scholarly journals Long-term mammal and nocturnal bird trends are influenced by vegetation type, weather and climate in temperate woodlands

2020 ◽  
Author(s):  
David B. Lindenmayer ◽  
Peter Lane ◽  
Martin J. Westgate ◽  
Ben C. Scheele ◽  
Mason Crane ◽  
...  
Keyword(s):  
Vegetation Type ◽  
Temperate Woodlands ◽  
Weather And Climate

scholarly journals Weather effects on birds of different size are mediated by long‐term climate and vegetation type in endangered temperate woodlands

2018 ◽  
Vol 25 (2) ◽  
pp. 675-685 ◽  
Author(s):  
David B. Lindenmayer ◽  
Peter Lane ◽  
Mason Crane ◽  
Daniel Florance ◽  
Claire N. Foster ◽  
...  
Keyword(s):  
Vegetation Type ◽  
Weather Effects ◽  
Temperate Woodlands

scholarly journals Monitoring Selected Species of Mammals in Grand Teton National Park in 2001

2001 ◽  
Vol 25 ◽  
pp. 82-87
Author(s):  
Brian Miller ◽  
Hank Harlow
Keyword(s):  
National Park ◽  
Vegetation Type ◽  
Vegetation Types ◽  
Population Composition ◽  
Grand Teton National Park ◽  
Needed Information ◽  
Mammal Distribution ◽  
The Impact ◽  
Term Monitoring

Our objective is to establish a long-term monitoring project that will assess the abundance and densities of selected species of mammals at sites representing five defined vegetation types found in Grand Teton National Park. The term monitoring implies data collection over multiple years. Taking long term estimations of population composition before, during, and after biotic and abiotic changes provides needed information to assess the impacts of such changes and furnish useful options for management decisions. This standardized monitoring plan will provide information on small and medium-sized mammals that will (1) assess species use of habitat, (2) monitor changes in species composition as a result of environmental change, such as precipitation and temperature, (3) produce predictive models of small and medium-sized mammal distribution based on vegetation type, and (4) analyze the impact of wolf colonization on the mammal (and plant) community.

scholarly journals Wind plants can impact long-term local atmospheric conditions

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Nicola Bodini ◽  
Julie K. Lundquist ◽  
Patrick Moriarty
Keyword(s):  
Wind Speed ◽  
Urban Areas ◽  
Weather Prediction ◽  
Atmospheric Conditions ◽  
Near Surface ◽  
Direct Observations ◽  
Stable Conditions ◽  
Weather And Climate ◽  
Central United States

AbstractLong-term weather and climate observatories can be affected by the changing environments in their vicinity, such as the growth of urban areas or changing vegetation. Wind plants can also impact local atmospheric conditions through their wakes, characterized by reduced wind speed and increased turbulence. We explore the extent to which the wind plants near an atmospheric measurement site in the central United States have affected their long-term measurements. Both direct observations and mesoscale numerical weather prediction simulations demonstrate how the wind plants induce a wind deficit aloft, especially in stable conditions, and a wind speed acceleration near the surface, which extend $$\sim 30$$ ∼ 30  km downwind of the wind plant. Turbulence kinetic energy is significantly enhanced within the wind plant wake in stable conditions, with near-surface observations seeing an increase of more than 30% a few kilometers downwind of the plants.

The In situ Global Ocean Observing System for Climate (and Other Needs)

2015 ◽  
Vol 49 (2) ◽  
pp. 112-121
Author(s):  
Stephen R. Piotrowicz ◽  
David M. Legler
Keyword(s):  
Weather Forecasting ◽  
Spatial Scales ◽  
The Arctic ◽  
Global Ocean ◽  
Observation System ◽  
Ocean Management ◽  
Accuracy And Precision ◽  
Weather And Climate ◽  
Ocean Observing

AbstractThe Global Ocean Observing System (GOOS) is the international observation system that ensures long-term sustained ocean observations. The ocean equivalent of the atmospheric observing system supporting weather forecasting, GOOS, was originally developed to provide data for weather and climate applications. Today, GOOS data are used for all aspects of ocean management as well as weather and climate research and forecasting. National Oceanic and Atmospheric Administration (NOAA), through the Climate Observation Division of the Office of Oceanic and Atmospheric Research/Climate Program Office, is a major supporter of the climate component of GOOS. This paper describes the eight elements of GOOS, and the Arctic Observing Network, to which the Climate Observation Division is a major contributor. In addition, the paper addresses the evolution of the observing system as rapidly evolving new capabilities in sensors, platforms, and telecommunications allow observations at unprecedented temporal and spatial scales with the accuracy and precision required to address questions of climate variability and change.

