scholarly journals Evaluating dust emission model performance using dichotomous satellite observations of dust emission

2022 ◽  
Author(s):  
Mark Hennen ◽  
Adrian Chappell ◽  
Nicholas Webb ◽  
Kerstin Schepanski ◽  
Matthew Baddock ◽  
...  
Keyword(s):  
Wind Speed ◽  
Dust Emission ◽  
Point Sources ◽  
Sediment Supply ◽  
Emission Model ◽  
Atmospheric Dust ◽  
Wind Speeds ◽  
Space And Time ◽  
The Us ◽  
Emission Models

Abstract. Measurements of dust in the atmosphere have long been used to calibrate dust emission models. However, there is growing recognition that atmospheric dust confounds the magnitude and frequency of emission from dust sources and hides potential weaknesses in dust emission model formulation. In the satellite era, dichotomous (presence = 1 or absence = 0) observations of dust emission point sources (DPS) provide a valuable inventory of regional dust emission. We used these DPS data to develop an open and transparent framework to routinely evaluate dust emission model (development) performance using coincidence of simulated and observed dust emission (or lack of emission). To illustrate the utility of this framework, we evaluated the recently developed albedo-based dust emission model (AEM) which included the traditional entrainment threshold (u*ts) at the grain scale, fixed over space and static over time, with sediment supply infinite everywhere. For comparison with the dichotomous DPS data, we reduced the AEM simulations to its frequency of occurrence in which soil surface wind friction velocity (us*) exceeds the u*ts, P(us* > u*ts). We used a global collation of nine DPS datasets from established studies to describe the spatio-temporal variation of dust emission frequency. A total of 37,352 unique DPS locations were aggregated into 1,945 1° grid boxes to harmonise data across the studies which identified a total of 59,688 dust emissions. The DPS data alone revealed that dust emission does not usually recur at the same location, are rare (1.8 %) even in North Africa and the Middle East, indicative of extreme, large wind speed events. The AEM over-estimated the occurrence of dust emission by between 1 and 2 orders of magnitude. More diagnostically, the AEM simulations coincided with dichotomous observations ~71 % of the time but simulated dust emission ~27 % of the time when no dust emission was observed. Our analysis indicates that u*ts was typically too small, needed to vary over space and time, and at the grain-scale u*ts is incompatible with the us* scale (MODIS 500 m). During observed dust emission, us* was too small because wind speeds were too small and/or the wind speed scale (ERA5; 11 km) is incompatible with the us* scale. The absence of any limit to sediment supply caused the AEM to simulate dust emission whenever P (us* > u*ts), producing many false positives when and where wind speeds were frequently large. Dust emission model scaling needs to be reconciled and new parameterisations are required for u*ts and to restrict sediment supply varying over space and time. Whilst u*ts remains poorly constrained and unrealistic assumptions persist about sediment supply and availability, the DPS data provide a basis for the calibration of dust emission models for operational use. As dust emission models develop, these DPS data provide a consistent, reproducible, and valid framework for their routine evaluation and potential model optimisation. This work emphasises the growing recognition that dust emission models should not be evaluated against atmospheric dust.

scholarly journals Weaknesses in dust emission modelling hidden by tuning to dust in the atmosphere

2021 ◽  
Author(s):  
Adrian Chappell ◽  
Nicholas Webb ◽  
Mark Hennen ◽  
Charles Zender ◽  
Philippe Ciais ◽  
...  
Keyword(s):  
Wind Speed ◽  
Vegetation Cover ◽  
Land Surface ◽  
Global Climate ◽  
Dust Emission ◽  
Point Sources ◽  
Emission Model ◽  
Emission Frequency ◽  
Emission Models ◽  
Aerodynamic Roughness

