scholarly journals Normal-mode function representation of global 3-D datasets: an open-access software for atmospheric research community

2014 ◽  
Vol 7 (6) ◽  
pp. 8805-8873
Author(s):  
N. Žagar ◽  
A. Kasahara ◽  
K. Terasaki ◽  
J. Tribbia ◽  
H. Tanaka
Keyword(s):  
Energy Distribution ◽  
Normal Mode ◽  
Large Scale ◽  
Climate Models ◽  
Successful Implementation ◽  
Reanalysis Dataset ◽  
Software Application ◽  
Weather Forecasts ◽  
Mode Function ◽  
Software Execution

Abstract. The paper presents new software for the analysis of global dynamical fields in (re)analyses, weather forecasts and climate models. A new diagnostic tool, developed within the MODES project, allows one to diagnose properties of balanced and inertio-gravity (IG) circulation across many scales. In particular, the IG spectrum, which has only recently become observable, can be studied simultaneously in the mass field and wind field and considering the whole model depth in contrary to majority of studies. The paper presentation includes the theory of normal-mode function expansion, technical details of the Fortran 90 code, examples of namelists which control the software execution and outputs of the software application on the reanalysis dataset ERA Interim. The applied libraries and default compiler are from the open-source domain. A limited understanding of Fortran suffices for the successful implementation of the software. The presented application of the software to the ERA Interim dataset show some features of the large-scale circulation after it has been split into the balanced and IG components. The global energy distribution is dominated by the balanced energy with IG modes making less than 10% of the total wave energy. However, on subsynoptic scales IG energy dominates and it is associated with the main features of tropical variability on all scales. The presented energy distribution and features of the zonally-averaged and equatorial circulation provide a reference for the validation of climate models.

scholarly journals Normal-mode function representation of global 3-D data sets: open-access software for the atmospheric research community

2015 ◽  
Vol 8 (4) ◽  
pp. 1169-1195 ◽  
Author(s):  
N. Žagar ◽  
A. Kasahara ◽  
K. Terasaki ◽  
J. Tribbia ◽  
H. Tanaka
Keyword(s):  
Energy Distribution ◽  
Normal Mode ◽  
Large Scale ◽  
Climate Models ◽  
Reanalysis Data ◽  
Successful Implementation ◽  
Wind Fields ◽  
Data Set ◽  
Software Application ◽  
Mode Function

Abstract. This article presents new software for the analysis of global dynamical fields in (re)analyses, weather forecasts and climate models. A new diagnostic tool, developed within the MODES project, allows one to diagnose properties of balanced and inertio-gravity (IG) circulations across many scales. In particular, the IG spectrum, which has only recently become observable, can be studied simultaneously in the mass and wind fields while considering the whole model depth in contrast to the majority of studies. The paper includes the theory of normal-mode function (NMF) expansion, technical details of the Fortran 90 code, examples of namelists which control the software execution and outputs of the software application on the ERA Interim reanalysis data set. The applied libraries and default compiler are from the open-source domain. A limited understanding of Fortran suffices for the successful implementation of the software. The presented application of the software to the ERA Interim data set reveals several aspects of the large-scale circulation after it has been partitioned into the linearly balanced and IG components. The global energy distribution is dominated by the balanced energy while the IG modes contribute around 10% of the total wave energy. However, on sub-synoptic scales, IG energy dominates and it is associated with the main features of tropical variability on all scales. The presented energy distribution and features of the zonally averaged and equatorial circulation provide a reference for the validation of climate models.

scholarly journals Brief Communication: Drought Likelihood for East Africa

2017 ◽  
Author(s):  
Hui Yang ◽  
Chris Huntingford
Keyword(s):  
East Africa ◽  
Climate Models ◽  
Global Climate ◽  
Extreme Rainfall ◽  
Global Climate Models ◽  
Severe Drought ◽  
East African ◽  
Reanalysis Dataset ◽  
Weather Forecasts ◽  
Medium Range

Abstract. The on-going effects of severe drought in East Africa are causing high levels of malnutrition, hunger, illness and death. Close to 16 million people across Somalia, Ethiopia and Kenya need food, water and medical assistance (DEC, 2017). Many factors influence drought stress and ability to respond. However, inevitably it is asked: are elevated atmospheric greenhouse gas (GHG) concentrations altering the likelihood of extreme rainfall deficits? We find small increases in probability of this for East African, based on merging the observation-based reanalysis dataset by the European Centre for Medium-Range Weather Forecasts (ECMWF) (Dee et al., 2011) with Global Climate Models (GCMs) in the CMIP5 database (Taylor et al., 2012).

scholarly journals Reanalysis comparisons of upper tropospheric–lower stratospheric jets and multiple tropopauses