scholarly journals MODELING PRECIPITATION DEPENDENT FOREST RESILIENCE IN INDIA

2018 ◽  
Vol XLII-3 ◽  
pp. 263-266 ◽  
Author(s):  
P. Das ◽  
M. D. Behera ◽  
P. S. Roy
Keyword(s):  
Forest Cover ◽  
Vegetation Type ◽  
Annual Precipitation ◽  
Mean Annual Precipitation ◽  
High Tendency ◽  
North East India ◽  
North East ◽  
Forest Resilience ◽  
The Impact

The impact of long term climate change that imparts stress on forest could be perceived by studying the regime shift of forest ecosystem. With the change of significant precipitation, forest may go through density change around globe at different spatial and temporal scale. The 100 class high resolution (60 meter spatial resolution) Indian vegetation type map was used in this study recoded into four broad categories depending on phrenology as (i) forest, (ii) scrubland, (iii) grassland and (iv) treeless area. The percentage occupancy of forest, scrub, grass and treeless were observed as 19.9&amp;thinsp;%, 5.05&amp;thinsp;%, 1.89&amp;thinsp;% and 7.79&amp;thinsp;% respectively. Rest of the 65.37&amp;thinsp;% land area was occupied by the cropland, built-up, water body and snow covers. The majority forest cover were appended into a 5&amp;thinsp;km&amp;thinsp;&amp;times;&amp;thinsp;5&amp;thinsp;km grid, along with the mean annual precipitation taken from Bioclim data. The binary presence and absence of different vegetation categories in relates to the annual precipitation was analyzed to calculate their resilience expressed in probability values ranging from 0 to 1. Forest cover observed having resilience probability (Pr) &amp;lt;&amp;thinsp;0.3 in only 0.3&amp;thinsp;% (200&amp;thinsp;km<sup>2</sup>) of total forest cover in India, which was 4.3&amp;thinsp;% &amp;lt;&amp;thinsp;0.5&amp;thinsp;Pr. Majority of the scrubs and grass (64.92&amp;thinsp;% Pr&amp;thinsp;&amp;lt;&amp;thinsp;0.5) from North East India which were the shifting cultivation lands showing low resilience, having their high tendency to be transform to forest. These results have spatial explicitness to highlight the resilient and non-resilient distribution of forest, scrub and grass, and treeless areas in India.

Trend analysis of extratropical cyclones in long-term ERA5 data series (1950-2019)

2021 ◽  
Author(s):  
Richard Blender ◽  
Alexia Karwat ◽  
Christian Franzke
Keyword(s):  
Nearest Neighbor ◽  
Climate Extremes ◽  
Reanalysis Data ◽  
Nearest Neighbor Search ◽  
Data Series ◽  
Extratropical Cyclones ◽  
Weather Forecasts ◽  
Neighbor Search ◽  
Weather And Climate

&lt;p&gt;Extratropical cyclones are the primary natural hazards affecting Europe. With the release of ERA5 reanalysis data from 1950-1978 by the European Centre for Medium-Range Weather Forecasts (ECMWF), new opportunities have arisen to investigate mid-latitude cyclones in terms of climatic features and trends in longer and higher resolution. We analyze cyclones by nearest neighbor search in 1000 hPa geopotential height minima in different high resolutions for different minimum life-times. We find an intensification of North Atlantic cyclones in 1950-2019. Short-lived cyclones grow in radius and depth. In the Mediterranean, however, long-lived cyclones have weakened; but traveled also further in 1950-2019. Additionally, we illustrate relations between cyclone tracks, radii and correlated weather and climate extremes.&lt;/p&gt;

Visualising the invisible: performing chaos theory

Leonardo ◽  
2020 ◽  
pp. 1-8
Author(s):  
Emma Weitkamp
Keyword(s):  
Complex Systems ◽  
Chaos Theory ◽  
Initial Conditions ◽  
Starting Point ◽  
Weather And Climate ◽  
Butterfly Effect ◽  
Long Term Behavior ◽  
The Invisible

