scholarly journals Rapid remote sensing assessment of impacts from Hurricane Maria on forests of Puerto Rico

2018 ◽  
Author(s):  
Yanlei Feng ◽  
Robinson I Negron-Juarez ◽  
Christina M Patricola ◽  
William D Collins ◽  
Maria Uriarte ◽  
...  
Keyword(s):  
Puerto Rico ◽  
Tree Mortality ◽  
Climate Model ◽  
Spectral Response ◽  
Regional Climate ◽  
Google Earth ◽  
Slope Aspect ◽  
Landsat 8 ◽  
The Impact ◽  
Entire Island

Hurricane Maria made landfall as a strong Category 4 storm in southeast Puerto Rico on September 20th, 2018. The powerful storm traversed the island in a northwesterly direction causing widespread destruction. This study focused on a rapid assessment of Hurricane Maria’s impact to Puerto Rico’s forests. Calibrated and corrected Landsat 8 image composites for the entire island were generated using Google Earth Engine for a comparable pre-Maria and post-Maria time period that accounted for phenology. Spectral mixture analysis (SMA) using image-derived endmembers was carried out on both composites to calculate the change in the non-photosynthetic vegetation (ΔNPV) spectral response, a metric that quantifies the increased fraction of exposed wood and surface litter associated with tree mortality and crown damage from the storm. Hurricane simulations were also conducted using the Weather Research and Forecasting (WRF) regional climate model to estimate wind speeds associated with forest disturbance. Dramatic changes in forest structure across the entire island were evident from pre- and post-Maria composited Landsat 8 images. A ΔNPV map for only the forested pixels illustrated significant spatial variability in disturbance, with patterns that associated with factors such as slope, aspect and elevation. An initial order-of-magnitude impact estimate based on previous work indicated that Hurricane Maria may have caused mortality and severe damage to 23-31 million trees. Additional field work and image analyses are required to further detail the impact of Hurricane Maria to Puerto Rico forests.

scholarly journals Rapid remote sensing assessment of impacts from Hurricane Maria on forests of Puerto Rico

2018 ◽  
Author(s):  
Yanlei Feng ◽  
Robinson I Negron-Juarez ◽  
Christina M Patricola ◽  
William D Collins ◽  
Maria Uriarte ◽  
...  
Keyword(s):  
Puerto Rico ◽  
Tree Mortality ◽  
Climate Model ◽  
Spectral Response ◽  
Regional Climate ◽  
Google Earth ◽  
Slope Aspect ◽  
Landsat 8 ◽  
The Impact ◽  
Entire Island

Hurricane Maria made landfall as a strong Category 4 storm in southeast Puerto Rico on September 20th, 2018. The powerful storm traversed the island in a northwesterly direction causing widespread destruction. This study focused on a rapid assessment of Hurricane Maria’s impact to Puerto Rico’s forests. Calibrated and corrected Landsat 8 image composites for the entire island were generated using Google Earth Engine for a comparable pre-Maria and post-Maria time period that accounted for phenology. Spectral mixture analysis (SMA) using image-derived endmembers was carried out on both composites to calculate the change in the non-photosynthetic vegetation (ΔNPV) spectral response, a metric that quantifies the increased fraction of exposed wood and surface litter associated with tree mortality and crown damage from the storm. Hurricane simulations were also conducted using the Weather Research and Forecasting (WRF) regional climate model to estimate wind speeds associated with forest disturbance. Dramatic changes in forest structure across the entire island were evident from pre- and post-Maria composited Landsat 8 images. A ΔNPV map for only the forested pixels illustrated significant spatial variability in disturbance, with patterns that associated with factors such as slope, aspect and elevation. An initial order-of-magnitude impact estimate based on previous work indicated that Hurricane Maria may have caused mortality and severe damage to 23-31 million trees. Additional field work and image analyses are required to further detail the impact of Hurricane Maria to Puerto Rico forests.

scholarly journals Impact of updated radiative transfer scheme in RACMO2.3p3 on the surface mass and energy budget of the Greenland ice sheet

2020 ◽  
Author(s):  
Christiaan T. van Dalum ◽  
Willem Jan van de Berg ◽  
Michiel R. van den Broeke
Keyword(s):  
Radiative Transfer ◽  
Energy Budget ◽  
Climate Model ◽  
Regional Climate ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Snow Melt ◽  
Transfer Scheme ◽  
Surface Mass ◽  
The Impact