2017 ◽  
Vol 17 (18) ◽  
pp. 11541-11566 ◽  
Author(s):  
Gloria L. Manney ◽  
Michaela I. Hegglin ◽  
Zachary D. Lawrence ◽  
Krzysztof Wargan ◽  
Luis F. Millán ◽  
...  
Keyword(s):  
High Resolution ◽  
Large Scale ◽  
Climate Models ◽  
Horizontal Resolution ◽  
Temperature Structure ◽  
Grid Spacing ◽  
Frequency Distributions ◽  
Weather Forecasts ◽  
Vertical Grid ◽  
Lowermost Part

Abstract. The representation of upper tropospheric–lower stratospheric (UTLS) jet and tropopause characteristics is compared in five modern high-resolution reanalyses for 1980 through 2014. Climatologies of upper tropospheric jet, subvortex jet (the lowermost part of the stratospheric vortex), and multiple tropopause frequency distributions in MERRA (Modern-Era Retrospective analysis for Research and Applications), ERA-I (ERA-Interim; the European Centre for Medium-Range Weather Forecasts, ECMWF, interim reanalysis), JRA-55 (the Japanese 55-year Reanalysis), and CFSR (the Climate Forecast System Reanalysis) are compared with those in MERRA-2. Differences between alternate products from individual reanalysis systems are assessed; in particular, a comparison of CFSR data on model and pressure levels highlights the importance of vertical grid spacing. Most of the differences in distributions of UTLS jets and multiple tropopauses are consistent with the differences in assimilation model grids and resolution – for example, ERA-I (with coarsest native horizontal resolution) typically shows a significant low bias in upper tropospheric jets with respect to MERRA-2, and JRA-55 (the Japanese 55-year Reanalysis) a more modest one, while CFSR (with finest native horizontal resolution) shows a high bias with respect to MERRA-2 in both upper tropospheric jets and multiple tropopauses. Vertical temperature structure and grid spacing are especially important for multiple tropopause characterizations. Substantial differences between MERRA and MERRA-2 are seen in mid- to high-latitude Southern Hemisphere (SH) winter upper tropospheric jets and multiple tropopauses as well as in the upper tropospheric jets associated with tropical circulations during the solstice seasons; some of the largest differences from the other reanalyses are seen in the same times and places. Very good qualitative agreement among the reanalyses is seen between the large-scale climatological features in UTLS jet and multiple tropopause distributions. Quantitative differences may, however, have important consequences for transport and variability studies. Our results highlight the importance of considering reanalyses differences in UTLS studies, especially in relation to resolution and model grids; this is particularly critical when using high-resolution reanalyses as an observational reference for evaluating global chemistry–climate models.

Characterizing the atmospheric boundary layer over Disko Bay: local structure and links to global dynamics

2021 ◽  
Author(s):  
Arno Hammann ◽  
Kirsty Langley
Keyword(s):  
Climate Change ◽  
Boundary Layer ◽  
Atmospheric Boundary Layer ◽  
Large Scale ◽  
Climate Models ◽  
Current Knowledge ◽  
The Arctic ◽  
Global Dynamics ◽  
Ecosystem Monitoring ◽  
Reanalysis Dataset

<p>Surface air temperatures have been rising roughly twice as fast in the Arctic as in the global average (“Arctic amplification”). Not all responsible physical mechanisms are understood or known, and current climate models frequently underestimate the pace of Arctic warming. Knowledge is lacking specifically about processes involving moisture and the formation of clouds in the the atmospheric boundary layer (ABL). This reduces the reliability of Arctic and global climate change projections and short-term weather predictions.</p><p>We use a comprehensive multi-sensor observational dataset from the Greenland Ecosystem Monitoring (GEM, https://g-e-m.dk/) research site in Qeqertarsuaq, Greenland, in order to identify dominant structural and dynamic patterns of the ABL. Central to this dataset are the atmospheric column profiles of air temperature and water content acquired by a passive microwave radiometer, one of only three such instruments operating in Greenland. The in situ data is related to the large-scale circulation via an analysis of the global ERA5 reanalysis dataset, with a focus on moisture transport from humid latitudes.</p><p>The statistical analysis comprises both process-level relationships between observed variables (regressions) for individual events and pattern recognition techniques (clustering) for the identification of dominant patterns on the small and large scale, an approach particularly suited for the study of an unsteady, changing climate. Moisture enters the Arctic in narrow and infrequent atmospheric bands termed atmospheric rivers, and climate change may alter the frequency of such events, but also the thermodynamic reaction of the ABL to the moisture influx. The current knowledge of the cloudy polar ABL is insufficient to predict important aspects of its behavior, e.g. the lifetime of clouds and the strength of their radiative effect, as well as how large-scale atmospheric dynamics and the presence of elevated inversion layers interact with the structure of the ABL.</p>

scholarly journals Using Deep Learning and Machine Learning Methods to Diagnose Hailstorms in Large-Scale Thermodynamic Environments

