Airborne lidar measurements of ozone, water vapor, and aerosols in large-scale atmospheric studies

2002 ◽  
Author(s):  
E.V. Browell
Keyword(s):  
Water Vapor ◽  
Large Scale ◽  
Airborne Lidar ◽  
Lidar Measurements

scholarly journals Monitoring tropical forest carbon stocks and emissions using Planet satellite data

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Ovidiu Csillik ◽  
Pramukta Kumar ◽  
Joseph Mascaro ◽  
Tara O’Shea ◽  
Gregory P. Asner
Keyword(s):  
Climate Change ◽  
Large Scale ◽  
Cost Effective ◽  
Carbon Stocks ◽  
Airborne Lidar ◽  
Aboveground Carbon ◽  
Lidar Measurements ◽  
High Resolution Map ◽  
Aboveground Carbon Density ◽  
Planet Satellite

AbstractTropical forests are crucial for mitigating climate change, but many forests continue to be driven from carbon sinks to sources through human activities. To support more sustainable forest uses, we need to measure and monitor carbon stocks and emissions at high spatial and temporal resolution. We developed the first large-scale very high-resolution map of aboveground carbon stocks and emissions for the country of Peru by combining 6.7 million hectares of airborne LiDAR measurements of top-of-canopy height with thousands of Planet Dove satellite images into a random forest machine learning regression workflow, obtaining an R2 of 0.70 and RMSE of 25.38 Mg C ha−1 for the nationwide estimation of aboveground carbon density (ACD). The diverse ecosystems of Peru harbor 6.928 Pg C, of which only 2.9 Pg C are found in protected areas or their buffers. We found significant carbon emissions between 2012 and 2017 in areas aggressively affected by oil palm and cacao plantations, agricultural and urban expansions or illegal gold mining. Creating such a cost-effective and spatially explicit indicators of aboveground carbon stocks and emissions for tropical countries will serve as a transformative tool to quantify the climate change mitigation services that forests provide.

scholarly journals Classifying stages of cirrus life-cycle evolution

2018 ◽  
Vol 176 ◽  
pp. 05021
Author(s):  
Benedikt Urbanek ◽  
Silke Groß ◽  
Andreas Schäfler ◽  
Martin Wirth
Keyword(s):  
Life Cycle ◽  
Water Vapor ◽  
Relative Humidity ◽  
Classification Scheme ◽  
Airborne Lidar ◽  
Temperature Fields ◽  
Lidar Measurements ◽  
Life Cycle Evolution ◽  
Ice Sublimation ◽  
Model Temperature

Airborne lidar backscatter data is used to determine in- and out-of-cloud regions. Lidar measurements of water vapor together with model temperature fields are used to calculate relative humidity over ice (RHi). Based on temperature and RHi we identify different stages of cirrus evolution: homogeneous and heterogeneous freezing, depositional growth, ice sublimation and sedimentation. We will present our classification scheme and first applications on mid-latitude cirrus clouds.

Lidar observations of a mesoscale moisture transport event impacting convection and comparison to Rapid Refresh model analysis

2020 ◽  
Author(s):  
Brian J. Carroll ◽  
Belay B. Demoz ◽  
David D. Turner ◽  
Ruben Delgado
Keyword(s):  
Boundary Layer ◽  
Water Vapor ◽  
Great Plains ◽  
Large Scale ◽  
Spatial Scales ◽  
Airborne Lidar ◽  
Water Vapor Transport ◽  
Analysis Model ◽  
Vapor Flux ◽  
Lidar Observations

