scholarly journals Investigation of June 2020 Giant Saharan Dust Storm Using Remote Sensing Observations and Model Reanalysis

2021 ◽  
Author(s):  
A. Asutosh ◽  
V. Vinoj ◽  
M. Nuncio
Keyword(s):  
Dust Storm ◽  
Radiative Forcing ◽  
Climate Models ◽  
Satellite Observation ◽  
Saharan Dust ◽  
Resolution Model ◽  
High Resolution Model ◽  
Dust Events ◽  
Index Value

This paper investigates the characteristics and impact of a major Saharan dust storm during June 14th -19th 2020 to atmospheric radiative and thermodynamics properties over the Atlantic Ocean. The event witnessed the highest ever aerosol optical depth (close to 2 during the peak of the storm) for June since 2002. The satellites and high-resolution model reanalysis products well captured the origin, spread and the effects of the dust storm. The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) profiles, lower angstrom exponent values (~ 0.12) and higher aerosol index value (> 4) tracked the presence of elevated dust. It was found that the dust AOD was as much as 250-300% higher than their climatology resulting in an atmospheric radiative forcing ~200% larger. As a result, elevated warming ( 8-16 %) was observed, followed by a drop in relative humidity(2-4%) in the atmospheric column, as evidenced by both in-situ and satellite measurements. Quantifications such as these for extreme dust events provide significant insights that may help in understanding their climate effects, including improvements to dust simulations using chemistry-climate models

scholarly journals Mean and extreme precipitation over European river basins better simulated in a 25 km AGCM

2018 ◽  
Vol 22 (7) ◽  
pp. 3933-3950 ◽  
Author(s):  
Reinhard Schiemann ◽  
Pier Luigi Vidale ◽  
Len C. Shaffrey ◽  
Stephanie J. Johnson ◽  
Malcolm J. Roberts ◽  
...  
Keyword(s):  
Extreme Precipitation ◽  
Climate Models ◽  
Global Climate ◽  
River Basins ◽  
Global Climate Models ◽  
Sensitivity Experiment ◽  
Scale Parameters ◽  
The North ◽  
Resolution Model ◽  
High Resolution Model

Abstract. Limited spatial resolution is one of the factors that may hamper applications of global climate models (GCMs), in particular over Europe with its complex coastline and orography. In this study, the representation of European mean and extreme precipitation is evaluated in simulations with an atmospheric GCM (AGCM) at different resolutions between about 135 and 25 km grid spacing in the mid-latitudes. The continent-wide root-mean-square error in mean precipitation in the 25 km model is about 25  % smaller than in the 135 km model in winter. Clear improvements are also seen in autumn and spring, whereas the model's sensitivity to resolution is very small in summer. Extreme precipitation is evaluated by estimating generalised extreme value distributions (GEVs) of daily precipitation aggregated over river basins whose surface area is greater than 50 000 km2. GEV location and scale parameters are measures of the typical magnitude and of the interannual variability of extremes, respectively. Median model biases in both these parameters are around 10 % in summer and around 20 % in the other seasons. For some river basins, however, these biases can be much larger and take values between 50 % and 100 %. Extreme precipitation is better simulated in the 25 km model, especially during autumn when the median GEV parameter biases are more than halved, and in the North European Plains, from the Loire in the west to the Vistula in the east. A sensitivity experiment is conducted showing that these resolution sensitivities in both mean and extreme precipitation are in many areas primarily due to the increase in resolution of the model orography. The findings of this study illustrate the improved capability of a global high-resolution model in simulating European mean and extreme precipitation.

scholarly journals Tuning and assessment of the HYCOM-NORWECOM V2.1 modeling system

2014 ◽  
Vol 7 (6) ◽  
pp. 8399-8432 ◽  
Author(s):  
A. Samuelsen ◽  
C. Hansen ◽  
H. Wehde
Keyword(s):  
High Resolution ◽  
Arctic Ocean ◽  
Basic Research ◽  
Grazing Rate ◽  
The Arctic ◽  
Atlantic Sector ◽  
In Situ Data ◽  
Resolution Model ◽  
High Resolution Model