Abstract. This study evaluates the impact of a new snow and ice albedo and radiative transfer scheme on the surface mass and energy budget for the Greenland ice sheet in the latest version of the regional climate model RACMO2, version 2.3p3. We also evaluate the modeled (sub)surface temperature and snow melt, as subsurface heating by radiation penetration now occurs. The results are compared to the previous model version and are evaluated against stake measurements and automatic weather station data of the K-transect and PROMICE projects. In addition, subsurface snow temperature profiles are compared at the K-transect, Summit and southeast Greenland. The surface mass balance is in good agreement with observations, and only changes considerably with respect to the previous RACMO2 version around the ice margins and in the percolation zone. Snow melt and refreezing, on the other hand, are changed more substantially in various regions due to the changed albedo representation, subsurface energy absorption and melt water percolation. Internal heating leads to considerably higher snow temperatures in summer, in agreement with observations, and introduces a shallow layer of subsurface melt.

scholarly journals PARASO, a circum-Antarctic fully-coupled ice-sheet - ocean - sea-ice - atmosphere - land model involving f.ETISh1.7, NEMO3.6, LIM3.6, COSMO5.0 and CLM4.5

2021 ◽  
Author(s):  
Charles Pelletier ◽  
Thierry Fichefet ◽  
Hugues Goosse ◽  
Konstanze Haubner ◽  
Samuel Helsen ◽  
...  
Keyword(s):  
Sea Ice ◽  
Climate Model ◽  
Regional Climate ◽  
Ice Sheet ◽  
Horizontal Resolution ◽  
Fine Tuning ◽  
Polar Regions ◽  
Surface Mass ◽  
The Impact ◽  
Fully Coupled

Abstract. We introduce PARASO, a novel five-component fully-coupled regional climate model over an Antarctic circumpolar domain covering the full Southern Ocean. The state-of-the-art models used are f.ETISh1.7 (ice sheet), NEMO3.6 (ocean), LIM3.6 (sea ice), COSMO5.0 (atmosphere) and CLM4.5 (land), which are here run at an horizontal resolution close to 1/4°. One key-feature of this tool resides in a novel two-way coupling interface for representing ocean – ice-sheet interactions, through explicitly resolved ice-shelf cavities. The impact of atmospheric processes on the Antarctic ice sheet is also conveyed through computed COSMO-CLM – f.ETISh surface mass exchanges. In this technical paper, we briefly introduce each model's configuration and document the developments that were carried out in order to establish PARASO. The new offline-based NEMO – f.ETISh coupling interface is thoroughly described. Our developments also include a new surface tiling approach to combine open-ocean and sea-ice covered cells within COSMO, which was required to make this model relevant in the context of coupled simulations in polar regions. We present results from a 2000–2001 coupled two-year experiment. PARASO is numerically stable and fully operational. The 2-year simulation conducted without fine tuning of the model reproduced the main expected features, although remaining systematic biases provide perspectives for further adjustment and development.

scholarly journals Determination of the Normalized Difference Vegetation Index (NDVI) with Top-of-Canopy (TOC) Reflectance from a KOMPSAT-3A Image Using Orfeo ToolBox (OTB) Extension

2020 ◽  
Vol 9 (4) ◽  
pp. 257 ◽  
Author(s):  
Kiwon Lee ◽  
Kwangseob Kim ◽  
Sun-Gu Lee ◽  
Yongseung Kim
Keyword(s):  
Open Source ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Spectral Response ◽  
Atmospheric Correction ◽  
Urban Forestry ◽  
Google Earth ◽  
Landsat 8 ◽  
Surface Reflectance ◽  
Reflectance Data

Surface reflectance data obtained by the absolute atmospheric correction of satellite images are useful for land use applications. For Landsat and Sentinel-2 images, many radiometric processing methods exist, and the images are supported by most types of commercial and open-source software. However, multispectral KOMPSAT-3A images with a resolution of 2.2 m are currently lacking tools or open-source resources for obtaining top-of-canopy (TOC) reflectance data. In this study, an atmospheric correction module for KOMPSAT-3A images was newly implemented into the optical calibration algorithm in the Orfeo Toolbox (OTB), with a sensor model and spectral response data for KOMPSAT-3A. Using this module, named OTB extension for KOMPSAT-3A, experiments on the normalized difference vegetation index (NDVI) were conducted based on TOC reflectance data with or without aerosol properties from AERONET. The NDVI results for these atmospherically corrected data were compared with those from the dark object subtraction (DOS) scheme, a relative atmospheric correction method. The NDVI results obtained using TOC reflectance with or without the AERONET data were considerably different from the results obtained from the DOS scheme and the Landsat-8 surface reflectance of the Google Earth Engine (GEE). It was found that the utilization of the aerosol parameter of the AERONET data affects the NDVI results for KOMPSAT-3A images. The TOC reflectance of high-resolution satellite imagery ensures further precise analysis and the detailed interpretation of urban forestry or complex vegetation features.