2020 ◽  
Vol 12 (24) ◽  
pp. 10499
Author(s):  
Farha Pulukool ◽  
Longzhuang Li ◽  
Chuntao Liu
Keyword(s):  
Machine Learning ◽  
Deep Learning ◽  
Random Forest ◽  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Tropical Rainfall Measuring Mission ◽  
Global Scale ◽  
Weather Forecasts ◽  
One Year

Hailstorms have caused damages in billions of dollars to industrial, electronic, and mechanical properties such as automobiles, buildings, roads, and aircrafts, as well as life threats to crop and cattle populations, due to their hazardous nature. Hence, the relevance of predicting hailstorms in the future has significant scientific, economic, and societal benefits. However, climate models do not have adequate resolutions to explicitly resolve these subscale phenomena. One solution is to estimate the probability of these storms by using large-scale atmospheric thermodynamic environment variables from climate model outputs, but the existing methods only carried out experiments on small datasets limited to a region, country, or location and a large number of input features. Using one year of Tropical Rainfall Measuring Mission (TRMM) observations and European Center for Medium-Range Weather Forecasts (ECMWF) Re-Analysis Interim (ERA-Interim) reanalysis on a global scale, this paper develops two deep-learning-based models (an autoencoder and convolutional neural network (CNN)) as well as a machine learning approach (random forest) for hailstorm prediction by using only four attributes—convective potential energy, convective inhibition, 1–3 km wind shear, and warm cloud depth. In the experiments, the random forest approach produces the best hailstorm prediction performance compared to the other two methods.

scholarly journals Effects of the Sea Breeze Circulation on Soil Temperature Over Kuwait Using in Situ Observations and the ECMWF Model

2019 ◽  
Vol 13 (1) ◽  
pp. 29-42
Author(s):  
Hussain Alsarraf ◽  
Matthew V.D. Broeke ◽  
Hala Aljassar
Keyword(s):  
Pressure Gradient ◽  
Soil Temperature ◽  
Large Scale ◽  
Sea Breeze ◽  
Mesoscale Circulation ◽  
Synoptic Scale ◽  
Reanalysis Dataset ◽  
Weather Forecasts ◽  
Soil Temperatures ◽  
The Persian Gulf

Background: The mesoscale circulation over Kuwait is an important influence on changes in surface temperatures and soil temperatures. Introduction: This paper presents two common summertime atmospheric features over Kuwait linking wind circulation to soil temperatures. Methods: In this study, we use the European Centre for Medium-range Weather Forecasts ECMWF reanalysis ERA-Interim dataset to investigate effects of the synoptic scale and mesoscale circulations. Results: The results show that a large-scale pressure gradient in summer typically leads to northerly winds over Kuwait, while a weak synoptic-scale pressure gradient leads to light easterly humid winds from the Persian Gulf, consistent with a mesoscale circulation. Conclusions: The results demonstrate the significance of wind circulations in driving the Soil Temperature (SOILT). Using the Era-Interim/Land reanalysis dataset for August 2015 over Kuwait, the average SOILT on days of sea breeze is higher than the average SOILT on days dominated by a synoptic-scale pressure gradient.

scholarly journals Extreme associated functions: optimally linking local extremes to large-scale atmospheric circulation structures

2007 ◽  
Vol 7 (5) ◽  
pp. 14433-14460 ◽  
Author(s):  
D. Panja ◽  
F. M. Selten
Keyword(s):  
Time Series ◽  
The Netherlands ◽  
Atmospheric Circulation ◽  
Large Scale ◽  
Climate Models ◽  
Weather Extremes ◽  
Pressure System ◽  
Reanalysis Dataset ◽  
Local Weather ◽  
Large Scale Atmospheric Circulation

Abstract. We present a new statistical method to optimally link local weather extremes to large-scale atmospheric circulation structures. The method is illustrated using July–August daily mean temperature at 2 m height (T2m) time-series over the Netherlands and 500 hPa geopotential height (Z500) time-series over the Euroatlantic region of the ECMWF reanalysis dataset (ERA40). The method identifies patterns in the Z500 time-series that optimally describe, in a precise mathematical sense, the relationship with local warm extremes in the Netherlands. Two patterns are identified; the most important one corresponds to a blocking high pressure system leading to subsidence and calm, dry and sunny conditions over the Netherlands. The second one corresponds to a rare, easterly flow regime bringing warm, dry air into the region. The patterns are robust; they are also identified in shorter subsamples of the total dataset. The method is generally applicable and might prove useful in evaluating the performance of climate models in simulating local weather extremes.

scholarly journals Changes in temperature-precipitation correlations over Europe: Are climate models reliable?