AbstractThe 2015 Plains Elevated Convection at Night (PECAN) field campaign provided a wealth of intensive observations for improving understanding of interplay between the Great Plains low-level jet (LLJ), mesoscale convective systems (MCSs), and other phenomena in the nocturnal boundary layer. This case study utilizes PECAN ground-based Doppler and water vapor lidar and airborne water vapor lidar observations for a detailed examination of water vapor transport in the Great Plains. The chosen case, 11 July 2015, featured a strong LLJ that helped sustain an MCS overnight. The lidars resolved boundary layer moisture being transported northward, leading to a large increase in water vapor in the lowest several hundred meters above the surface in northern Kansas. A branch of nocturnal convection initiated coincident with the observed maximum water vapor flux. Radiosondes confirmed an increase in convective potential within the LLJ layer. Moist static energy (MSE) growth was generated by increasing moisture in spite of a temperature decrease in the LLJ layer. This unique dataset is also used to evaluate the Rapid Refresh (RAP) analysis model performance, comparing model output against the continuous lidar profiles of water vapor and wind. While the RAP analysis captured the large-scale trends, errors in water vapor mixing ratio were found ranging 0 to 2 g/kg at the ground-based lidar sites. Comparison with the airborne lidar throughout the PECAN domain yielded a RMSE of 1.14 g/kg in the planetary boundary layer. These errors mostly manifested as contiguous dry or wet regions spanning spatial scales of O(10s-100s km).

Deep Learning-Based Classification of Large-Scale Airborne LiDAR Point Cloud

2021 ◽  
pp. 1-15
Author(s):  
Mathieu Turgeon-Pelchat ◽  
Samuel Foucher ◽  
Yacine Bouroubi
Keyword(s):  
Deep Learning ◽  
Point Cloud ◽  
Large Scale ◽  
Airborne Lidar

scholarly journals Extreme Floods in the Eastern Part of Europe: Large-Scale Drivers and Associated Impacts

Water ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1122
Author(s):  
Monica Ionita ◽  
Viorica Nagavciuc
Keyword(s):  
Water Vapor ◽  
Heavy Rainfall ◽  
Large Scale ◽  
Vapor Transport ◽  
Water Vapor Transport ◽  
Flood Events ◽  
Rainfall Events ◽  
Catchment Areas ◽  
Large Scale Atmospheric Circulation ◽  
Heavy Rainfall Events

The role of the large-scale atmospheric circulation in producing heavy rainfall events and floods in the eastern part of Europe, with a special focus on the Siret and Prut catchment areas (Romania), is analyzed in this study. Moreover, a detailed analysis of the socio-economic impacts of the most extreme flood events (e.g., July 2008, June–July 2010, and June 2020) is given. Analysis of the largest flood events indicates that the flood peaks have been preceded up to 6 days in advance by intrusions of high Potential Vorticity (PV) anomalies toward the southeastern part of Europe, persistent cut-off lows over the analyzed region, and increased water vapor transport over the catchment areas of Siret and Prut Rivers. The vertically integrated water vapor transport prior to the flood peak exceeds 300 kg m−1 s−1, leading to heavy rainfall events. We also show that the implementation of the Flood Management Plan in Romania had positive results during the 2020 flood event compared with the other flood events, when the authorities took several precaution measurements that mitigated in a better way the socio-economic impact and risks of the flood event. The results presented in this study offer new insights regarding the importance of large-scale atmospheric circulation and water vapor transport as drivers of extreme flooding in the eastern part of Europe and could lead to a better flood forecast and flood risk management.

Simultaneous lidar measurements of wind, temperature, water vapor, and nonsphericity of aerosol in the troposphere

2001 ◽  
Author(s):  
Makoto Abo ◽  
Chikao Nagasawa ◽  
Yasukuni Shibata ◽  
Masahiro Funada
Keyword(s):  
Water Vapor ◽  
Lidar Measurements ◽  
Temperature Water

scholarly journals Application and Validation of a Model for Terrain Slope Estimation Using Space-Borne LiDAR Waveform Data

2018 ◽  
Vol 10 (11) ◽  
pp. 1691 ◽  
Author(s):  
Xuebo Yang ◽  
Cheng Wang ◽  
Sheng Nie ◽  
Xiaohuan Xi ◽  
Zhenyue Hu ◽  
...  
Keyword(s):  
Surface Characteristics ◽  
Airborne Lidar ◽  
Estimation Accuracy ◽  
Estimation Model ◽  
Large Area ◽  
Waveform Data ◽  
Terrain Slope ◽  
Lidar Measurements ◽  
Slope Estimation ◽  
Study Sites