Abstract. The HYCOM-NORWECOM modeling system is used both for basic research and as a part of the forecasting system for the Arctic Marine Forecasting Centre through the MyOcean project. Here we present a revised version of this model. The present model, as well as the sensitivity simulations leading up to this version, has been compared to a dataset of in-situ measurements of nutrient and chlorophyll from the Norwegian Sea and the Atlantic sector of the Arctic Ocean. The revisions having most impact included adding diatoms to the diet of micro-zooplankton, increasing micro-zooplankton grazing rate and decreased silicate-to-nitrate ratio in diatoms. Model runs are performed both with a coarse- (~50 km) and higher-resolution (~15 km) model configuration, both covering the North Atlantic and Arctic Ocean. While the new model formulation improves the results in both the coarse- and high-resolution model, the nutrient bias is smaller in the high-resolution model, probably as a result of the better resolution of the main processes and with that improved circulation. The final revised version delivers satisfactory results for all three nutrients as well as improved result for chlorophyll in terms of the annual cycle amplitude. However, for chlorophyll the correlation with in-situ data remains relatively low. Besides the large uncertainties associated with observational data this is possibly caused by the fact that constant C / N and Chl / N ratios are implemented in the model.

Contribution of IASI to the observation of the dust aerosol diurnal cycle over Sahara

2020 ◽  
Author(s):  
virginie capelle ◽  
alain chedin ◽  
Noelle Scott ◽  
Martin Todd
Keyword(s):  
Diurnal Cycle ◽  
Deep Convection ◽  
Dust Emission ◽  
Saharan Dust ◽  
Dust Aerosols ◽  
Source Regions ◽  
Resolution Model ◽  
High Resolution Model ◽  
Dust Distribution ◽  
Realistic Information

<p>The Infrared Atmospheric Sounder Interferometer (IASI) is well suited for monitoring of dust aerosols because of its capability to determine both AOD and altitude of the dust layer, and because of the good match between the IASI times of observation (9.30 am and pm, local time) and the time of occurrence of the main Saharan dust uplift mechanisms. Here, starting from IASI-derived dust characteristics for an 11-year period, we assess the capability of IASI to bring realistic information on the dust diurnal cycle. We first show the morning and nighttime climatology of IASI-derived dust AOD for two major dust source regions of the Sahara: The Bodele Depression and the Adrar region. Compared with simulations from a high resolution model, permitting deep convection to be explicitly resolved, IASI performs well. In a second step, a Dust Emission Index specific to IASI is constructed, combining simultaneous information on dust AOD and mean altitude, with the aim of observing the main dust emission areas, daytime and nighttime. Comparisons are then made with other equivalent existing results derived from ground based or other satellite observations. Results demonstrate the capability of IASI to improve the documentation of dust distribution over Sahara over a long period of time. Associating observations of dust aerosols in the visible, on which a majority of aerosol studies are so far based, and in the infrared thus appears as a way to complement the results from other satellite instruments in view of improving our knowledge of their impact on climate.</p>

scholarly journals Improved Simulation of Regional Climate by Global Models with Higher Resolution: Skill Scores Correlated with Grid Length*

2015 ◽  
Vol 28 (15) ◽  
pp. 5985-6000 ◽  
Author(s):  
I. G. Watterson
Keyword(s):  
Climate Models ◽  
Regional Climate ◽  
Coupled Model ◽  
Skill Score ◽  
Cmip5 Models ◽  
Four Seasons ◽  
Skill Scores ◽  
Resolution Model ◽  
High Resolution Model ◽  
Grid Length

Abstract The current generation of climate models, as represented by phase 5 of the Coupled Model Intercomparison Project (CMIP5), has previously been assessed as having more skill in simulating the observed climate than the previous ensemble from phase 3 of CMIP (CMIP3). Furthermore, the skill of models in reproducing seasonal means of precipitation, temperature, and pressure from two observational datasets, quantified by the nondimensional Arcsin–Mielke skill score, appeared to be influenced by model resolution. The analysis is extended to 42 CMIP5 and 24 CMIP3 models. For the combined skill scores for six continents, averaged over the three variables and four seasons, the correlation with model grid length in the 66-model ensemble is −0.73. Focusing on the comparison with ERA-Interim data at higher resolution and with greater regional detail, correlations are nearly as strong for scores over the ocean domain as for land. For the global domain (excluding the Antarctic cap), the correlation of the overall skill score with grid length is −0.61, and it is nearly as strong for each variable. For most tests the improved averaged score of CMIP5 models relative to those from CMIP3 is largely consistent with their increased resolution. However, the improvement for precipitation and the correlations with length are both smaller if rmse is used as a metric. They are smaller again using the GPCP observational data, as the regional detail from a high-resolution model can lead to larger differences when compared to relatively smooth observational fields.

