Spatial variability in long-term temperature trends in the middle atmosphere from SABER/TIMED observations

2021 ◽  
Author(s):  
Uma Das
Keyword(s):  
Spatial Variability ◽  
Middle Atmosphere ◽  
Temperature Trends

The season peculiarities of behaviour of the long-term temperature trends in the middle atmosphere on the mid-latitudes

2002 ◽  
Vol 27 (6-8) ◽  
pp. 529-534 ◽  
Author(s):  
A.I Semenov ◽  
N.N Shefov ◽  
E.V Lysenko ◽  
G.V Givishvili ◽  
A.V Tikhonov
Keyword(s):  
Middle Atmosphere ◽  
Temperature Trends

scholarly journals Special Issue on Climate Migration

2021 ◽  
pp. 1-3
Author(s):  
Anda David ◽  
Frédéric Docquier
Keyword(s):  
Climate Change ◽  
Human Mobility ◽  
Economic Research ◽  
Special Issue ◽  
Low Latitude ◽  
Weather Shocks ◽  
Temperature Trends ◽  
Agricultural Areas ◽  
Slow Onset

How do weather shocks influence human mobility and poverty, and how will long-term climate change affect future migration over the course of the 21st century? These questions have gained unprecedented attention in public debates as global warming is already having severe impacts around the world, and prospects for the coming decades get worse. Low-latitude countries in general, and their agricultural areas in particular, have contributed the least to climate change but are the most adversely affected. The effect on people's voluntary and forced displacements is of major concern for both developed and developing countries. On 18 October 2019, Agence Française de Développement (AFD) and Luxembourg Institute of Socio-Economic Research (LISER) organized a workshop on Climate Migration with the aim of uncovering the mechanisms through which fast-onset variables (such as weather anomalies, storms, hurricanes, torrential rains, floods, landslides, etc.) and slow-onset variables (such as temperature trends, desertification, rising sea level, coastal erosion, etc.) influence both people's incentives to move and mobility constraints. This special issue gathers five papers prepared for this workshop, which shed light on (or predict) the effect of extreme weather shocks and long-term climate change on human mobility, and stress the implications for the development community.

scholarly journals Climatological and statistical characteristics of the Haines Index for North America

2007 ◽  
Vol 16 (2) ◽  
pp. 139 ◽  
Author(s):  
Julie A. Winkler ◽  
Brian E. Potter ◽  
Dwight F. Wilhelm ◽  
Ryan P. Shadbolt ◽  
Krerk Piromsopa ◽  
...  
Keyword(s):  
North America ◽  
Spatial Variability ◽  
Atmospheric Pressure ◽  
Statistical Characteristics ◽  
Potential Contribution ◽  
Extensive Analysis ◽  
Temperature And Humidity ◽  
Humidity Measurements ◽  
Operational Tool

The Haines Index is an operational tool for evaluating the potential contribution of dry, unstable air to the development of large or erratic plume-dominated wildfires. The index has three variants related to surface elevation, and is calculated from temperature and humidity measurements at atmospheric pressure levels. To effectively use the Haines Index, fire forecasters and managers must be aware of the climatological and statistical characteristics of the index for their location. However, a detailed, long-term, and spatially extensive analysis of the index does not currently exist. To meet this need, a 40-year (1961–2000) climatology of the Haines Index was developed for North America. The climatology is based on gridded (2.5° latitude × 2.5° longitude) temperature and humidity fields from the NCEP/NCAR reanalysis. The climatology illustrates the large spatial variability in the Haines Index both within and between regions using the different index variants. These spatial variations point to the limitations of the index and must be taken into account when using the Haines Index operationally.

scholarly journals Two decades of in-situ temperature measurements in the upper troposphere and lowermost stratosphere from IAGOS long-term routine observation

2017 ◽  
Author(s):  
Florian Berkes ◽  
Patrick Neis ◽  
Martin G. Schultz ◽  
Ulrich Bundke ◽  
Susanne Rohs ◽  
...  
Keyword(s):  
Weather Forecast ◽  
Global Scale ◽  
Temperature Trend ◽  
Data Set ◽  
Medium Range Weather Forecast ◽  
Upper Troposphere ◽  
Temperature Trends ◽  
Geographical Regions

