scholarly journals Empirical values and assumptions in the convection of numerical models

2021 ◽  
Author(s):  
Anahí Villalba-Pradas ◽  
Francisco J. Tapiador
Keyword(s):  
Climate Models ◽  
Prediction Models ◽  
Numerical Models ◽  
Global Climate ◽  
Weather Prediction ◽  
Global Climate Models ◽  
Spatial And Temporal Scales ◽  
Weather Events ◽  
Wide Range ◽  
Convection Schemes

Abstract. Convection influences climate and weather events over a wide range of spatial and temporal scales. Therefore, accurate predictions of the time and location of convection and its development into severe weather are of great importance. Convection has to be parameterized in Numerical Weather Prediction models, Global Climate Models, and Earth System Models (NWPs, GCMs, and ESMs) as the key physical processes occur at scales much lower than the model grid size. The convection schemes described in the literature represent the physics by simplified models that require assumptions about the processes and the use of a number of parameters based on empirical values. The present paper examines these choices and their impacts on model outputs and emphasizes the importance of observations to improve our current understanding of the physics of convection.

scholarly journals Back to the Future: Using Long-Term Observational and Paleo-Proxy Reconstructions to Improve Model Projections of Antarctic Climate

Geosciences ◽  
2019 ◽  
Vol 9 (6) ◽  
pp. 255 ◽  
Author(s):  
Thomas J. Bracegirdle ◽  
Florence Colleoni ◽  
Nerilie J. Abram ◽  
Nancy A. N. Bertler ◽  
Daniel A. Dixon ◽  
...  
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Ice Core ◽  
Global Climate Models ◽  
Climate Projections ◽  
Past Performance ◽  
Wide Range ◽  
Proxy Reconstructions

Quantitative estimates of future Antarctic climate change are derived from numerical global climate models. Evaluation of the reliability of climate model projections involves many lines of evidence on past performance combined with knowledge of the processes that need to be represented. Routine model evaluation is mainly based on the modern observational period, which started with the establishment of a network of Antarctic weather stations in 1957/58. This period is too short to evaluate many fundamental aspects of the Antarctic and Southern Ocean climate system, such as decadal-to-century time-scale climate variability and trends. To help address this gap, we present a new evaluation of potential ways in which long-term observational and paleo-proxy reconstructions may be used, with a particular focus on improving projections. A wide range of data sources and time periods is included, ranging from ship observations of the early 20th century to ice core records spanning hundreds to hundreds of thousands of years to sediment records dating back 34 million years. We conclude that paleo-proxy records and long-term observational datasets are an underused resource in terms of strategies for improving Antarctic climate projections for the 21st century and beyond. We identify priorities and suggest next steps to addressing this.

Northern Hemisphere Atmospheric Blocking Representation in Global Climate Models: Twenty Years of Improvements?

2016 ◽  
Vol 29 (24) ◽  
pp. 8823-8840 ◽  
Author(s):  
Paolo Davini ◽  
Fabio D’Andrea
Keyword(s):  
Northern Hemisphere ◽  
General Circulation ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Model ◽  
Weather Prediction ◽  
Global Climate Models ◽  
Main Concern ◽  
Atmospheric Blocking ◽  
Atlantic Sector

Abstract The correct simulation of midlatitude atmospheric blocking has always been a main concern since the earliest days of numerical modeling of Earth’s atmosphere. To this day blocking represents a considerable source of error for general circulation models from both a numerical weather prediction and a climate perspective. In the present work, 20 years of global climate model (GCM) developments are analyzed from the special point of view of Northern Hemisphere atmospheric blocking simulation. Making use of a series of equivalent metrics, three generations of GCMs are compared. This encompasses a total of 95 climate models, many of which are different—successive—versions of the same model. Results from model intercomparison projects AMIP1 (1992), CMIP3 (2007), and CMIP5 (2012) are taken into consideration. Although large improvements are seen over the Pacific Ocean, only minor advancements have been achieved over the Euro-Atlantic sector. Some of the most recent GCMs still exhibit the same negative bias as 20 years ago in this region, associated with large geopotential height systematic errors. Some individual models, nevertheless, have improved and do show good performances in both sectors. Negligible differences emerge among ocean-coupled or atmosphere-only simulations, suggesting weak relevance of sea surface temperature biases. Conversely, increased horizontal resolution seems to be able to alleviate the Euro-Atlantic blocking bias.

scholarly journals Mesoscale Simulations of Australian Direct Normal Irradiance, Featuring an Extreme Dust Event

