scholarly journals SPECTRAL CHARACTERISTICS OF TUNDRA AND FOREST TUNDRA LANDSCAPES DURING THE YEARS OF SUMMER TEMPERATURE ANOMALIES

2020 ◽  
Vol 4 ◽  
pp. 88-103
Author(s):  
T.B. Titkova ◽  
◽  
A.N. Zolotokrylin ◽  
V.V. Vinogradov ◽  
◽  
...  
Keyword(s):  
Surface Temperature ◽  
Regulatory Mechanism ◽  
Spectral Characteristics ◽  
Extreme Temperature ◽  
Regulatory Mechanisms ◽  
Spectral Parameters ◽  
Vegetation Diversity ◽  
Forest Tundra ◽  
Temperature Anomalies ◽  
Novaya Zemlya

The warming at high latitudes, remaining in recent years, has a direct impact on arctic and subarctic landscapes. Possible changes of this landscapes under the climate warming are closely related with regulatory mechanisms for the underlying surface temperature. The circumstances of forming radiation and evapotranspirational regulatory mechanisms for the surface temperature were explored for tundra (from arctic to southern) and forest tundra landscapes of Novaya Zemlya and Western Siberia. The MODIS data of surface spectral characteristics were used, and more specifically albedo (Al) and surface temperature (Ts) for July 2000-2019. The work shows that the radiation regulatory mechanism of the surface temperature is dominated in glacial and polar desert landscapes of Arctic and Subarctic with a predominance of stony and rubble types of surfaces with lichens. At the same time, radiative surface temperature control mechanism in mountain and arctic tundra of Novaya Zemlya almost does not depend on weather anomalies and so far has a little implication for the temperature trend. In the mainland and forest tundra, the evapotranspirational regulatory mechanism for the surface temperature starts to prevail. This is supported by the increasing of monthly average air temperatures to 15-16°С, which is beneficial to the vegetation diversity. In subzones of the southern and forest tundra, the connection of albedo and surface temperature depends on altitudes, slope exposure and especially on extreme temperature anomalies. In basins, or hydromorphic complexes, in cold years against the backdrop of wetlands the regulatory mechanism for the surface temperature prevails, and in warm years the humidity decreasing leads to the highest vegetation development and the connection type can turn into the evapotranspirational one. On the high grounds the return process is observed, which is also connected with the changes in humidification conditions. In forest tundra, where the air temperature rises and the canopy height increases, the evapotranspirational mechanism of spectral parameters Al–Ts connections is weakening. As a result, in southern and forest tundra two balanced steady states of the connection types of surface spectral characteristics can exist in relation to lighting conditions and temperature anomalies.

The Lifecycle and Physical Drivers of Heatwaves in a Hierarchy of Model Simulations  

2021 ◽  
Author(s):  
Bernat Jiménez-Esteve ◽  
Daniela I.V. Domeisen
Keyword(s):  
Surface Temperature ◽  
Extreme Temperature ◽  
Model Complexity ◽  
Extreme Weather Events ◽  
Horizontal Wind ◽  
Physical Processes ◽  
Near Surface ◽  
Temperature Anomalies ◽  
Model Configuration ◽  
Diabatic Processes

<p>Heatwaves are extreme weather events characterized by extreme near-surface temperature anomalies that persist for several days, which lead to catastrophic impacts on natural ecosystems, agriculture, human health, and economies. Different physical processes can contribute to the increase in temperature associated with heatwaves. Previous studies have shown that adiabatic compression due to subsidence and local land-atmosphere coupling are important drivers of summer heatwaves. However, less is known about the respective roles of these processes for heat extremes occurring in different seasons and latitudes.</p><p>By analyzing the different terms of the temperature tendency equation, we quantify the relative importance of horizontal wind advection, adiabatic, and diabatic processes (including radiation and surface fluxes) during the lifecycle of realistic and idealized heatwaves. We identify heatwaves both in reanalysis and in simulations using the ICOsahedral Nonhydrostatic (ICON) climate model. These simulations range from a simple zonally symmetric temperature relaxation and dry dynamics to a simulation using full physics, with coupled land and sea surface temperature forcing. This step-wise inclusion of physical processes and increasing model complexity allows us to identify the key drivers of extreme warm events and the characteristics of these across the different model complexities. In the simplest model configuration, i.e. only dry dynamics and no surface coupling, extreme temperature events are generally shorter but produce more intense temperature anomalies in the midlatitudes, where the horizontal temperature gradient is strongest. These idealized heatwaves are almost entirely driven by a very strong advection of warm air from more equatorward locations and are linked to local amplification of Rossby wave packets and atmospheric blocking. In contrast, in the complex model configuration as well as in reanalysis, summer heatwaves over land areas are mainly driven by adiabatic and diabatic processes, while advection is of secondary importance. On the other hand, extreme warm periods during winter are mainly driven by advection both in the model and reanalysis. Identifying the most relevant processes driving heatwaves can potentially benefit the prediction and representation of extreme events in operational weather and climate forecasts.</p>

scholarly journals An Analysis of the Potential for Extreme Temperature Change Based on Observations and Model Simulations