Abstract. Dust emissions influence global climate while simultaneously reducing the productive potential and resilience of landscapes to climate stressors, together impacting food security and human health. Vegetation is a major control on dust emission because it extracts momentum from the wind and shelters the soil surface, protecting dry and loose material from erosion by winds. Many of the current dust emission models (TEM) assume that the Earth’s land surface is constantly devoid of vegetation, then adjust the dust emission using a vegetation cover reciprocal, and finally calibrate to dust in the atmosphere. We compare this approach with an albedo-based dust emission model (AEM) which calibrates Earth’s land surface shadow to shelter depending on wind speed, to represent aerodynamic roughness spatio-temporal variation. We also compare these dust emission models with estimates of dust in the atmosphere using dust optical depth frequency (DOD). Using existing datasets of satellite observed dust emission from dust point sources (DPS), we show that during the same period, DOD frequency exceeds DPS frequency by up to two orders of magnitude (RMSEDOD = 67 days). Relative to DPS frequency, both models over-estimated dust emission frequency by up to one order of magnitude (RMSETEM = 6 days; RMSEAEM = 4 days) but showed strong relations with DPS frequency suitable for calibrating models to observed dust emission. Theoretically, the TEM is incomplete in its formulation, which despite the pragmatic adjustment using the vegetation cover reciprocal, causes dust emission to be highly dependent on wind speed and over-estimates large (> 0.1 kg m−2 a−1) dust emission over vast vegetated areas. Consequently, the TEM produces considerable falsely positive change in dust emission, relative to the AEM. Since the main difference between the dust emission models is the treatment of aerodynamic roughness we conclude that its crude representation in the TEM has caused large, previously unknown, uncertainty in Earth System Models (ESMs). Our results indicate that tuning dust emission models to dust in the atmosphere has hidden for more than two decades, these TEM modelling weaknesses and its poor performance. The AEM overcomes these weaknesses and improves performance without tuning. In ESMs the AEM can be driven by available prognostic albedo to represent the fidelity of drag partition physics to reduce uncertainty of aerosol effects on, and responses to, contemporary and future environmental change.

scholarly journals Identification of Dust Sources in a Saharan Dust Hot-Spot and Their Implementation in a Dust-Emission Model

2018 ◽  
Vol 11 (1) ◽  
pp. 4 ◽  
Author(s):  
Stefanie Feuerstein ◽  
Kerstin Schepanski
Keyword(s):  
Mineral Dust ◽  
Dust Emission ◽  
Sediment Supply ◽  
Emission Model ◽  
Atmospheric Dust ◽  
Dust Source ◽  
Dust Sources ◽  
Dust Load ◽  
Supply Information ◽  
Sentinel 2

Although mineral dust plays a key role in the Earth’s climate system and in climate and weather prediction, models still have difficulties in predicting the amount and distribution of mineral dust in the atmosphere. One reason for this is the limited understanding of the distribution of dust sources and their behavior with respect to their spatiotemporal variability in activity. For a better estimation of the atmospheric dust load, this paper presents an approach to localize dust sources and thereby estimate the sediment supply for a study area centered on the Aïr Massif in Niger with a north–south extent of 16 ∘ –22 ∘ N and an east–west extent of 4 ∘ –12 ∘ E. This approach uses optical Sentinel-2 data at visible and near infrared wavelengths together with HydroSHEDS flow accumulation data to localize ephemeral riverbeds. Visible channels from Sentinel-2 data are used to detect sand sheets and dunes. The identified sediment supply map was compared to the dust source activation frequency derived from the analysis of Desert-Dust-RGB imagery from the Meteosat Second Generation series of satellites. This comparison reveals the strong connection between dust activity, prevailing meteorology and sediment supply. In a second step, the sediment supply information was implemented in a dust-emission model. The simulated emission flux shows how much the model results benefit from the updated sediment supply information in localizing the main dust sources and in retrieving the seasonality of dust activity from these sources. The described approach to characterize dust sources can be implemented in other regional model studies, or even globally, and can thereby help to get a more accurate picture of dust source distribution and a more realistic estimation of the atmospheric dust load.

scholarly journals Does the size distribution of mineral dust aerosols depend on the wind speed at emission?

