scholarly journals Observations of mesoscale and boundary-layer circulations affecting dust uplift and transport in the Saharan boundary layer

2008 ◽  
Vol 8 (3) ◽  
pp. 8817-8846 ◽  
Author(s):  
J. H. Marsham ◽  
D. J. Parker ◽  
C. M. Grams ◽  
W. M. F. Grey ◽  
B. T. Johnson
Keyword(s):  
Boundary Layer ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Climate Models ◽  
Vertical Mixing ◽  
Large Eddy ◽  
The Mean ◽  
Weak Winds ◽  
Along Track

Abstract. Observations of the Saharan boundary layer, made during the GERBILS field campaign, show that mesoscale land surface temperature variations (which were related to albedo variations) induced mesoscale circulations, and that mesoscale and boundary-layer circulations affected dust uplift and transport. These processes are unrepresented in many climate models, but may have significant impacts on the vertical transport and uplift of desert dust. Mesoscale effects in particular tend to be difficult to parameterise. With weak winds along the aircraft track, land surface temperature anomalies with scales of greater than 10 km are shown to significantly affect boundary-layer temperatures and winds. Such anomalies are expected to affect the vertical mixing of the dusty and weakly stratified Saharan Air Layer (SAL). Mesoscale variations in winds are also shown to affect dust loadings in the boundary-layer. In a region of local uplift, with strong along-track winds, boundary-layer rolls are shown to lead to warm moist dusty updraughts in the boundary layer. Large eddy model (LEM) simulations suggest that these rolls increased uplift by approximately 30%. The modelled effects of boundary-layer convection on uplift is shown to be larger when the boundary-layer wind is decreased, and most significant when the mean wind is below the threshold for dust uplift and the boundary-layer convection leads to uplift which would not otherwise occur.

scholarly journals Observations of mesoscale and boundary-layer scale circulations affecting dust transport and uplift over the Sahara

2008 ◽  
Vol 8 (23) ◽  
pp. 6979-6993 ◽  
Author(s):  
J. H. Marsham ◽  
D. J. Parker ◽  
C. M. Grams ◽  
B. T. Johnson ◽  
W. M. F. Grey ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Climate Models ◽  
Vertical Mixing ◽  
Dust Transport ◽  
Uplift Rates ◽  
Weak Winds ◽  
Local Dust

Abstract. Observations of the Saharan boundary layer, made during the GERBILS field campaign, show that mesoscale land surface temperature variations (which were related to albedo variations) induced mesoscale circulations. With weak winds along the aircraft track, land surface temperature anomalies with scales of greater than 10 km are shown to significantly affect boundary-layer temperatures and winds. Such anomalies are expected to affect the vertical mixing of the dusty and weakly stratified Saharan Residual Layer (SRL). Mesoscale variations in winds are also shown to affect dust loadings in the boundary layer. Using the aircraft observations and data from the COSMO model, a region of local dust uplift, with strong along-track winds, was identified in one low-level flight. Large eddy model (LEM) simulations based on this location showed linearly organised boundary-layer convection. Calculating dust uplift rates from the LEM wind field showed that the boundary-layer convection increased uplift by approximately 30%, compared with the uplift rate calculated neglecting the convection. The modelled effects of boundary-layer convection on uplift are shown to be larger when the boundary-layer wind is decreased, and most significant when the mean wind is below the threshold for dust uplift and the boundary-layer convection leads to uplift which would not otherwise occur. Both the coupling of albedo features to the atmosphere on the mesoscale, and the enhancement of dust uplift by boundary-layer convection are unrepresented in many climate models, but may have significant impacts on the vertical transport and uplift of desert dust. Mesoscale effects in particular tend to be difficult to parametrise.

scholarly journals An evapotranspiration model self-calibrated from remotely sensed surface soil moisture, land surface temperature and vegetation cover fraction: application to disaggregated SMOS and MODIS data

2019 ◽  
Author(s):  
Bouchra Ait Hssaine ◽  
Olivier Merlin ◽  
Jamal Ezzahar ◽  
Nitu Ojha ◽  
Salah Er-raki ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Energy Balance ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Vegetation Cover ◽  
Land Surface ◽  
Surface Soil ◽  
Surface Soil Moisture ◽  
Wide Range ◽  
The Mean