scholarly journals Towards Direct Simulation of Future Tropical Cyclone Statistics in a High-Resolution Global Atmospheric Model

2010 ◽  
Vol 2010 ◽  
pp. 1-13 ◽  
Author(s):  
Michael F. Wehner ◽  
G. Bala ◽  
Phillip Duffy ◽  
Arthur A. Mirin ◽  
Raquel Romano
Keyword(s):  
High Resolution ◽  
Radiative Forcing ◽  
General Circulation ◽  
Circulation Model ◽  
Atmospheric Model ◽  
Tropical Storm ◽  
Model Studies ◽  
The North ◽  
Resolution Model ◽  
High Resolution Model

We present a set of high-resolution global atmospheric general circulation model (AGCM) simulations focusing on the model's ability to represent tropical storms and their statistics. We find that the model produces storms of hurricane strength with realistic dynamical features. We also find that tropical storm statistics are reasonable, both globally and in the north Atlantic, when compared to recent observations. The sensitivity of simulated tropical storm statistics to increases in sea surface temperature (SST) is also investigated, revealing that a credible late 21st century SST increase produced increases in simulated tropical storm numbers and intensities in all ocean basins. While this paper supports previous high-resolution model and theoretical findings that the frequency of very intense storms will increase in a warmer climate, it differs notably from previous medium and high-resolution model studies that show a global reduction in total tropical storm frequency. However, we are quick to point out that this particular model finding remains speculative due to a lack of radiative forcing changes in our time-slice experiments as well as a focus on the Northern hemisphere tropical storm seasons.

scholarly journals Improving our fundamental understanding of the role of aerosol−cloud interactions in the climate system

2016 ◽  
Vol 113 (21) ◽  
pp. 5781-5790 ◽  
Author(s):  
John H. Seinfeld ◽  
Christopher Bretherton ◽  
Kenneth S. Carslaw ◽  
Hugh Coe ◽  
Paul J. DeMott ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Radiative Forcing ◽  
General Circulation ◽  
Climate Models ◽  
Large Range ◽  
General Circulation Models ◽  
Radiative Properties ◽  
Aerosol Cloud ◽  
Aerosol Cloud Interactions

The effect of an increase in atmospheric aerosol concentrations on the distribution and radiative properties of Earth’s clouds is the most uncertain component of the overall global radiative forcing from preindustrial time. General circulation models (GCMs) are the tool for predicting future climate, but the treatment of aerosols, clouds, and aerosol−cloud radiative effects carries large uncertainties that directly affect GCM predictions, such as climate sensitivity. Predictions are hampered by the large range of scales of interaction between various components that need to be captured. Observation systems (remote sensing, in situ) are increasingly being used to constrain predictions, but significant challenges exist, to some extent because of the large range of scales and the fact that the various measuring systems tend to address different scales. Fine-scale models represent clouds, aerosols, and aerosol−cloud interactions with high fidelity but do not include interactions with the larger scale and are therefore limited from a climatic point of view. We suggest strategies for improving estimates of aerosol−cloud relationships in climate models, for new remote sensing and in situ measurements, and for quantifying and reducing model uncertainty.

scholarly journals Vertical profiles of aerosol mass concentration derived by unmanned airborne in situ and remote sensing instruments during dust events

2018 ◽  
Vol 11 (5) ◽  
pp. 2897-2910 ◽  
Author(s):  
Dimitra Mamali ◽  
Eleni Marinou ◽  
Jean Sciare ◽  
Michael Pikridas ◽  
Panagiotis Kokkalis ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Mass Concentration ◽  
Climate Models ◽  
In Situ Measurements ◽  
Saharan Dust ◽  
Dust Particles ◽  
Vertical Profiles ◽  
Aerosol Mass ◽  
Aerosol Mass Concentration