2011 ◽  
Vol 11 (7) ◽  
pp. 19995-20012 ◽  
Author(s):  
J. F. Kok
Keyword(s):  
Wind Speed ◽  
Size Distribution ◽  
Mineral Dust ◽  
Dust Emission ◽  
Dust Deposition ◽  
Dust Aerosols ◽  
Wind Speeds ◽  
Dust Size Distribution ◽  
Emission Models ◽  
Mineral Dust Aerosols

Abstract. The size distribution of mineral dust aerosols greatly affects their interactions with clouds, radiation, ecosystems, and other components of the Earth system. Several theoretical dust emission models predict that the dust size distribution depends on the wind speed at emission, with larger wind speeds predicted to produce smaller aerosols. The present study investigates this prediction using a compilation of published measurements of the size-resolved vertical dust flux emitted by eroding soils. Surprisingly, these measurements indicate that the size distribution of naturally emitted dust aerosols is independent of the wind speed. This finding is consistent with the recently formulated brittle fragmentation theory of dust emission, but inconsistent with other theoretical dust emission models. The independence of the emitted dust size distribution with wind speed simplifies both the parameterization of dust emission in atmospheric circulation models as well as the interpretation of geological records of dust deposition.

scholarly journals Towards accurate methane point-source quantification from high-resolution 2-D plume imagery

2019 ◽  
Vol 12 (12) ◽  
pp. 6667-6681 ◽  
Author(s):  
Siraput Jongaramrungruang ◽  
Christian Frankenberg ◽  
Georgios Matheou ◽  
Andrew K. Thorpe ◽  
David R. Thompson ◽  
...  
Keyword(s):  
Wind Speed ◽  
Infrared Imaging ◽  
Methane Flux ◽  
Point Sources ◽  
Emission Rates ◽  
Flux Rate ◽  
Background Wind ◽  
Imaging Spectrometer ◽  
Wind Speeds ◽  
Methane Enhancement

Abstract. Methane is the second most important anthropogenic greenhouse gas in the Earth climate system but emission quantification of localized point sources has been proven challenging, resulting in ambiguous regional budgets and source category distributions. Although recent advancements in airborne remote sensing instruments enable retrievals of methane enhancements at an unprecedented resolution of 1–5 m at regional scales, emission quantification of individual sources can be limited by the lack of knowledge of local wind speed. Here, we developed an algorithm that can estimate flux rates solely from mapped methane plumes, avoiding the need for ancillary information on wind speed. The algorithm was trained on synthetic measurements using large eddy simulations under a range of background wind speeds of 1–10 m s−1 and source emission rates ranging from 10 to 1000 kg h−1. The surrogate measurements mimic plume mapping performed by the next-generation Airborne Visible/Infrared Imaging Spectrometer (AVIRIS-NG) and provide an ensemble of 2-D snapshots of column methane enhancements at 5 m spatial resolution. We make use of the integrated total methane enhancement in each plume, denoted as integrated methane enhancement (IME), and investigate how this IME relates to the actual methane flux rate. Our analysis shows that the IME corresponds to the flux rate nonlinearly and is strongly dependent on the background wind speed over the plume. We demonstrate that the plume width, defined based on the plume angular distribution around its main axis, provides information on the associated background wind speed. This allows us to invert source flux rate based solely on the IME and the plume shape itself. On average, the error estimate based on randomly generated plumes is approximately 30 % for an individual estimate and less than 10 % for an aggregation of 30 plumes. A validation against a natural gas controlled-release experiment agrees to within 32 %, supporting the basis for the applicability of this technique to quantifying point sources over large geographical areas in airborne field campaigns and future space-based observations.

scholarly journals SMOKE for Europe – adaptation, modification and evaluation of a comprehensive emission model for Europe

2010 ◽  
Vol 3 (3) ◽  
pp. 949-1007 ◽  
Author(s):  
J. Bieser ◽  
A. Aulinger ◽  
V. Matthias ◽  
M. Quante ◽  
P. Builtjes
Keyword(s):  
Emission Model ◽  
Transport Models ◽  
Emission Data ◽  
Criteria Pollutants ◽  
The Us ◽  
Spatially Distributed ◽  
Us Epa ◽  
Emission Models ◽  
Year 2000