Impact of climate change on water requirements and growth of potato in different climatic zones of Montenegro

2018 ◽  
Vol 9 (4) ◽  
pp. 657-671 ◽  
Author(s):  
Mirko Knežević ◽  
Ljubomir Zivotić ◽  
Nataša Čereković ◽  
Ana Topalović ◽  
Nikola Koković ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Model ◽  
Regional Climate ◽  
Baseline Period ◽  
Yield Reduction ◽  
Adaptation Measures ◽  
Impact Of Climate Change ◽  
Temperature And Precipitation ◽  
Viable Solution ◽  
The Impact

Abstract The impact of climate change on potato cultivation in Montenegro was assessed. Three scenarios (A1B, A1Bs and A2) for 2001–2030, 2071–2100 and 2071–2100, respectively, were generated by a regional climate model and compared with the baseline period 1961–1990. The results indicated an increase of temperature during the summer season from 1.3 to 4.8 °C in the mountain region and from 1 to 3.4 °C in the coastal zone. The precipitation decreased between 5 and 50% depending on the scenario, region and season. The changes in temperature and precipitation influenced phenology, yield and water needs. The impact was more pronounced in the coastal areas than in the mountain regions. The growing season was shortened 13.6, 22.9 and 29.7 days for A1B, A1Bs and A2, respectively. The increase of irrigation requirement was 4.0, 19.5 and 7.3 mm for A1B, A1Bs and A2, respectively. For the baseline conditions, yield reduction under rainfed cultivation was lower than 30%. For A1B, A1Bs and A2 scenarios, yield reductions were 31.0 ± 8.2, 36.3 ± 11.6 and 34.1 ± 10.9%, respectively. Possible adaptation measures include shifting of production to the mountain (colder) areas and irrigation application. Rainfed cultivation remains a viable solution when the anticipation of sowing is adopted.

scholarly journals Climate Change Impact on the Frequency of Hydrometeorological Extremes in the Island of Crete

Water ◽  
2019 ◽  
Vol 11 (3) ◽  
pp. 587 ◽  
Author(s):  
Evdokia Tapoglou ◽  
Anthi Vozinaki ◽  
Ioannis Tsanis
Keyword(s):  
Climate Change ◽  
Frequency Analysis ◽  
Extreme Precipitation ◽  
Climate Model ◽  
Regional Climate ◽  
Standardized Precipitation Index ◽  
Hydrological Drought ◽  
Drought Indices ◽  
Rcp Scenarios ◽  
The Impact

Frequency analysis on extreme hydrological and meteorological events under the effect of climate change is performed in the island of Crete. Data from Regional Climate Model simulations (RCMs) that follow three Representative Concentration Pathways (RCP2.6, RCP4.5, RCP8.5) are used in the analysis. The analysis was performed for the 1985–2100 time period, divided into three equal-duration time slices (1985–2010, 2025–2050, and 2075–2100). Comparison between the results from the three time slices for the different RCMs under different RCP scenarios indicate that drought events are expected to increase in the future. The meteorological and hydrological drought indices, relative Standardized Precipitation Index (SPI) and Standardized Runoff index (SRI), are used to identify the number of drought events for each RCM. Results from extreme precipitation, extreme flow, meteorological and hydrological drought frequency analysis over Crete show that the impact of climate change on the magnitude of 100 years return period extreme events will also increase, along with the magnitude of extreme precipitation and flow events.

scholarly journals The Impact of Climate Change on Material Degradation Criteria in Heritage over Iran: Regional Climate Model Evaluation

2020 ◽  
Vol 172 ◽  
pp. 02006
Author(s):  
Hamed Hedayatnia ◽  
Marijke Steeman ◽  
Nathan Van Den Bossche
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Salt Crystallization ◽  
Climate Modelling ◽  
Impact Of Climate Change ◽  
Climate Change Effects ◽  
The Impact

Understanding how climate change accelerates or slows down the process of material deterioration is the first step towards assessing adaptive approaches for the preservation of historical heritage. Analysis of the climate change effects on the degradation risk assessment parameters like salt crystallization cycles is of crucial importance when considering mitigating actions. Due to the vulnerability of cultural heritage in Iran to climate change, the impact of this phenomenon on basic parameters plus variables more critical to building damage like salt crystallization index needs to be analyzed. Regional climate modelling projections can be used to asses the impact of climate change effects on heritage. The output of two different regional climate models, the ALARO-0 model (Ghent University-RMI, Belgium) and the REMO model (HZG-GERICS, Germany), is analyzed to find out which model is more adapted to the region. So the focus of this research is mainly on the evaluation to determine the reliability of both models over the region. For model validation, a comparison between model data and observations was performed in 4 different climate zones for 30 years to find out how reliable these models are in the field of building pathology.

