to a known forcing, LSMPs are defined relative to the occurrence of a specific phenomenon—here, extreme precipitation—and with an emphasis on the synoptic scales that have a primary influence in individual events, have medium-range weather predictability, and are well-resolved in both weather and climate models. For the LSMP relationship with extreme precipitation, we consider the previous literature with respect to definitions and data, dynamical mechanisms, model representation, and climate change trends. There is considerable uncertainty in identifying extremes based on existing observational precipitation data and some limitations in analyzing the associated LSMPs in reanalysis data. Many different definitions of “extreme” are in use, making it difficult to directly compare different studies. Dynamically, several types of meteorological systems—extratropical cyclones, tropical cyclones, mesoscale convective systems, and mesohighs—and several mechanisms—fronts, atmospheric rivers, and orographic ascent—have been shown to be important aspects of extreme precipitation LSMPs. The extreme precipitation is often realized through mesoscale processes organized, enhanced, or triggered by the LSMP. Understanding of model representation, trends, and projections for LSMPs is at an early stage, although some promising analysis techniques have been identified and the LSMP perspective is useful for evaluating the model dynamics associated with extremes.
Journal Article