Abstract. The US EPA regional emission model SMOKE was adopted and modified to create temporally and spatially distributed emission for Europe and surrounding countries based on official reports and public domain data only. The aim is to develop a flexible model capable of creating consistent high resolution emission data for long-term runs of Chemical Transport Models (CTM). This modified version of SMOKE, called SMOKE for EUROPE (SMOKE-EU) was successfully used to create hourly gridded emissions for the timespan 1970–2010. In this paper the SMOKE-EU model and the underlying European datasets are introduced. Emission data created by SMOKE-EU for the year 2000 are evaluated by comparison to data of three different state of the art emission models. Differences of SMOKE-EU to those models were in the same range as the differences amongst them. Further, concentrations of criteria pollutants calculated by the CTM CMAQ using the four different emission datasets were compared against EMEP measurements with hourly and daily resolution. Using SMOKE-EU emissions O3, NO2 and SO4 could be modelled most reliably. The amount of simulated concentrations within a factor of 2 (F2) of the observations for these species are: O3 (F2=0.79 N=329 197), NO2 (F2=0.55 N=11 465), and SO4 (F2=0.62 N=17 536). The lowest values were found for NH4 (F2=0.34 N=7400) and NO3 (F2=0.25 N=6184). NH4 concentrations were generally overestimated, leading to a fractional bias (FB) averaged over 22 measurement stations of (FB=0.83±0.41) while better agreements with observations were found for SO4 (FB=0.06±0.38, 51 stations) and NO3 (FB=0.13±0.75, 18 stations). CMAQ simulations using the three other emission datasets were similar to those modelled using SMOKE-EU emissions. Highest differences where found for NH4 while O3 concentrations were almost identical. The results of this comparison confirm that it is adequate to use emissions created by SMOKE-EU as input for CTMs.

scholarly journals The Fennec Automatic Weather Station (AWS) Network: Monitoring the Saharan Climate System

2013 ◽  
Vol 30 (4) ◽  
pp. 709-724 ◽  
Author(s):  
Matthew Hobby ◽  
Matthew Gascoyne ◽  
John H. Marsham ◽  
Mark Bart ◽  
Christopher Allen ◽  
...  
Keyword(s):  
Wind Speed ◽  
Dust Emission ◽  
Longwave Radiation ◽  
Weather Station ◽  
Automatic Weather Station ◽  
Wind Speeds ◽  
Speed Distribution ◽  
Ground Heat Flux ◽  
Wind Speed Distribution ◽  
Communications Protocol

Abstract The Fennec automatic weather station (AWS) network consists of eight stations installed across the Sahara, with four in remote locations in the central desert, where no previous meteorological observations have existed. The AWS measures temperature, humidity, pressure, wind speed, wind direction, shortwave and longwave radiation (upwelling and downwelling), ground heat flux, and ground temperature. Data are recorded every 3 min 20 s, that is, at 3 times the temporal resolution of the World Meteorological Organization’s standard 10-min reporting for winds and wind gusts. Variations in wind speeds on shorter time scales are recorded through the use of second- and third-order moments of 1-Hz data. Using the Iridium Router-Based Unrestricted Digital Internetworking Connectivity Solutions (RUDICS) service, data are transmitted in near–real time (1-h lag) to the United Kingdom, where calibrations are applied and data are uploaded to the Global Telecommunications System (GTS), for assimilation into forecast models. This paper describes the instrumentation used and the data available from the network. Particular focus is given to the engineering applied to the task of making measurements in this remote region and challenging climate. The communications protocol developed to operate over the Iridium RUDICS satellite service is described. Transmitting the second moment of the wind speed distribution is shown to improve estimates of the dust-generating potential of observed winds, especially for winds close to the threshold speed for dust emission of the wind speed distribution. Sources of error are discussed and some preliminary results are presented, demonstrating the system’s potential to record key features of this region.

scholarly journals Towards accurate methane point-source quantification from high-resolution 2D plume imagery