Edward Lorenz, the pioneering figure in the field of chaos theory coined the phrase “butterfly effect” and posed the famous question “Does the flap of a butterfly's wings in Brazil set off a tornado in Texas?” In posing the question, Lorenz sought to highlight the intrinsic difficulty of predicting the long term behavior of complex systems that are sensitive to initial conditions, like, for example, the weather and climate; these systems are often referred to as chaotic. Taking Lorenz' butterfly as a starting point, Chaos Cabaret sought to explore the nuances of chaos theory through performance and music.

scholarly journals Scientific motivation for ADM/Aeolus mission

2018 ◽  
Vol 176 ◽  
pp. 02008
Author(s):  
Erland Källén
Keyword(s):  
Weather Forecast ◽  
Weather Forecasts ◽  
Weather And Climate ◽  
Medium Range ◽  
Forecast Models ◽  
Tropical Areas ◽  
Global Coverage ◽  
Wind Lidar ◽  
Wind Profiles

The ADM/Aeolus wind lidar mission will provide a global coverage of atmospheric wind profiles. Atmospheric wind observations are required for initiating weather forecast models and for predicting and monitoring long term climate change. Improved knowledge of the global wind field is widely recognised as fundamental to advancing the understanding and prediction of weather and climate. In particular over tropical areas there is a need for better wind data leading to improved medium range (3-10 days) weather forecasts over the whole globe.

scholarly journals Continuous Single-Column Model Evaluation at a Permanent Meteorological Supersite

2012 ◽  
Vol 93 (9) ◽  
pp. 1389-1400 ◽  
Author(s):  
R. A. J. Neggers ◽  
A. P. Siebesma ◽  
T. Heus
Keyword(s):  
Case Studies ◽  
General Circulation ◽  
Column Model ◽  
Parameterization Schemes ◽  
Numerical Predictions ◽  
Single Column ◽  
Weather And Climate ◽  
Single Column Model ◽  
Process Level

Uncertainties in numerical predictions of weather and climate are often linked to the representation of unresolved processes that act relatively quickly compared to the resolved general circulation. These processes include turbulence, convection, clouds, and radiation. Single-column model (SCM) simulation of idealized cases and the subsequent evaluation against large-eddy simulation (LES) results has become an often used and relied on method to obtain insight at process level into the behavior of such parameterization schemes; benefits of SCM simulation are the enhanced model transparency and the high computational efficiency. Although this approach has achieved demonstrable success, some shortcomings have been identified; among these, i) the statistical significance and relevance of single idealized case studies might be questioned and ii) the use of observational datasets has been relatively limited. A recently initiated project named the Royal Netherlands Meteorological Institute (KNMI) Parameterization Testbed (KPT) is part of a general move toward a more statistically significant process-level evaluation, with the purpose of optimizing the identification of problems in general circulation models that are related to parameterization schemes. The main strategy of KPT is to apply continuous long-term SCM simulation and LES at various permanent meteorological sites, in combination with comprehensive evaluation against observations at multiple time scales. We argue that this strategy enables the reproduction of typical long-term mean behavior of fast physics in large-scale models, but it still preserves the benefits of single-case studies (such as model transparency). This facilitates the tracing and understanding of errors in parameterization schemes, which should eventually lead to a reduction of related uncertainties in numerical predictions of weather and climate.

scholarly journals Hydroclimatic Controls on the Means and Variability of Vegetation Phenology and Carbon Uptake

2014 ◽  
Vol 27 (14) ◽  
pp. 5632-5652 ◽  
Author(s):  
R. D. Koster ◽  
G. K. Walker ◽  
G. J. Collatz ◽  
P. E. Thornton
Keyword(s):  
Spatial Variation ◽  
Primary Productivity ◽  
Vegetation Type ◽  
Temporal Variations ◽  
Carbon Uptake ◽  
Type Ii ◽  
Vegetation Phenology ◽  
Spatial And Temporal Distributions ◽  
Phenology Model

Abstract Long-term, global offline (land only) simulations with a dynamic vegetation phenology model are used to examine the control of hydroclimate over vegetation-related quantities. First, with a control simulation, the model is shown to capture successfully (though with some bias) key observed relationships between hydroclimate and the spatial and temporal variations of phenological expression. In subsequent simulations, the model shows that (i) the global spatial variation of seasonal phenological maxima is controlled mostly by hydroclimate, irrespective of distributions in vegetation type; (ii) the occurrence of high interannual moisture-related phenological variability in grassland areas is determined by hydroclimate rather than by the specific properties of grassland; and (iii) hydroclimatic means and variability have a corresponding impact on the spatial and temporal distributions of gross primary productivity (GPP).

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