scholarly journals Application of Tropospheric Sulfate Aerosol Emissions to Mitigate Meteorological Phenomena with Extremely High Daily Temperatures

2019 ◽  
Vol 23 (1) ◽  
pp. 14-40 ◽  
Author(s):  
Gabriela C. Mulena ◽  
Salvador E. Puliafito ◽  
Susan G. Lakkis
Keyword(s):  
Surface Temperature ◽  
Regional Scale ◽  
High Rate ◽  
Shortwave Radiation ◽  
Design Parameters ◽  
Practical Implementation ◽  
Aerosol Layer ◽  
Mesoscale Meteorology ◽  
Wave Event ◽  
Aerosol Emissions

Abstract This research examined whether tropospheric sulfate ion aerosols (SO42−) might be applied at a regional scale to mitigate meteorological phenomena with extremely high daily temperatures. The specific objectives of this work were: 1) to model the behaviour of SO42−aerosols in the troposphere and their influence on surface temperature and incident solar radiation, at a regional scale, using an appropriate online coupled mesoscale meteorology and chemistry model; 2) to determine the main engineering design parameters using tropospheric SO42−aerosols in order to artificially reduce the temperature and incoming radiation at surface during events of extremely high daily temperatures, and 3) to evaluate a preliminary technical proposal for the injection of regionally engineered tropospheric SO42−aerosols based on the integral anti-hail system of the Province of Mendoza. In order to accomplish these objectives, we used the Weather Research & Forecasting Model coupled with Chemistry (WRF/Chem) to model and evaluate the behaviour of tropospheric SO42−over the Province of Mendoza (Argentina) (PMA) on a clear sky day during a heat wave event occurred in January 2012. In addition, using WRF/Chem, we evaluated the potential reductions on surface temperature and incident shortwave radiation around the metropolitan area of Great Mendoza, PMA, based on an artificially designed aerosol layer and on observed meteorological parameters. The results demonstrated the ability of WRF/Chem to represent the behaviour of tropospheric SO42− aerosols at a regional scale and suggested that the inclusion of these aerosols in the atmosphere causes changes in the surface energy balance and, therefore, in the surface temperature and the regional atmospheric circulation. However, it became evident that, given the high rate of injection and the large amount of mass required for its practical implementation by means of the technology currently used by the anti-hail program, it is inefficient and energetically costly.

scholarly journals Improving the Evapotranspiration Estimation under Cloudy Condition by Extending the Ts-VI Triangle Model

2021 ◽  
Vol 13 (8) ◽  
pp. 1516
Author(s):  
Boyang Li ◽  
Yaokui Cui ◽  
Xiaozhuang Geng ◽  
Huan Li
Keyword(s):  
Remote Sensing ◽  
Surface Temperature ◽  
Land Surface ◽  
Energy Exchange ◽  
Vegetation Index ◽  
Regional Scale ◽  
Reconstruction Algorithm ◽  
Heihe River ◽  
Main Process ◽  
In Situ Data

Evapotranspiration (ET) of soil-vegetation system is the main process of the water and energy exchange between the atmosphere and the land surface. Spatio-temporal continuous ET is vitally important to agriculture and ecological applications. Surface temperature and vegetation index (Ts-VI) triangle ET model based on remote sensing land surface temperature (LST) is widely used to monitor the land surface ET. However, a large number of missing data caused by the presence of clouds always reduces the availability of the main parameter LST, thus making the remote sensing-based ET estimation unavailable. In this paper, a method to improve the availability of ET estimates from Ts-VI model is proposed. Firstly, continuous LST product of the time series is obtained using a reconstruction algorithm, and then, the reconstructed LST is applied to the estimate ET using the Ts-VI model. The validation in the Heihe River Basin from 2009 to 2011 showed that the availability of ET estimates is improved from 25 days per year (d/yr) to 141 d/yr. Compared with the in situ data, a very good performance of the estimated ET is found with RMSE 1.23 mm/day and R2 0.6257 at point scale and RMSE 0.32 mm/day and R2 0.8556 at regional scale. This will improve the understanding of the water and energy exchange between the atmosphere and the land surface, especially under cloudy conditions.

scholarly journals Optimization of the Local Split-Window Algorithm for FY-4A Land Surface Temperature Retrieval

2019 ◽  
Vol 11 (17) ◽  
pp. 2016
Author(s):  
Lijuan Wang ◽  
Ni Guo ◽  
Wei Wang ◽  
Hongchao Zuo
Keyword(s):  
Surface Temperature ◽  
Diurnal Variation ◽  
Land Surface Temperature ◽  
Satellite Data ◽  
Land Surface ◽  
Regional Scale ◽  
Pso Algorithm ◽  
Variation Characteristics ◽  
Split Window Algorithm ◽  
Mean Square Errors