2019 ◽  
Author(s):  
Siraput Jongaramrungruang ◽  
Christian Frankenberg ◽  
Georgios Matheou ◽  
Andrew Thorpe ◽  
David R. Thompson ◽  
...  
Keyword(s):  
Wind Speed ◽  
Infrared Imaging ◽  
Geographical Area ◽  
Methane Flux ◽  
Point Sources ◽  
Emission Rates ◽  
Flux Rate ◽  
Background Wind ◽  
Wind Speeds ◽  
Methane Enhancement

Abstract. Methane is the second most important anthropogenic greenhouse gas in the Earth climate system but emission quantification of localized point sources has been proven challenging, resulting in ambiguous regional budgets and source categories distributions. Although recent advancements in airborne remote sensing instruments enable retrievals of methane enhancements at unprecedented resolution of 1–5 m at regional scales, emission quantification of individual sources can be limited by the lack of knowledge of local wind speed. Here, we developed an algorithm that can estimate flux rates solely from mapped methane plumes, avoiding the need for ancillary information on wind speed. The algorithm was trained on synthetic measurements using Large Eddy Simulation under a range of background wind speeds of 1–10 m/s and source emission rates ranging from 10 to 1000 kg/hr. The surrogate measurements mimic plume mapping performed by the next generation Airborne Visible/Infrared Imaging Spectrometer (AVIRIS-NG) and provide an ensemble of 2-D snapshots of column methane enhancements at 5m spatial resolution. We make use of the integrated total methane enhancement in each plume, denoted as Integrated Methane Enhancement (IME), and investigate how this IME relates to the actual methane flux rate. Our analysis shows that the IME corresponds to the flux rate non-linearly and is strongly dependent on the background wind speed over the plume. We demonstrate that the plume width, defined based on the plume angular distribution around its main axis, provides information on the associated background wind speed. This allows us to invert source flux rate based solely on the IME and the plume-shape itself. On average, the error estimate based on randomly generated plumes is approximately 30 % for an individual estimates and less than 10 % for an aggregation of 30 plumes. A validation against a natural gas controlled release experiment agree to within 32 %, supporting the basis for the applicability of this technique to quantifying point sources over large geographical area in airborne field campaigns and future space-based observations.

scholarly journals Quantifying changes of wind speed distributions in the historical record of Atlantic tropical cyclones

2009 ◽  
Vol 9 (5) ◽  
pp. 1749-1757 ◽  
Author(s):  
K. Chen ◽  
J. McAneney ◽  
K. Cheung
Keyword(s):  
Wind Speed ◽  
Insurance Industry ◽  
Global Climate ◽  
Historical Record ◽  
Systematic Change ◽  
Atlantic Basin ◽  
Wind Speeds ◽  
The Us ◽  
Single Category ◽  
The Stability

Abstract. Here we re-examine the official Atlantic basin tropical cyclone (hurricane) database HURDAT (1851–2008) and quantify differences between wind speed distributions in the early historical (1851–1943) record and more recent observations. Analyses were performed at three different geographical levels: for all six-hourly track segments of all Atlantic basin events, all segments of all events that crossed the US mainland, and US landfalling segments alone. At all three geographical levels of study, distributions of windspeeds over the last two, four and six decades display negligible dispersion or systematic change over time. On the other hand and relative to wind speed frequencies for subsequent years, the 1851–1943 record has a marked and statistically significant over-representation of wind speeds largely corresponding to Saffir-Simpson Categories 1 and 2 and under-representation of Categories 4 and 5 events; importantly, no single Category 5 event is recorded prior to 1924. The stability of the distribution of windspeeds at landfall over the last six decades, the dataset in which we can have most confidence, suggests that the differences in the earlier record are most likely explained by well-known measurement and observational deficiencies. Moreover by disaggregating the Power Dissipation Index (PDI), we demonstrate that the upward trend in Atlantic basin PDI since 1970s does not imply stronger and longer duration Category 5 windspeeds despite a warming climate. These results have implications for hurricane catastrophe loss modeling for the insurance industry and long-term trend analyses of the historical wind speed record, especially those related to the attribution of the role of Global Climate Change.

scholarly journals Modelling soil dust aerosol in the Bodélé depression during the BoDEx campaign