2021 ◽  
Author(s):  
Mathieu Vrac ◽  
Soulivanh Thao ◽  
Pascal Yiou
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Historical Period ◽  
Model Ensemble ◽  
Reanalysis Dataset ◽  
The Past ◽  
Temperature And Precipitation ◽  
Compound Events ◽  
Changes Over Time ◽  
Climate Events

Abstract Inter-variable correlations (e.g., between daily temperature and precipitation) are key statistical properties to characterise probabilities of simultaneous climate events and compound events. Their correct simulations from climate models, both in values and in changes over time, is then a prerequisite to investigate their future changes and associated impacts. Therefore, this study first evaluates the capabilities of one 11-member multi-model ensemble (CMIP6) and one 40-member multi-run single model ensemble (CESM) over Europe to reproduce the characteristics of a reanalysis dataset (ERA5) in terms of temperature-precipitation correlations and their historical changes. Next, the ensembles’ correlations for the end of the 21st century are compared to assess the robustness of the future correlation changes. Over historical period, both CMIP6 and CESM ensembles have season-dependent and spatially structured biases. Moreover, the inter-variable correlations from both ensembles mostly appear stationary. Thus, although reanalyses display significant correlation changes, none of the ensembles is able to reproduce them. However, future correlations show significant changes over large spatial patterns. Yet, those patterns are rather different for CMIP6 and CESM, reflecting a large uncertainty in changes. In addition, for historical and future projections, an analysis conditional on atmospheric circulation regimes is performed. The conditional correlations given the regimes are found to be the main contributor to the biases in correlation over the historical period, and to the past and future changes of correlation. These results highlight the importance of the large-scale circulation regimes and the need to understand their physical relationships with local-scale phenomena associated to specific inter-variable correlations.

Some applications of electron beam microanalysis techniques in VLSI process evaluation

1983 ◽  
Vol 41 ◽  
pp. 160-161
Author(s):  
Simon Thomas
Keyword(s):  
Integrated Circuits ◽  
Process Evaluation ◽  
Large Scale ◽  
Technology Development ◽  
Analytical Techniques ◽  
Successful Implementation ◽  
Analysis Of Failures ◽  
Characterization Of Materials ◽  
Circuits Vlsi

Trends in the technology development of very large scale integrated circuits (VLSI) have been in the direction of higher density of components with smaller dimensions. The scaling down of device dimensions has been not only laterally but also in depth. Such efforts in miniaturization bring with them new developments in materials and processing. Successful implementation of these efforts is, to a large extent, dependent on the proper understanding of the material properties, process technologies and reliability issues, through adequate analytical studies. The analytical instrumentation technology has, fortunately, kept pace with the basic requirements of devices with lateral dimensions in the micron/ submicron range and depths of the order of nonometers. Often, newer analytical techniques have emerged or the more conventional techniques have been adapted to meet the more stringent requirements. As such, a variety of analytical techniques are available today to aid an analyst in the efforts of VLSI process evaluation. Generally such analytical efforts are divided into the characterization of materials, evaluation of processing steps and the analysis of failures.

scholarly journals Global climatology and trends in convective environments from ERA5 and rawinsonde data

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Mateusz Taszarek ◽  
John T. Allen ◽  
Mattia Marchio ◽  
Harold E. Brooks
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Global Climate ◽  
Convective Available Potential Energy ◽  
Global Climate Models ◽  
Convective Precipitation ◽  
The Past ◽  
The Tropics ◽  
Rawinsonde Data

AbstractGlobally, thunderstorms are responsible for a significant fraction of rainfall, and in the mid-latitudes often produce extreme weather, including large hail, tornadoes and damaging winds. Despite this importance, how the global frequency of thunderstorms and their accompanying hazards has changed over the past 4 decades remains unclear. Large-scale diagnostics applied to global climate models have suggested that the frequency of thunderstorms and their intensity is likely to increase in the future. Here, we show that according to ERA5 convective available potential energy (CAPE) and convective precipitation (CP) have decreased over the tropics and subtropics with simultaneous increases in 0–6 km wind shear (BS06). Conversely, rawinsonde observations paint a different picture across the mid-latitudes with increasing CAPE and significant decreases to BS06. Differing trends and disagreement between ERA5 and rawinsondes observed over some regions suggest that results should be interpreted with caution, especially for CAPE and CP across tropics where uncertainty is the highest and reliable long-term rawinsonde observations are missing.

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