FY-4A is a second generation of geostationary orbiting meteorological satellite, and the successful launch of FY-4A satellite provides a new opportunity to obtain diurnal variation of land surface temperature (LST). In this paper, different underlying surfaces-observed data were applied to evaluate the applicability of the local split-window algorithm for FY-4A, and the local split-window algorithm parameters were optimized by the artificial intelligent particle swarm optimization (PSO) algorithm to improve the accuracy of retrieved LST. Results show that the retrieved LST can efficiently reproduce the diurnal variation characteristics of LST. However, the estimated values deviate hugely from the observed values when the local split-window algorithms are directly used to process the FY-4A satellite data, and the root mean square errors (RMSEs) are approximately 6K. The accuracy of the retrieved LST cannot be effectively improved by merely modifying the emissivity-estimated model or optimizing the algorithm. Based on the measured emissivity, the RMSE of LST retrieved by the optimized local split-window algorithm is reduced to 3.45 K. The local split-window algorithm is a simple and easy retrieval approach that can quickly retrieve LST on a regional scale and promote the application of FY-4A satellite data in related fields.

scholarly journals Shallow groundwater effect on land surface temperature and surface energy balance under bare soil conditions: modeling and description

2012 ◽  
Vol 16 (7) ◽  
pp. 1817-1831 ◽  
Author(s):  
F. Alkhaier ◽  
G. N. Flerchinger ◽  
Z. Su
Keyword(s):  
Energy Balance ◽  
Surface Temperature ◽  
Land Surface ◽  
Shallow Groundwater ◽  
Bare Soil ◽  
Heat Fluxes ◽  
Shortwave Radiation ◽  
Soil Conditions ◽  
Potential Evaporation ◽  
Available Energy

Abstract. Understanding when and how groundwater affects surface temperature and energy fluxes is significant for utilizing remote sensing in groundwater studies and for integrating aquifers within land surface models. To investigate the shallow groundwater effect under bare soil conditions, we numerically exposed two soil profiles to identical metrological forcing. One of the profiles had shallow groundwater. The different responses that the two profiles manifested were inspected regarding soil moisture, temperature and energy balance at the land surface. The findings showed that the two profiles differed in three aspects: the absorbed and emitted amounts of energy, the portioning out of the available energy and the heat fluency in the soil. We concluded that due to their lower albedo, shallow groundwater areas reflect less shortwave radiation and consequently get a higher magnitude of net radiation. When potential evaporation demand is sufficiently high, a large portion of the energy received by these areas is consumed for evaporation. This increases the latent heat flux and reduces the energy that could have heated the soil. Consequently, lower magnitudes of both sensible and ground heat fluxes are caused to occur. The higher soil thermal conductivity in shallow groundwater areas facilitates heat transfer between the top soil and the subsurface, i.e. soil subsurface is more thermally connected to the atmosphere. For the reliability of remote sensors in detecting shallow groundwater effect, it was concluded that this effect can be sufficiently clear to be detected if at least one of the following conditions occurs: high potential evaporation and high contrast between day and night temperatures. Under these conditions, most day and night hours are suitable for shallow groundwater depth detection.

scholarly journals Bias in CMIP6 models as compared to observed regional dimming and brightening

2020 ◽  
Vol 20 (24) ◽  
pp. 16023-16040
Author(s):  
Kine Onsum Moseid ◽  
Michael Schulz ◽  
Trude Storelvmo ◽  
Ingeborg Rian Julsrud ◽  
Dirk Olivié ◽  
...  
Keyword(s):  
Sulfur Dioxide ◽  
Surface Energy ◽  
Coupled Model ◽  
Shortwave Radiation ◽  
Anthropogenic Aerosol ◽  
Surface Energy Fluxes ◽  
Aerosol Emission ◽  
Wrong Reason ◽  
The Right ◽  
Aerosol Emissions