scholarly journals The Cloud_cci simulator for the ESA Cloud_cci climate data record and its application to a global and a regional climate model

2018 ◽  
Author(s):  
Salomon Eliasson ◽  
Karl Göran Karlsson ◽  
Erik van Meijgaard ◽  
Jan Fokke Meirink ◽  
Martin Stengel ◽  
...  
Keyword(s):  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Cloud Fraction ◽  
Climate Data ◽  
European Continent ◽  
Cloud Properties ◽  
Data Record ◽  
The Impact ◽  
Climate Data Record

Abstract. The Cloud_cci satellite simulator has been developed to enable comparisons between the Cloud_cci Climate Data Record (CDR) and climate models. The Cloud_cci simulator is applied here to the EC-Earth Global Climate Model as well as the RACMO Regional Climate Model. We demonstrate the importance of using a satellite simulator that emulates the retrieval process underlying the CDR as opposed to taking the model output directly. The impact of not sampling the model at the local overpass time of the polar-orbiting satellites used to make the dataset was shown to be large, yielding up to 100 % error in Liquid Water Path (LWP) simulations in certain regions. The simulator removes all clouds with optical thickness smaller than 0.2 to emulate the Cloud_cci CDR's lack of sensitivity to very thin clouds. This reduces Total Cloud Fraction (TCF) globally by about 10 % for EC-Earth and by a few percent for RACMO over Europe. Globally, compared to the Cloud_cci CDR, EC-Earth is shown to be mostly in agreement on the distribution of clouds and their height, but it generally underestimates the high cloud fraction associated with tropical convection regions, and overestimates the occurrence and height of clouds over the Sahara and the Arabian sub-continent. In RACMO, TCF is higher than retrieved over the northern Atlantic Ocean, but lower than retrieved over the European continent, where in addition the Cloud Top Pressure (CTP) is underestimated. The results shown here demonstrate again that a simulator is needed to make meaningful comparisons between modelled and retrieved cloud properties. It is promising to see that for (nearly) all cloud properties the simulator improves the agreement of the model with the satellite data.

scholarly journals Diagnosing the Strength of Land–Atmosphere Coupling at Subseasonal to Seasonal Time Scales in Asia

2014 ◽  
Vol 15 (1) ◽  
pp. 320-339 ◽  
Author(s):  
Di Liu ◽  
Guiling Wang ◽  
Rui Mei ◽  
Zhongbo Yu ◽  
Huanghe Gu
Keyword(s):  
Soil Moisture ◽  
Time Scales ◽  
Climate Model ◽  
Regional Climate ◽  
Precipitation Amount ◽  
Data Sources ◽  
Conditional Correlation ◽  
Global Land ◽  
Land Data Assimilation System ◽  
The Impact

Abstract This paper focuses on diagnosing the strength of soil moisture–atmosphere coupling at subseasonal to seasonal time scales over Asia using two different approaches: the conditional correlation approach [applied to the Global Land Data Assimilation System (GLDAS) data, the Climate Forecast System Reanalysis (CFSR) data, and output from the regional climate model, version 4 (RegCM4)] and the Global Land–Atmosphere Coupling Experiment (GLACE) approach applied to the RegCM4. The conditional correlation indicators derived from the model output and the two observational/reanalysis datasets agree fairly well with each other in the spatial pattern of the land–atmosphere coupling signal, although the signal in CFSR data is stronger and spatially more extensive than the GLDAS data and the RegCM4 output. Based on the impact of soil moisture on 2-m air temperature, the land–atmosphere coupling hotspots common to all three data sources include the Indochina region in spring and summer, the India region in summer and fall, and north-northeastern China and southwestern Siberia in summer. For precipitation, all data sources produce a weak and spatially scattered signal, indicating the lack of any strong coupling between soil moisture and precipitation, for both precipitation amount and frequency. Both the GLACE approach and the conditional correlation approach (applied to all three data sources) identify evaporation and evaporative fraction as important links for the coupling between soil moisture and precipitation/temperature. Results on soil moisture–temperature coupling strength from the GLACE-type experiment using RegCM4 are in good agreement with those from the conditional correlation analysis applied to output from the same model, despite substantial differences between the two approaches in the terrestrial segment of the land–atmosphere coupling.

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