Abstract. Thermal-based two-source energy balance modeling is very useful for estimating the land evapotranspiration (ET) at a wide range of spatial and temporal scales. However, the land surface temperature (LST) is not sufficient for constraining simultaneously both soil and vegetation flux components in such a way that assumptions (on either the soil or the vegetation fluxes) are commonly required. To avoid such assumptions, a new energy balance model (TSEB-SM) was recently developed in Ait Hssaine et al. (2018a) to integrate the microwave-derived near-surface soil moisture (SM), in addition to the thermal-derived LST and vegetation cover fraction (fc). Whereas, TSEB-SM has been recently tested using in-situ measurements, the objective of this paper is to evaluate the performance of TSEB-SM in real-life using 1 km resolution MODIS (Moderate resolution imaging spectroradiometer) LST and fc data and the 1 km resolution SM data disaggregated from SMOS (Soil Moisture and Ocean Salinity) observations by using DisPATCh. The approach is applied during a four-year period (2014–2018) over a rainfed wheat field in the Tensift basin, central Morocco, during a four-year period (2014–2018). The field was seeded for the 2014–2015 (S1), 2016–2017 (S2) and 2017–2018 (S3) agricultural season, while it was not ploughed (remained as bare soil) during the 2015–2016 (B1) agricultural season. The mean retrieved values of (arss, brss) calculated for the entire study period using satellite data are (7.32, 4.58). The daily calibrated αPT ranges between 0 and 1.38 for both S1 and S2. Its temporal variability is mainly attributed to the rainfall distribution along the agricultural season. For S3, the daily retrieved αPT remains at a mostly constant value (∼ 0.7) throughout the study period, because of the lack of clear sky disaggregated SM and LST observations during this season. Compared to eddy covariance measurements, TSEB driven only by LST and fc data significantly overestimates latent heat fluxes for the four seasons. The overall mean bias values are 119, 94, 128 and 181 W/m2 for S1, S2, S3 and B1 respectively. In contrast, these errors are much reduced when using TSEB-SM (SM and LST combined data) with the mean bias values estimated as 39, 4, 7 and 62 W/m2 for S1, S2, S3 and B1 respectively.

scholarly journals Comparison of Land Surface Temperature During and Before the Emergence of Covid-19 using Modis Imagery in Wuhan City, China

2020 ◽  
Vol 34 (1) ◽  
Author(s):  
Hamim Zaky Hadibasyir ◽  
Seftiawan Samsu Rijal ◽  
Dewi Ratna Sari
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Anthropogenic Activities ◽  
Temporal Analysis ◽  
The Past ◽  
Modis Imagery ◽  
Rapid Transmission ◽  
The Mean ◽  
Spatio Temporal

Coronavirus disease (COVID-19) was firstly identified in Wuhan, China. By 23rd January 2020, China’s Government made a decision to execute lockdown policy in Wuhan due to the rapid transmission of COVID-19. It is essential to investigate the land surface temperature (LST) dynamics due to changes in level of anthropogenic activities. Therefore, this study aims (1) to investigate mean LST differences between during, i.e., December 2019 to early March 2020, and before the emergence of COVID-19 in Wuhan; (2) to conduct spatio-temporal analysis of mean LST with regards to lockdown policy; and (3) to examine mean LST differences for each land cover type. MODIS data consist of MOD11A2 and MCD12Q1 were employed. The results showed that during the emergence of COVID-19 with lockdown policy applied, the mean LST was lower than the mean LST of the past three years on the same dates. Whereas, during the emergence of COVID-19 without lockdown policy applied, the mean LST was relatively higher than the mean LST of the past three years. In addition, the mean LST of built-up areas experienced the most significant differences between during the emergence of COVID-19 with lockdown policy applied in comparison to the average of the past three years.

scholarly journals An Evaluation of Modeled Evaporation Regimes in Europe Using Observed Dry Spell Land Surface Temperature

2017 ◽  
Vol 18 (5) ◽  
pp. 1453-1470 ◽  
Author(s):  
Phil P. Harris ◽  
Sonja S. Folwell ◽  
Belen Gallego-Elvira ◽  
José Rodríguez ◽  
Sean Milton ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Climate Models ◽  
Bare Soil ◽  
Surface Model ◽  
Continental Scale ◽  
Dry Spells ◽  
Dry Spell

Abstract Soil moisture availability exerts control over the land surface energy partition in parts of Europe. However, determining the strength and variability of this control is impeded by the lack of reliable evaporation observations at the continental scale. This makes it difficult to refine the broad range of soil moisture–evaporation behaviors across global climate models (GCMs). Previous studies show that satellite observations of land surface temperature (LST) during rain-free dry spells can be used to diagnose evaporation regimes at the GCM gridbox scale. This relative warming rate (RWR) diagnostic quantifies the increase in dry spell LST relative to air temperature and is used here to evaluate a land surface model (JULES) both offline and coupled to a GCM (HadGEM3-A). It is shown that RWR can be calculated using outputs from an atmospheric GCM provided the satellite clear-sky sampling bias is incorporated. Both offline JULES and HadGEM3-A reproduce the observed seasonal and regional RWR variations, but with weak springtime RWRs in central Europe. This coincides with sustained bare soil evaporation (Ebs) during dry spells, reflecting previous site-level JULES studies in Europe. To assess whether RWR can discriminate between surface descriptions, the bare soil surface conductance and the vegetation root profile are revised to limit Ebs. This increases RWR by increasing the occurrence of soil moisture–limited dry spells, yielding more realistic springtime RWRs as a function of antecedent precipitation but poorer relationships in summer. This study demonstrates the potential for using satellite LST to assess evaporation regimes in climate models.

scholarly journals Simulation of land surface temperatures: comparison of two climate models and satellite retrievals