2018 ◽  
Vol 57 (3) ◽  
pp. 493-515 ◽  
Author(s):  
S. K. Mukkavilli ◽  
A. A. Prasad ◽  
R. A. Taylor ◽  
A. Troccoli ◽  
M. J. Kay
Keyword(s):  
Radiative Transfer ◽  
Climate Models ◽  
Global Climate ◽  
Weather Prediction ◽  
Wrf Model ◽  
Global Climate Models ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Dust Event ◽  
Direct Normal Irradiance

AbstractDirect normal irradiance (DNI) is the main input for concentrating solar power (CSP) technologies—an important component in future energy scenarios. DNI forecast accuracy is sensitive to radiative transfer schemes (RTSs) and microphysics in numerical weather prediction (NWP) models. Additionally, NWP models have large regional aerosol uncertainties. Dust aerosols can significantly attenuate DNI in extreme cases, with marked consequences for applications such as CSP. To date, studies have not compared the skill of different physical parameterization schemes for predicting hourly DNI under varying aerosol conditions over Australia. The authors address this gap by aiming to provide the first Weather and Forecasting (WRF) Model DNI benchmarks for Australia as baselines for assessing future aerosol-assimilated models. Annual and day-ahead simulations against ground measurements at selected sites focusing on an extreme dust event are run. Model biases are assessed for five shortwave RTSs at 30- and 10-km grid resolutions, along with the Thompson aerosol-aware scheme in three different microphysics configurations: no aerosols, fixed optical properties, and monthly climatologies. From the annual simulation, the best schemes were the Rapid Radiative Transfer Model for global climate models (RRTMG), followed by the new Goddard and Dudhia schemes, despite the relative simplicity of the latter. These top three RTSs all had 1.4–70.8 W m−2 lower mean absolute error than persistence. RRTMG with monthly aerosol climatologies was the best combination. The extreme dust event had large DNI mean bias overpredictions (up to 4.6 times), compared to background aerosol results. Dust storm–aware DNI forecasts could benefit from RRTMG with high-resolution aerosol inputs.

scholarly journals Compound Hydrometeorological Extremes: Drivers, Mechanisms and Methods

2021 ◽  
Vol 9 ◽  
Author(s):  
Wei Zhang ◽  
Ming Luo ◽  
Si Gao ◽  
Weilin Chen ◽  
Vittal Hari ◽  
...  
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Statistical Modeling ◽  
Storm Surge ◽  
Climate Models ◽  
Heat Waves ◽  
Numerical Models ◽  
Global Climate ◽  
The State ◽  
Global Climate Models

Compound extremes pose immense challenges and hazards to communities, and this is particularly true for compound hydrometeorological extremes associated with deadly floods, surges, droughts, and heat waves. To mitigate and better adapt to compound hydrometeorological extremes, we need to better understand the state of knowledge of such extremes. Here we review the current advances in understanding compound hydrometeorological extremes: compound heat wave and drought (hot-dry), compound heat stress and extreme precipitation (hot-wet), cold-wet, cold-dry and compound flooding. We focus on the drivers of these extremes and methods used to investigate and quantify their associated risk. Overall, hot-dry compound extremes are tied to subtropical highs, blocking highs, atmospheric stagnation events, and planetary wave patterns, which are modulated by atmosphere-land feedbacks. Compared with hot-dry compound extremes, hot-wet events are less examined in the literature with most works focusing on case studies. The cold-wet compound events are commonly associated with snowfall and cold frontal systems. Although cold-dry events have been found to decrease, their underlying mechanisms require further investigation. Compound flooding encompasses storm surge and high rainfall, storm surge and sea level rise, storm surge and riverine flooding, and coastal and riverine flooding. Overall, there is a growing risk of compound flooding in the future due to changes in sea level rise, storm intensity, storm precipitation, and land-use-land-cover change. To understand processes and interactions underlying compound extremes, numerical models have been used to complement statistical modeling of the dependence between the components of compound extremes. While global climate models can simulate certain types of compound extremes, high-resolution regional models coupled with land and hydrological models are required to simulate the variability of compound extremes and to project changes in the risk of such extremes. In terms of statistical modeling of compound extremes, previous studies have used empirical approach, event coincidence analysis, multivariate distribution, the indicator approach, quantile regression and the Markov Chain method to understand the dependence, greatly advancing the state of science of compound extremes. Overall, the selection of methods depends on the type of compound extremes of interests and relevant variables.

scholarly journals Geometrical and Microphysical Properties of Clouds Formed in the Presence of Dust above the Eastern Mediterranean

2021 ◽  
Vol 13 (24) ◽  
pp. 5001
Author(s):  
Eleni Marinou ◽  
Kalliopi Artemis Voudouri ◽  
Ioanna Tsikoudi ◽  
Eleni Drakaki ◽  
Alexandra Tsekeri ◽  
...  
Keyword(s):  
Climate Models ◽  
Eastern Mediterranean ◽  
Global Climate ◽  
Weather Prediction ◽  
Global Climate Models ◽  
Mixed Phase ◽  
Atmospheric Conditions ◽  
Low Level ◽  
Microphysical Properties ◽  
Mixed Phase Clouds