2006 ◽  
Vol 6 (12) ◽  
pp. 4345-4359 ◽  
Author(s):  
I. Tegen ◽  
B. Heinold ◽  
M. Todd ◽  
J. Helmert ◽  
R. Washington ◽  
...  
Keyword(s):  
Dust Cloud ◽  
Surface Wind ◽  
Dust Emission ◽  
Regional Model ◽  
Dust Aerosol ◽  
Emission Model ◽  
Measured Temperature ◽  
Dust Production ◽  
Wind Speeds ◽  
Input Parameters

Abstract. We present regional model simulations of the dust emission events during the Bodélé Dust Experiment (BoDEx) that was carried out in February and March 2005 in Chad. A box model version of the dust emission model is used to test different input parameters for the emission model, and to compare the dust emissions computed with observed wind speeds to those calculated with wind speeds from the regional model simulation. While field observations indicate that dust production occurs via self-abrasion of saltating diatomite flakes in the Bodélé, the emission model based on the assumption of dust production by saltation and using observed surface wind speeds as input parameters reproduces observed dust optical thicknesses well. Although the peak wind speeds in the regional model underestimate the highest wind speeds occurring on 10–12 March 2005, the spatio-temporal evolution of the dust cloud can be reasonably well reproduced by this model. Dust aerosol interacts with solar and thermal radiation in the regional model; it is responsible for a decrease in maximum daytime temperatures by about 5 K at the beginning the dust storm on 10 March 2005. This direct radiative effect of dust aerosol accounts for about half of the measured temperature decrease compared to conditions on 8 March. Results from a global dust model suggest that the dust from the Bodélé is an important contributor to dust crossing the African Savannah region towards the Gulf of Guinea and the equatorial Atlantic, where it can contribute up to 40% to the dust optical thickness.

scholarly journals SMOKE for Europe – adaptation, modification and evaluation of a comprehensive emission model for Europe

2011 ◽  
Vol 4 (1) ◽  
pp. 47-68 ◽  
Author(s):  
J. Bieser ◽  
A. Aulinger ◽  
V. Matthias ◽  
M. Quante ◽  
P. Builtjes
Keyword(s):  
Emission Model ◽  
Transport Models ◽  
Emission Data ◽  
Criteria Pollutants ◽  
The Us ◽  
Spatially Distributed ◽  
Us Epa ◽  
Emission Models ◽  
Year 2000

Abstract. The US EPA regional emission model SMOKE was adopted and modified to create temporally and spatially distributed emission for Europe and surrounding countries based on official reports and public domain data only. The aim is to develop a flexible model capable of creating consistent high resolution emission data for long-term runs of Chemical Transport Models (CTMs). This modified version of SMOKE, called SMOKE for EUROPE (SMOKE-EU) was successfully used to create hourly gridded emissions for the timespan 1970–2010. In this paper the SMOKE-EU model and the underlying European datasets are introduced. Emission data created by SMOKE-EU for the year 2000 are evaluated by comparison to data of three different state-of-the-art emission models. SMOKE-EU produced a range of values comparable to the other three datasets. Further, concentrations of criteria pollutants calculated by the CTM CMAQ using the four different emission datasets were compared against EMEP measurements with hourly and daily resolution. Using SMOKE-EU gave the most reliable modelling of O3, NO2 and SO42−. The amount of simulated concentrations within a factor of 2 (F2) of the observations for these species are: O3 (F2 = 0.79, N = 329 197), NO2 (F2 = 0.55, N = 11 465) and SO42− (F2 = 0.62, N = 17 536). The lowest values were found for NH4+ (F2 = 0.34, N = 7400) and NO3− (F2 = 0.25, N = 6184). NH4+ concentrations were generally overestimated, leading to a fractional bias (FB) averaged over 22 measurement stations of (FB = 0.83 ± 0.41) while better agreements with observations were found for SO42− (FB = 0.06 ± 0.38, 51 stations) and NO3− (FB = 0.13 ± 0.75, 18 stations). CMAQ simulations using the three other emission datasets were similar to those modelled using SMOKE-EU emissions. Highest differences where found for NH4+ while O3 concentrations were almost identical.

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