Abstract. Despite several studies on temperature trends in the tropopause region, a comprehensive understanding of the evolution of temperatures in this climate-sensitive region of the atmosphere remains elusive. Here we present a unique global-scale, long-term data set of high-resolution in-situ temperature data measured aboard passenger aircraft within the European Research Infrastructure IAGOS (In-service Aircraft for a Global Observing System, www.iagos.org). This data set is used to investigate temperature trends within the global upper troposphere and lowermost stratosphere (UTLS) for the period 1995 to 2012 in different geographical regions and vertical layers of the UTLS. The largest amount of observations is available over the North Atlantic. Here, a neutral temperature trend is found within the lowermost stratosphere. This contradicts the temperature trend in the European Centre for Medium Range Weather Forecast (ECMWF) ERA-Interim reanalysis, where a significant (95 % confidence) temperature increase of +0.56 K/decade is obtained. Differences between trends derived from observations and reanalysis data can be traced back to changes in the temperature bias between observation and model data over the studied period. This study demonstrates the value of the IAGOS temperature observations as anchor point for the evaluation of reanalyses and its suitability for independent trend analyses.

scholarly journals NLC and the background atmosphere above ALOMAR

2011 ◽  
Vol 11 (12) ◽  
pp. 5701-5717 ◽  
Author(s):  
J. Fiedler ◽  
G. Baumgarten ◽  
U. Berger ◽  
P. Hoffmann ◽  
N. Kaifler ◽  
...  
Keyword(s):  
Diurnal Cycle ◽  
Middle Atmosphere ◽  
Thermal State ◽  
Atmospheric Tides ◽  
Data Set ◽  
Ice Particles ◽  
Cloud Water Content ◽  
Radar Measurements ◽  
Mf Radar

Abstract. Noctilucent clouds (NLC) have been measured by the Rayleigh/Mie/Raman-lidar at the ALOMAR research facility in Northern Norway (69° N, 16° E). From 1997 to 2010 NLC were detected during more than 1850 h on 440 different days. Colocated MF-radar measurements and calculations with the Leibniz-Institute Middle Atmosphere (LIMA-) model are used to characterize the background atmosphere. Temperatures as well as horizontal winds at 83 km altitude show distinct differences during NLC observations compared to when NLC are absent. The seasonally averaged temperature is lower and the winds are stronger westward when NLC are detected. The wind separation is a robust feature as it shows up in measurements as well as in model results and it is consistent with the current understanding that lower temperatures support the existence of ice particles. For the whole 14-year data set there is no statistically significant relation between NLC occurrence and solar Lyman-α radiation. On the other hand NLC occurrence and temperatures at 83 km show a significant anti-correlation, which suggests that the thermal state plays a major role for the existence of ice particles and dominates the pure Lyman-α influence on water vapor during certain years. We find the seasonal mean NLC altitudes to be correlated to both Lyman-α radiation and temperature. NLC above ALOMAR are strongly influenced by atmospheric tides. The cloud water content varies by a factor of 2.8 over the diurnal cycle. Diurnal and semidiurnal amplitudes and phases show some pronounced year-to-year variations. In general, amplitudes as well as phases vary in a different manner. Amplitudes change by a factor of more than 3 and phases vary by up to 7 h. Such variability could impact long-term NLC observations which do not cover the full diurnal cycle.

Using hillslope-scale groundwater model to bridge the gap between basin inputs and river concentrations. The case of nitrates in Brittany (France).

2021 ◽  
Author(s):  
Luca Guillaumot ◽  
Luc Aquilina ◽  
Jean-Raynald de Dreuzy ◽  
Jean Marçais ◽  
Patrick Durand
Keyword(s):  
Spatial Variability ◽  
Groundwater Resources ◽  
Residence Times ◽  
Groundwater Model ◽  
Nitrogen Inputs ◽  
Nitrate Concentrations ◽  
Physically Based ◽  
Nutrient Surplus ◽  
Hillslope Scale

<p>Over the past decades, intensive agriculture has altered surface water and groundwater resources quality. Nutrient surplus increased nitrate concentrations in groundwater and rivers resulting in eutrophication or drinking water risk having ecosystem, sanitary and economic repercussions. Legislations led to a reduction of agricultural inputs of nitrogen since 1990’s followed by a decrease of nitrate concentrations in rivers, but still difficult to predict and evaluate. Indeed, the incomplete knowledge of the spatial variability of climate and nitrogen inputs, cumulated to the unknown groundwater heterogeneity,  leads to hydrological and biogeochemical processes difficult to model. This study deals with the long-term variations (~decades) of nitrate concentrations in three rivers (~30 km² catchment) located in Brittany. Thus, we focus on groundwater modelling because they constitute the bigger hydrological reservoir. We developed a parsimonious equivalent hillslope-scale groundwater model. The model parameterization, which controls hydrological functioning such as mean groundwater residence times, young water contribution to the river or denitrification, relies on long-term monitored streamflow and nitrate river concentrations. In addition, dissolved CFC were sampled in the catchments. Finally, we found that uncertainty on simulated nitrate river concentrations is low. The physically-based model also brings information on temporal and spatial variability of groundwater residence times highlighting the relative importance of young (1-5 yr) and old waters (~decades) for nitrate river concentrations. Moreover, calibrated models show similar trends looking at two fictive input scenarios from 2015 to 2050.</p>