2009 ◽  
Vol 2 (1) ◽  
pp. 309-340
Author(s):  
J. M. Edwards
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Diurnal Cycle ◽  
Land Surface ◽  
General Circulation ◽  
Climate Models ◽  
Surface Flux ◽  
Spatial Coverage ◽  
Diurnal Range ◽  
Satellite Retrievals

Abstract. Recently there has been significant progress in the retrieval of land surface temperature from satellite observations. Satellite retrievals of surface temperature offer several advantages, including broad spatial coverage, and such data are potentially of great value in assessing general circulation models of the atmosphere. Here, retrievals of the land surface temperature over the contiguous United States are compared with simulations from two climate models. The models generally simulate the diurnal range realistically, but show significant warm biases during the summer. The models' diurnal cycle of surface temperature is related to their surface flux budgets. Differences in the diurnal cycle of the surface flux budget between the models are found to be more pronounced than those in the diurnal cycle of surface temperature.

scholarly journals Influence of Land Use and Land Cover Change on Land surface temperature

2021 ◽  
Vol 283 ◽  
pp. 01038
Author(s):  
Jing Sun ◽  
Jing He
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Expansion ◽  
Rapid Urbanization ◽  
Lulc Changes ◽  
The Mean ◽  
The Relationship

The rapid urbanization process has recently led to significant land use and land cover (LULC) changes, thereby affecting the climate and the environment. The purpose of this study is to analyze the LULC changes in Hefei City, Anhui Province, and their relationship with land surface temperature (LST). To achieve this goal, multitemporal Landsat data were used to monitor the LULC and LST between 2005 and 2015. The study also used correlation analysis to analyze the relationship between LST, LULC, and other spectral indices (NDVI, NDBI, and NDWI). The results show that the built-up land has expanded significantly, transforming from 488.26 km2 in 2005 to 575.64 km2 in 2015. It further shows that the mean LST in Hefei city has increased from 284.0 K in 2005 to 285.86 K in 2015. The results also indicate that there is a positive correlation between LST and NDVI and NDBI, while there is a negative correlation between LST and NDWI. This means that urban expansion and reduced water bodies will lead to an increase in LST.

scholarly journals Spatiotemporal Impacts of Urban Land Use/Land Cover Changes on Land Surface Temperature: A Comparative Study of Damascus and Aleppo (Syria)

Atmosphere ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 1037
Author(s):  
Mohamed Ali Mohamed
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Vegetation Cover ◽  
Land Surface ◽  
Land Use Land Cover ◽  
Lulc Changes ◽  
Increasing Trend ◽  
The Mean

Monitoring the impact of changes in land use/land cover (LULC) and land surface temperature (LST) is of great importance in environmental and urban studies. In this context, this study aimed to analyze the dynamics of LULC and its impact on the spatiotemporal variation of the LST in the two largest urban cities in Syria, Damascus, and Aleppo. To achieve this, LULC changes, normalized difference vegetation index (NDVI), and LST were calculated from multi-temporal Landsat data for the period 2010 to 2018. The study revealed significant changes in LULC, which were represented by a decrease in agricultural land and green areas and an increase in bare areas in both cities. In addition, built-up areas decreased in Aleppo and increased in Damascus during the study period. The temporal and spatial variation of the LST and its distribution pattern was closely related to the effect of changes in LULC as well as to land use conditions in each city. This effect was greater in Aleppo than in Damascus, where Aleppo recorded a higher increase in the mean LST, by about 2 °C, than in Damascus, where it was associated with greater degradation and loss of vegetation cover. In general, there was an increasing trend in the minimum and maximum LST as well as an increasing trend in the mean LST in both cities. The negative linear relationship between LST and NDVI confirms that vegetation cover can help reduce LST in both cities. This study can draw the attention of relevant departments to pay more attention to mitigating the negative impact of LULC changes in order to limit the increase in LST.

scholarly journals Extents of Predictors for Land Surface Temperature Using Multiple Regression Model

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
R. M. Yuvaraj
Keyword(s):  
Surface Temperature ◽  
Regression Model ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Areas ◽  
Climate Models ◽  
Multiple Linear Regression Model ◽  
Multiple Regression Model ◽  
Landsat 8 ◽  
Study Region

Land surface temperature (LST) is a key factor in numerous areas such as climate change, land use/land cover in the urban areas, and heat balance and is also a significant participant in the creation of climate models. Landsat data has given numerous possibilities to understand the land processes by means of remote sensing. The present study has been performed to identify the LST of the study region using Landsat 8 OLI/TIRS satellite images for two time periods in order to compare the data. The study also attempted to identify and predict the role and importance of NDVI, NDBI, and the slope of the region on LST. The study concludes that the maximum and minimum temperatures of 40.44 C and 20.78 C were recorded during the November month whereas the maximum and minimum LST for month March has increased to 42.44 C and 24.57 C respectively. The result indicates that LST is inversely proportional to NDVI (−6.369) and slope (−0.077) whereas LST is directly proportional to NDBI (+14.74). Multiple linear regression model has been applied to calculate the extents of NDVI, NDBI, and slope on the LST. It concludes that the increase in vegetation and slope would result in slight decrease in temperature whereas the increase in built-up will result in a huge increase in temperature.

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