In this work, collocated lidar–radar observations are used to retrieve the vertical profiles of cloud properties above the Eastern Mediterranean. Measurements were performed in the framework of the PRE-TECT experiment during April 2017 at the Greek atmospheric observatory of Finokalia, Crete. Cloud geometrical and microphysical properties at different altitudes were derived using the Cloudnet target classification algorithm. We found that the variable atmospheric conditions that prevailed above the region during April 2017 resulted in complex cloud structures. Mid-level clouds were observed in 38% of the cases, high or convective clouds in 58% of the cases, and low-level clouds in 2% of the cases. From the observations of cloudy profiles, pure ice phase occurred in 94% of the cases, mixed-phase clouds were observed in 27% of the cases, and liquid clouds were observed in 8.7% of the cases, while Drizzle or rain occurred in 12% of the cases. The significant presence of Mixed-Phase Clouds was observed in all the clouds formed at the top of a dust layer, with three times higher abundance than the mean conditions (26% abundance at −15 °C). The low-level clouds were formed in the presence of sea salt and continental particles with ice abundance below 30%. The derived statistics on clouds’ high-resolution vertical distributions and thermodynamic phase can be combined with Cloudnet cloud products and lidar-retrieved aerosol properties to study aerosol-cloud interactions in this understudied region and evaluate microphysics parameterizations in numerical weather prediction and global climate models.

scholarly journals Improving the visual communication of environmental model projections

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hayley J. Bannister ◽  
Paul G. Blackwell ◽  
Kieran Hyder ◽  
Thomas J. Webb
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Scientific Evidence ◽  
Evidence Base ◽  
Global Climate Models ◽  
Accurate Information ◽  
Research Areas ◽  
Box Plots ◽  
Wide Range ◽  
The Impact

AbstractEnvironmental and ecosystem models can help to guide management of changing natural systems by projecting alternative future states under a common set of scenarios. Combining contrasting models into multi-model ensembles (MMEs) can improve the skill and reliability of projections, but associated uncertainty complicates communication of outputs, affecting both the effectiveness of management decisions and, sometimes, public trust in scientific evidence itself. Effective data visualisation can play a key role in accurately communicating such complex outcomes, but we lack an evidence base to enable us to design them to be visually appealing whilst also effectively communicating accurate information. To address this, we conducted a survey to identify the most effective methods for visually communicating the outputs of an ensemble of global climate models. We measured the accuracy, confidence, and ease with which the survey participants were able to interpret 10 visualisations depicting the same set of model outputs in different ways, as well as their preferences. Dot and box plots outperformed all other visualisations, heat maps and radar plots were comparatively ineffective, while our infographic scored highly for visual appeal but lacked information necessary for accurate interpretation. We provide a set of guidelines for visually communicating the outputs of MMEs across a wide range of research areas, aimed at maximising the impact of the visualisations, whilst minimizing the potential for misinterpretations, increasing the societal impact of the models and ensuring they are well-placed to support management in the future.

Sensitivity of resolved gravity wave momentum fluxes on different background separation methods in a high resolution simulation.

2020 ◽  
Author(s):  
Zuzana Procházková ◽  
Petr Šácha ◽  
Aleš Kuchař ◽  
Petr Pišoft ◽  
Christopher Kruse
Keyword(s):  
High Resolution ◽  
Climate Models ◽  
Global Climate ◽  
Internal Gravity Waves ◽  
Complex Problem ◽  
Global Climate Models ◽  
Satellite Observations ◽  
Detection Methods ◽  
Spatial And Temporal Scales ◽  
Resolution Model

<p>Internal gravity waves (GWs) and their interaction with the atmospheric circulation present a complex problem for global climate models (GCMs) due to a variety of spatial and temporal scales involved. GWs and their effects in GCMs are parameterized by employing various simplifications and restrictions<br>(propagation, spectrum). Also, our incomplete knowledge of the GW properties in the real atmosphere complicates the situation. Global (satellite) observations of the GW activity are spatiotemporally sparse, making the quantification of the GW interaction with the circulation hardly possible. Recently, atmospheric models capable of resolving most of the GW spectrum have been emerging due to the increasing performance of computing systems. It is increasingly acknowledged that a combination of various types of observations with dedicated high-resolution, GW resolving, simulations has a potential to provide the most precise information about GWs. This combination will allow us to better understand the uncertainty of satellite observations of GW activity, which in turn will be used to develop new GW parameterizations or in development of GW resolving models.<br>In this study, we will analyze sensitivity of GW momentum flux and its divergence on background separation (and other GW detection) methods and approximations (Boussinesq, anelastic) used in the formulas. We analyze data from high-resolution model simulations produced for an observing system simulation experiment of the ISSI team "New Quantitative Constraints on Orographic GW Stress and Drag" (to be introduced in an invited presentation by Ch. Kruse).</p>

scholarly journals Multi-thousand member ensemble atmospheric simulations with global 60km resolution using climateprediction.net