scholarly journals Deeper waters are changing less consistently than surface waters in a global analysis of 102 lakes

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Rachel M. Pilla ◽  
Craig E. Williamson ◽  
Boris V. Adamovich ◽  
Rita Adrian ◽  
Orlane Anneville ◽  
...  
Keyword(s):  
Surface Water ◽  
Average Rate ◽  
Thermal Structure ◽  
Global Analysis ◽  
Regional Climate ◽  
Data Set ◽  
Water Column Stability ◽  
Temperature Trends ◽  
Lake Characteristics

AbstractGlobally, lake surface water temperatures have warmed rapidly relative to air temperatures, but changes in deepwater temperatures and vertical thermal structure are still largely unknown. We have compiled the most comprehensive data set to date of long-term (1970–2009) summertime vertical temperature profiles in lakes across the world to examine trends and drivers of whole-lake vertical thermal structure. We found significant increases in surface water temperatures across lakes at an average rate of + 0.37 °C decade−1, comparable to changes reported previously for other lakes, and similarly consistent trends of increasing water column stability (+ 0.08 kg m−3 decade−1). In contrast, however, deepwater temperature trends showed little change on average (+ 0.06 °C decade−1), but had high variability across lakes, with trends in individual lakes ranging from − 0.68 °C decade−1 to + 0.65 °C decade−1. The variability in deepwater temperature trends was not explained by trends in either surface water temperatures or thermal stability within lakes, and only 8.4% was explained by lake thermal region or local lake characteristics in a random forest analysis. These findings suggest that external drivers beyond our tested lake characteristics are important in explaining long-term trends in thermal structure, such as local to regional climate patterns or additional external anthropogenic influences.

scholarly journals Effects of Fire and Large Herbivores on Canopy Nitrogen in a Tallgrass Prairie

2019 ◽  
Vol 11 (11) ◽  
pp. 1364 ◽  
Author(s):  
Bohua Ling ◽  
Edward J. Raynor ◽  
Douglas G. Goodin ◽  
Anthony Joern
Keyword(s):  
Spatial Variability ◽  
Nitrogen Content ◽  
Tallgrass Prairie ◽  
High Nitrogen Content ◽  
High Nitrogen ◽  
Grazing History ◽  
One Year ◽  
Canopy Nitrogen

This study analyzed the spatial heterogeneity of grassland canopy nitrogen in a tallgrass prairie with different treatments of fire and ungulate grazing (long-term bison grazing vs. recent cattle grazing). Variogram analysis was applied to continuous remotely sensed canopy nitrogen images to examine the spatial variability in grassland canopies. Heterogeneity metrics (e.g., the interspersion/juxtaposition index) were calculated from the categorical canopy nitrogen maps and compared among fire and grazing treatments. Results showed that watersheds burned within one year had higher canopy nitrogen content and lower interspersions of high-nitrogen content patches than watersheds with longer fire intervals, suggesting an immediate and transient fire effect on grassland vegetation. In watersheds burned within one year, high-intensity grazing reduced vegetation density, but promoted grassland heterogeneity, as indicated by lower canopy nitrogen concentrations and greater interspersions of high-nitrogen content patches at the grazed sites than at the ungrazed sites. Variogram analyses across watersheds with different grazing histories showed that long-term bison grazing created greater spatial variability of canopy nitrogen than recent grazing by cattle. This comparison between bison and cattle is novel, as few field experiments have evaluated the role of grazing history in driving grassland heterogeneity. Our analyses extend previous research of effects from pyric herbivory on grassland heterogeneity by highlighting the role of grazing history in modulating the spatial and temporal distribution of aboveground nitrogen content in tallgrass prairie vegetation using a remote sensing approach. The comparison of canopy nitrogen properties and the variogram analysis of canopy nitrogen distribution provided by our study are useful for further mapping grassland canopy features and modeling grassland dynamics involving interplays among fire, large grazers, and vegetation communities.

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