Abstract. In situ measurements using unmanned aerial vehicles (UAVs) and remote sensing observations can independently provide dense vertically resolved measurements of atmospheric aerosols, information which is strongly required in climate models. In both cases, inverting the recorded signals to useful information requires assumptions and constraints, and this can make the comparison of the results difficult. Here we compare, for the first time, vertical profiles of the aerosol mass concentration derived from light detection and ranging (lidar) observations and in situ measurements using an optical particle counter on board a UAV during moderate and weak Saharan dust episodes. Agreement between the two measurement methods was within experimental uncertainty for the coarse mode (i.e. particles having radii >0.5 µm), where the properties of dust particles can be assumed with good accuracy. This result proves that the two techniques can be used interchangeably for determining the vertical profiles of aerosol concentrations, bringing them a step closer towards their systematic exploitation in climate models.

scholarly journals An initial assessment of SMAP soil moisture retrievals using high-resolution model simulations and in situ observations

2016 ◽  
Vol 43 (18) ◽  
pp. 9662-9668 ◽  
Author(s):  
Ming Pan ◽  
Xitian Cai ◽  
Nathaniel W. Chaney ◽  
Dara Entekhabi ◽  
Eric F. Wood
Keyword(s):  
Soil Moisture ◽  
High Resolution ◽  
Initial Assessment ◽  
Model Simulations ◽  
Resolution Model ◽  
High Resolution Model ◽  
In Situ Observations

scholarly journals Precipitation bias correction of very high resolution regional climate models

2013 ◽  
Vol 10 (6) ◽  
pp. 8145-8165 ◽  
Author(s):  
D. Argüeso ◽  
J. P. Evans ◽  
L. Fita
Keyword(s):  
High Resolution ◽  
Bias Correction ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Correction Method ◽  
Accurate Information ◽  
Recent Climate ◽  
Resolution Model ◽  
High Resolution Model

Abstract. Regional climate models are prone to biases in precipitation that are problematic for use in impact models such as hydrology models. A large number of methods have already been proposed aimed at correcting various moments of the rainfall distribution. They all require that the model produce the same or a higher number of rain days than the observational datasets, which are usually gridded datasets. Models have traditionally met this condition because their spatial resolution was coarser than the observational grids. But recent climate simulations use higher resolution than the gridded observational products and the models are likely to produce fewer rain days than the gridded observations. In this study, model output from a simulation at 2 km resolution are compared with gridded and in-situ observational datasets to determine whether the new scenario calls for revised methodologies. The gridded observations are found to be inadequate to correct the high-resolution model at daily timescales. A histogram equalisation bias correction method is selected and adapted to the use of stations, alleviating the problems associated with relatively low-resolution observational grids. The method is efficient at bias correcting both seasonal and daily characteristics of precipitation, providing more accurate information that is crucial for impact assessment studies.

scholarly journals A Satellite-Based Model for Estimating Latent Heat Flux From Urban Vegetation

2021 ◽  
Vol 9 ◽  
Author(s):  
Ian A. Smith ◽  
Joy B. Winbourne ◽  
Koen F. Tieskens ◽  
Taylor S. Jones ◽  
Fern L. Bromley ◽  
...  
Keyword(s):  
Heat Flux ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Extreme Heat ◽  
Extreme Heat Events ◽  
Resolution Model ◽  
Complex Landscape ◽  
High Resolution Model ◽  
Heat Events

The impacts of extreme heat events are amplified in cities due to unique urban thermal properties. Urban greenspace mitigates high temperatures through evapotranspiration and shading; however, quantification of vegetative cooling potential in cities is often limited to simple remote sensing greenness indices or sparse, in situ measurements. Here, we develop a spatially explicit, high-resolution model of urban latent heat flux from vegetation. The model iterates through three core equations that consider urban climatological and physiological characteristics, producing estimates of latent heat flux at 30-m spatial resolution and hourly temporal resolution. We find strong agreement between field observations and model estimates of latent heat flux across a range of ecosystem types, including cities. This model introduces a valuable tool to quantify the spatial heterogeneity of vegetation cooling benefits across the complex landscape of cities at an adequate resolution to inform policies addressing the effects of extreme heat events.

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