Abstract. Anthropogenic aerosol emissions have increased considerably over the last century, but climate effects and quantification of the emissions are highly uncertain as one goes back in time. This uncertainty is partly due to a lack of observations in the pre-satellite era, making the observations we do have before 1990 additionally valuable. Aerosols suspended in the atmosphere scatter and absorb incoming solar radiation and thereby alter the Earth's surface energy balance. Previous studies show that Earth system models (ESMs) do not adequately represent surface energy fluxes over the historical era. We investigated global and regional aerosol effects over the time period 1961–2014 by looking at surface downwelling shortwave radiation (SDSR). We used observations from ground stations as well as multiple experiments from eight ESMs participating in the Coupled Model Intercomparison Project Version 6 (CMIP6). Our results show that this subset of models reproduces the observed transient SDSR well in Europe but poorly in China. We suggest that this may be attributed to missing emissions of sulfur dioxide in China, sulfur dioxide being a precursor to sulfate, which is a highly reflective aerosol and responsible for more reflective clouds. The emissions of sulfur dioxide used in the models do not show a temporal pattern that could explain observed SDSR evolution over China. The results from various aerosol emission perturbation experiments from DAMIP, RFMIP and AerChemMIP show that only simulations containing anthropogenic aerosol emissions show dimming, even if the dimming is underestimated. Simulated clear-sky and all-sky SDSR do not differ greatly, suggesting that cloud cover changes are not a dominant cause of the biased SDSR evolution in the simulations. Therefore we suggest that the discrepancy between modeled and observed SDSR evolution is partly caused by erroneous aerosol and aerosol precursor emission inventories. This is an important finding as it may help interpret whether ESMs reproduce the historical climate evolution for the right or wrong reason.

scholarly journals Correction of systematic model forcing bias of CLM using assimilation of cosmic-ray Neutrons and land surface temperature: a study in the Heihe Catchment, China

2015 ◽  
Vol 19 (1) ◽  
pp. 615-629 ◽  
Author(s):  
X. Han ◽  
H.-J. H. Franssen ◽  
R. Rosolem ◽  
R. Jin ◽  
X. Li ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Regional Scale ◽  
Cosmic Ray ◽  
Systematic Bias ◽  
Area Index ◽  
Community Land Model ◽  
Independent Field

Abstract. The recent development of the non-invasive cosmic-ray soil moisture sensing technique fills the gap between point-scale soil moisture measurements and regional-scale soil moisture measurements by remote sensing. A cosmic-ray probe measures soil moisture for a footprint with a diameter of ~ 600 m (at sea level) and with an effective measurement depth between 12 and 76 cm, depending on the soil humidity. In this study, it was tested whether neutron counts also allow correcting for a systematic error in the model forcings. A lack of water management data often causes systematic input errors to land surface models. Here, the assimilation procedure was tested for an irrigated corn field (Heihe Watershed Allied Telemetry Experimental Research – HiWATER, 2012) where no irrigation data were available as model input although for the area a significant amount of water was irrigated. In the study, the measured cosmic-ray neutron counts and Moderate-Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) products were jointly assimilated into the Community Land Model (CLM) with the local ensemble transform Kalman filter. Different data assimilation scenarios were evaluated, with assimilation of LST and/or cosmic-ray neutron counts, and possibly parameter estimation of leaf area index (LAI). The results show that the direct assimilation of cosmic-ray neutron counts can improve the soil moisture and evapotranspiration (ET) estimation significantly, correcting for lack of information on irrigation amounts. The joint assimilation of neutron counts and LST could improve further the ET estimation, but the information content of neutron counts exceeded the one of LST. Additional improvement was achieved by calibrating LAI, which after calibration was also closer to independent field measurements. It was concluded that assimilation of neutron counts was useful for ET and soil moisture estimation even if the model has a systematic bias like neglecting irrigation. However, also the assimilation of LST helped to correct the systematic model bias introduced by neglecting irrigation and LST could be used to update soil moisture with state augmentation.

Dust Aerosol Optical Depth Retrieval over a Desert Surface Using the SEVIRI Window Channels

2009 ◽  
Vol 26 (4) ◽  
pp. 704-718 ◽  
Author(s):  
Bart De Paepe ◽  
Steven Dewitte
Keyword(s):  
Surface Temperature ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Surface Radiation ◽  
Retrieval Algorithm ◽  
Aerosol Layer ◽  
Surface Emissivity ◽  
Ir Radiation ◽  
Clear Sky ◽  
A Minor

Abstract The authors present a new algorithm to retrieve aerosol optical depth (AOD) over a desert using the window channels centered at 8.7, 10.8, and 12.0 μm of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument on board the Meteosat Second Generation satellite. The presence of dust aerosols impacts the longwave outgoing radiation, allowing the aerosols over the desert surfaces to be detected in the thermal infrared (IR) wavelengths. To retrieve the aerosol properties over land, the surface contribution to the satellite radiance measured at the top of the atmosphere has to be taken into account. The surface radiation depends on the surface temperature, which is characterized by a strong diurnal variation over the desert, and the surface emissivity, which is assumed to be constant over a time span of 24 h. The surface emissivity is based on clear-sky observations that are corrected for atmospheric absorption and emission. The clear-sky image is a composite of pixels that is characterized by the highest brightness temperature (BT) of the SEVIRI channel at 10.8 μm, and by a negative BT difference between the channels at 8.7 and 10.8 μm. Because of the lower temperatures of clouds and aerosols compared to clear-sky conditions, the authors assume that the selected pixel values are obtained for a clear-sky day. A forward model is used to simulate the thermal IR radiation transfer in the dust layer. The apparent surface radiation for the three window channels in the presence of aerosols is calculated as a function of the surface emissivity and the surface temperature, the aerosol layer temperature, and the AOD for different aerosol loadings. From these simulations two emissivity ratios, which are stored in lookup tables (LUT), are calculated. The retrieval algorithm consists of processing the clear-sky image and computing the surface emissivity, processing the instantaneous image, and computing the apparent surface radiation for the three window channels. The two emissivity ratios are computed using the radiances at 8.7 and 10.8 μm and at 8.7 and 12.0 μm, respectively. The SEVIRI AOD is obtained by the inversion of these emissivity ratios using the corresponding LUT. The algorithm is applied to a minor dust event over the Sahara between 19 and 22 June 2007. For the validation the SEVIRI AOD is compared with the AOD from the Cloud Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) along the satellite track.