The terrain slope is one of the most important surface characteristics for quantifying the Earth surface processes. Space-borne LiDAR sensors have produced high-accuracy and large-area terrain measurement within the footprint. However, rigorous procedures are required to accurately estimate the terrain slope especially within the large footprint since the estimated slope is likely affected by footprint size, shape, orientation, and terrain aspect. Therefore, based on multiple available datasets, we explored the performance of a proposed terrain slope estimation model over several study sites and various footprint shapes. The terrain slopes were derived from the ICESAT/GLAS waveform data by the proposed method and five other methods in this study. Compared with five other methods, the proposed method considered the influence of footprint shape, orientation, and terrain aspect on the terrain slope estimation. Validation against the airborne LiDAR measurements showed that the proposed method performed better than five other methods (R2 = 0.829, increased by ~0.07, RMSE = 3.596°, reduced by ~0.6°, n = 858). In addition, more statistics indicated that the proposed method significantly improved the terrain slope estimation accuracy in high-relief region (RMSE = 5.180°, reduced by ~1.8°, n = 218) or in the footprint with a great eccentricity (RMSE = 3.421°, reduced by ~1.1°, n = 313). Therefore, from these experiments, we concluded that this terrain slope estimation approach was beneficial for different terrains and various footprint shapes in practice and the improvement of estimated accuracy was distinctly related with the terrain slope and footprint eccentricity.

scholarly journals Modelling above-ground carbon dynamics using multi-temporal airborne lidar: insights from a Mediterranean woodland

2016 ◽  
Vol 13 (4) ◽  
pp. 961-973 ◽  
Author(s):  
W. Simonson ◽  
P. Ruiz-Benito ◽  
F. Valladares ◽  
D. Coomes
Keyword(s):  
Climate Change ◽  
Large Scale ◽  
Critical Role ◽  
Carbon Fluxes ◽  
Carbon Dynamics ◽  
Airborne Lidar ◽  
Lidar Data ◽  
Low Carbon ◽  
Data Set ◽  
Multi Temporal

Abstract. Woodlands represent highly significant carbon sinks globally, though could lose this function under future climatic change. Effective large-scale monitoring of these woodlands has a critical role to play in mitigating for, and adapting to, climate change. Mediterranean woodlands have low carbon densities, but represent important global carbon stocks due to their extensiveness and are particularly vulnerable because the region is predicted to become much hotter and drier over the coming century. Airborne lidar is already recognized as an excellent approach for high-fidelity carbon mapping, but few studies have used multi-temporal lidar surveys to measure carbon fluxes in forests and none have worked with Mediterranean woodlands. We use a multi-temporal (5-year interval) airborne lidar data set for a region of central Spain to estimate above-ground biomass (AGB) and carbon dynamics in typical mixed broadleaved and/or coniferous Mediterranean woodlands. Field calibration of the lidar data enabled the generation of grid-based maps of AGB for 2006 and 2011, and the resulting AGB change was estimated. There was a close agreement between the lidar-based AGB growth estimate (1.22 Mg ha−1 yr−1) and those derived from two independent sources: the Spanish National Forest Inventory, and a tree-ring based analysis (1.19 and 1.13 Mg ha−1 yr−1, respectively). We parameterised a simple simulator of forest dynamics using the lidar carbon flux measurements, and used it to explore four scenarios of fire occurrence. Under undisturbed conditions (no fire) an accelerating accumulation of biomass and carbon is evident over the next 100 years with an average carbon sequestration rate of 1.95 Mg C ha−1 yr−1. This rate reduces by almost a third when fire probability is increased to 0.01 (fire return rate of 100 years), as has been predicted under climate change. Our work shows the power of multi-temporal lidar surveying to map woodland carbon fluxes and provide parameters for carbon dynamics models. Space deployment of lidar instruments in the near future could open the way for rolling out wide-scale forest carbon stock monitoring to inform management and governance responses to future environmental change.

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