2020 ◽  
Author(s):  
Peter Watson ◽  
Sarah Sparrow ◽  
William Ingram ◽  
Simon Wilson ◽  
Drouard Marie ◽  
...  
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Atmospheric Model ◽  
Computing System ◽  
Extreme Weather ◽  
Global Climate Models ◽  
Extreme Weather Events ◽  
Weather Events ◽  
The Impact

<p>Multi-thousand member climate model simulations are highly valuable for showing how extreme weather events will change as the climate changes, using a physically-based approach. However, until now, studies using such an approach have been limited to using models with a resolution much coarser than the most modern systems. We have developed a global atmospheric model with 5/6°x5/9° resolution (~60km in middle latitudes) that can be run in the climateprediction.net distributed computing system to produce such large datasets. This resolution is finer than that of many current global climate models and sufficient for good simulation of extratropical synoptic features such as storms. It will also allow many extratropical extreme weather events to be simulated without requiring regional downscaling. We will show that this model's simulation of extratropical weather is competitive with that in other current models. We will also present results from the first multi-thousand member ensembles produced at this resolution, showing the impact of 1.5°C and 2°C global warming on extreme winter rainfall and extratropical cyclones in Europe.</p>

scholarly journals Connection of Quasi-Resonant Amplification to the Delay in Atmospheric Residence Times Over India

2021 ◽  
Vol 9 ◽  
Author(s):  
T. V. Lakshmi Kumar ◽  
G. Purna Durga ◽  
K. Koteswara Rao ◽  
Humberto Barbosa ◽  
Ashwini Kulkarni ◽  
...  
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Monsoon Season ◽  
Coupled Model ◽  
Southwest Monsoon ◽  
Global Climate Models ◽  
Extreme Weather Events ◽  
Residence Times ◽  
Tropical Country ◽  
Weather Events

Mean monthly Atmospheric Residence Times (ART), deduced from the global climate models of Coupled Model Intercomparison Project 5 (CMIP5) under RCP4.5 and RCP8.5 emission scenarios over Indian landmass, show a perceptible increase by the end of the 21st century. India, being a tropical country, faces prolonged ART, particularly during the June month of Southwest monsoon season (June to September) which will be an indicative measure of the increased frequency of extreme weather events. Here we show a possible connection of quasi-resonant amplification (QRA) to the recent (August 2018) Kerala heavy rains that resulted in severe floods and claimed more than 400 mortalities. Remarkable delay in residence times over India during June is shown to have an association with QRA evidenced by the higher magnitudes of amplitudes at the wavenumbers six and seven from the 19 global climate models of CMIP5 under the RCP4.5 and RCP8.5 scenarios.

CLIMATE CHANGE: A 1994 SCIENCE SUMMARY

1994 ◽  
Vol 34 (2) ◽  
pp. 104
Author(s):  
C.D. Mitchell
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Numerical Models ◽  
Global Climate ◽  
Statistical Tests ◽  
Global Scale ◽  
Global Climate Models ◽  
Climate System ◽  
Improve Model ◽  
Regional Estimates

New observations of the chemical composition of the atmosphere are reshaping scientific understanding of the global sources and sinks of the greenhouse gases. Current trends in the atmospheric concentrations of some of these gases are reviewed, with reference to new work emerging from Antarctic ice cores.Accompanying an understanding of the composition of the atmosphere, is the need to understand the processes which drive the global climate system, including interactions between the atmosphere and oceans. Studies of climatic processes therefore form the scientific underpinning for the development of numerical models that describe the response of the global climate system to observed changes in the composition of the atmosphere.Success or failure in efforts to improve model simulations can be assessed using a variety of objective statistical tests. Examples of such tests show demonstrable progress in the ability of global climate models to simulate the present day climate realistically.Since confidence in the regional details of climate predictions from climate models is low, considerable effort is being devoted to developing models capable of providing improved regional estimates of climate change and in practice a variety of models not limited to the global-scale models are used in this work. In the meantime, several approaches to assessing the potential impacts of climate change are possible. These are discussed with special reference to tropical cyclones and east coast lows.Throughout this review emphasis is placed on recent Australian contributions to the field, most notably work conducted within CSIRO.

Sign in / Sign up

Export Citation Format

Share Document