Multibeam bathymetric data at NOAA/NGDC

Virden, W.; Habermann, Ted; Glover, G.; Divins, David; Sharman, G. F.; Fox, Christopher G.

doi:10.1109/oceans.2004.1405673

Cited by 3 publications

(2 citation statements)

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“…This yields print-quality maps based on the raster and vector layers processed using a combination of various GMT modules, as required in scripting. GMT has gained popularity in topographic, marine geologic and geophysical mapping where highly detailed and accurate data for modelling the phenomena of the Earth processes and structures are essential [93][94][95][96][97][98][99].…”

Section: Methodsmentioning

confidence: 99%

Mapping Climate Parameters over the Territory of Botswana Using GMT and Gridded Surface Data from TerraClimate

Lemenkova

2022

IJGI

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This articles presents a new series of maps showing the climate and environmental variability of Botswana. Situated in southern Africa, Botswana has an arid to semi-arid climate, which significantly varies in its different regions: Kalahari Desert, Makgadikgadi Pan and Okavango Delta. While desert regions are prone to droughts and periods of extreme heat during the summer months, other regions experience heavy downpours, as well as episodic and unpredictable rains that affect agricultural activities. Such climatic variations affect social and economic aspects of life in Botswana. This study aimed to visualise the non-linear correlations between the topography and climate setting at the country’s scale. Variables included T °C min, T °C max, precipitation, soil moisture, evapotranspiration (PET and AET), downward surface shortwave radiation, vapour pressure and vapour pressure deficit (VPD), wind speed and Palmer Drought Severity Index (PDSI). The dataset was taken from the TerraClimate source and GEBCO for topographic mapping. The mapping approach included the use of Generic Mapping Tools (GMT), a console-based scripting toolset, which enables the use of a scripting method of automated mapping. Several GMT modules were used to derive a set of climate parameters for Botswana. The data were supplemented with the adjusted cartographic elements and inspected by the Geospatial Data Abstraction Library (GDAL). The PDSI in Botswana in 2018 shows stepwise variation with seven areas of drought: (1) −3.7 to −2.2. (extreme); (2) −2.2 to −0.8 (strong, southern Kalahari); (3) −0.8 to 0.7 (significant, central Kalahari; (4) 0.7 to 2.1 (moderate); (5) 2.1 to 3.5 (lesser); (6) 3.5 to 4.9 (low); (7) 4.9 to 6.4 (least). The VPD has a general trend towards the south-western region (Kalahari Desert, up to 3.3), while it is lower in the north-eastern region of Botswana (up to 1.4). Other values vary respectively, as demonstrated in the presented 12 maps of climate and environmental inventory in Botswana.

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Section: Methodsmentioning

confidence: 99%

Mapping Climate Parameters over the Territory of Botswana Using GMT and Gridded Surface Data from TerraClimate

Lemenkova

2022

IJGI

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“…The study presents a series of the eleven new maps (ten climate maps and a topographic map) made using scripting techniques of GMT, applied in the existing cartographic studies [73][74][75][76][77][78]. Full GMT scripts used for plotting these maps are available in the Appendices with provided live-links to the corresponding maps for repeatability of these techniques in similar cartographic tasks in relevant studies and as a technical reference.…”

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confidence: 99%

Console-Based Mapping of Mongolia Using GMT Cartographic Scripting Toolset for Processing TerraClimate Data

Lemenkova

2022

Geosciences

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This paper explores spatial variability of the ten climatic variables of Mongolia in 2019: average minimal and maximal temperatures, wind speed, soil moisture, downward surface shortwave radiation (DSRAD), snow water equivalent (SWE), vapor pressure deficit (VPD), vapor pressure anomaly (VAP), monthly precipitation and Palmer Drought Severity Index (PDSI). The PDSI demonstrates the simplified soil water balance estimating relative soil moisture conditions in Mongolia. The research presents mapping of the climate datasets derived from TerraClimate open source repository of the meteorological and climate measurements in NetCDF format. The methodology presented the compiled observations of Mongolia visualised by GMT coding approach using Generic Mapping Tools (GMT) cartographic scripting toolset. The results present 10 new maps of climate data over Mongolia made using automated cartographic techniques of GMT. Spatial environmental and climate analysis were conducted which determine relative distribution of PDSI and temperature extremes, precipitation and soil moisture, wind speed and DSRAD. The DSRAD showed minimum at 40 Wm−2, maximum at 113 Wm−2 in the Gobi Desert region, SWE (up to 491 mm), VAP and VPD compared with landmass parameters represent powerful cartographic tools to address complex regional climate and environmental issues in Mongolia, a country with contrasting topography, extreme climate conditions and unique environmental setting.

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What Doesn't Kill You Will Only Make You More Risk-Loving: Early-Life Disasters and CEO Behavior

2014

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The literature on managerial style posits a linear relation between a CEO's past experiences and firm risk. We show that there is a non-monotonic relation between the intensity of CEOs' earlylife exposure to fatal disasters and corporate risk-taking. CEOs who experience fatal disasters without extremely negative consequences lead firms that behave more aggressively, whereas CEOs who witness the extreme downside of disasters behave more conservatively. These patterns manifest across various corporate policies including leverage, cash holdings, and acquisition activity. Ultimately, the link between CEOs' disaster experience and corporate policies has real economic consequences on firm riskiness and cost of capital.

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Multibeam bathymetric data at NOAA/NGDC

Cited by 3 publications

References 0 publications

Mapping Climate Parameters over the Territory of Botswana Using GMT and Gridded Surface Data from TerraClimate

Mapping Climate Parameters over the Territory of Botswana Using GMT and Gridded Surface Data from TerraClimate

Console-Based Mapping of Mongolia Using GMT Cartographic Scripting Toolset for Processing TerraClimate Data

What Doesn't Kill You Will Only Make You More Risk-Loving: Early-Life Disasters and CEO Behavior

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