scholarly journals Optimization of Noah and Noah_MP WRF Land Surface Schemes in Snow-Melting Conditions over Complex Terrain

2017 ◽  
Vol 145 (12) ◽  
pp. 4727-4745 ◽  
Author(s):  
Elena Tomasi ◽  
Lorenzo Giovannini ◽  
Dino Zardi ◽  
Massimiliano de Franceschi
Keyword(s):  
Surface Temperature ◽  
Land Surface ◽  
Winter Season ◽  
Wrf Model ◽  
Longwave Radiation ◽  
Shortwave Radiation ◽  
Land Use Classification ◽  
Near Surface ◽  
Thermal Inversion ◽  
Alpine Valley

The paper presents the results of high-resolution simulations performed with the WRF Model, coupled with two different land surface schemes, Noah and Noah_MP, with the aim of accurately reproducing winter season meteorological conditions in a typical Alpine valley. Accordingly, model results are compared against data collected during an intensive field campaign performed in the Adige Valley, in the eastern Italian Alps. In particular, the ability of the model in reproducing the time evolution of 2-m temperature and of incoming and outgoing shortwave and longwave radiation is examined. The validation of model results highlights that, in this context, WRF reproduces rather poorly near-surface temperature over snow-covered terrain, with an evident underestimation, during both daytime and nighttime. Furthermore it fails to capture specific atmospheric processes, such as the temporal evolution of the ground-based thermal inversion. The main cause of these errors lies in the miscalculation of the mean gridcell albedo, resulting in an inaccurate estimate of the reflected solar radiation calculated by both Noah and Noah_MP. Therefore, modifications to the initialization, to the land-use classification, and to both land surface models are performed to improve model results, by intervening in the calculation of the albedo, of the snow cover, and of the surface temperature. Qualitative and quantitative analyses show that, after these changes, a significant improvement in the comparability between model results and observations is achieved. In particular, outgoing shortwave radiation is lowered, 2-m temperature maxima increased accordingly, and ground-based thermal inversions are better captured.

Regional-scale surface temperature variability allows prediction of Pacific bluefin tuna recruitment

2018 ◽  
Vol 75 (4) ◽  
pp. 1341-1352 ◽  
Author(s):  
Barbara A Muhling ◽  
Desiree Tommasi ◽  
Seiji Ohshimo ◽  
Michael A Alexander ◽  
Gerard DiNardo
Keyword(s):  
Surface Temperature ◽  
Sea Of Japan ◽  
Environmental Variability ◽  
Regional Scale ◽  
Bluefin Tuna ◽  
Additive Models ◽  
The Sea Of Japan ◽  
Pacific Bluefin Tuna ◽  
Proactive Management ◽  
Late Fall

Abstract Future sustainable management of fisheries will require resilience to the effects of environmental variability and climate change on stock productivity. In this study, we examined relationships between sea surface temperature (SST) in the region between Taiwan and the Sea of Japan, and annual recruitment of Pacific bluefin tuna (Thunnus orientalis: PBF) over the past 35 years. Spatial correlation maps showed that warmer SSTs south of Shikoku, in the East China Sea and in the Sea of Japan from summer to late fall were associated with above average recruitment. SST anomalies near larval and juvenile habitats were most strongly correlated with local air temperatures. Generalized Additive Models predicting annual PBF recruitment from SST fields suggested that the influence of SST on recruitment was stronger than that of spawning stock biomass. Correlations between SST and recruitment likely reflect biological processes relevant to early juvenile habitat suitability. The influence of late fall SSTs could also be a result of varying availability of age-0 fish to the troll fishery; however, the relative importance of these processes was not clear. Despite these knowledge gaps, the strong predictive power of SST on PBF recruitment can allow more proactive management of this species under varying environmental conditions.

Sign in / Sign up

Export Citation Format

Share Document