2007 ◽  
Vol 20 (8) ◽  
pp. 1539-1554 ◽  
Author(s):  
Barry H. Lynn ◽  
Richard Healy ◽  
Leonard M. Druyan
Keyword(s):  
United States ◽  
Surface Temperature ◽  
Temperature Change ◽  
Extreme Temperature ◽  
Sea Surface ◽  
Eastern Pacific ◽  
Moist Convection ◽  
Eastern United States ◽  
Maximum Surface ◽  
Temperature Anomalies

Abstract The study analyzes observational climate data for June–August 1977–2004 and simulations of current and future climate scenarios from a nested GCM/regional climate model system to assess the potential for extreme temperature change over the eastern United States. Observational evidence indicates that anomalously warm summers in the eastern United States coincide with anomalously cool eastern Pacific sea surface temperatures, conditions that are conducive to geopotential ridging over the east, less frequent precipitation, and lower accumulated rainfall. The study also found that days following nighttime rain are warmer on average than daytime rain events, emphasizing the importance of the timing of precipitation on the radiation balance. Precipitation frequency and eastern Pacific sea surface temperature anomalies together account for 57% of the 28-yr variance in maximum surface temperature anomalies. Simulation results show the sensitivity of maximum surface air temperature to the moist convection parameterization that is employed, since different schemes produce different diurnal cycles and frequencies of precipitation. The study suggests that, in order to accurately project scenarios of extreme temperature change, models need to realistically simulate changes in the surface energy balance caused by the interannual variation of these precipitation characteristics. The mesoscale model that was realistic in this respect predicted much warmer mean and maximum surface air temperatures for five future summers than the parallel GCM driving simulation.

Copepod and monogenean infection of fish under sea surface temperature anomalies

2021 ◽  
pp. 102098
Author(s):  
F. Neptalí Morales-Serna ◽  
Lorenia Olivas-Padilla ◽  
Emigdio Marín-Enriquez ◽  
Juan M. Osuna-Cabanillas ◽  
Hugo Aguirre-Villaseñor ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Sea Surface ◽  
Temperature Anomalies ◽  
Sea Surface Temperature Anomalies ◽  
Monogenean Infection

scholarly journals A Process-Oriented Approach to Identify Evolutions of Sea Surface Temperature Anomalies with a Time-Series of a Raster Dataset

2021 ◽  
Vol 10 (8) ◽  
pp. 500
Author(s):  
Lianwei Li ◽  
Yangfeng Xu ◽  
Cunjin Xue ◽  
Yuxuan Fu ◽  
Yuanyu Zhang
Keyword(s):  
Time Series ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Global Climate ◽  
Sea Surface ◽  
Temperature Anomalies ◽  
Global Climate Changes ◽  
Space And Time ◽  
Novel Approach ◽  
Sea Surface Temperature Anomalies

It is important to consider where, when, and how the evolution of sea surface temperature anomalies (SSTA) plays significant roles in regional or global climate changes. In the comparison of where and when, there is a great challenge in clearly describing how SSTA evolves in space and time. In light of the evolution from generation, through development, and to the dissipation of SSTA, this paper proposes a novel approach to identifying an evolution of SSTA in space and time from a time-series of a raster dataset. This method, called PoAIES, includes three key steps. Firstly, a cluster-based method is enhanced to explore spatiotemporal clusters of SSTA, and each cluster of SSTA at a time snapshot is taken as a snapshot object of SSTA. Secondly, the spatiotemporal topologies of snapshot objects of SSTA at successive time snapshots are used to link snapshot objects of SSTA into an evolution object of SSTA, which is called a process object. Here, a linking threshold is automatically determined according to the overlapped areas of the snapshot objects, and only those snapshot objects that meet the specified linking threshold are linked together into a process object. Thirdly, we use a graph-based model to represent a process object of SSTA. A node represents a snapshot object of SSTA, and an edge represents an evolution between two snapshot objects. Using a number of child nodes from an edge’s parent node and a number of parent nodes from the edge’s child node, a type of edge (an evolution relationship) is identified, which shows its development, splitting, merging, or splitting/merging. Finally, an experiment on a simulated dataset is used to demonstrate the effectiveness and the advantages of PoAIES, and a real dataset of satellite-SSTA is used to verify the rationality of PoAIES with the help of ENSO’s relevant knowledge, which may provide new references for global change research.

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