Long Term Temperature Trends in Daily Station Data: Australia

2017 ◽  
Author(s):  
Jamal Munshi
Keyword(s):  
Temperature Trends ◽  
Station Data

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 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 Repeat station data compared to a global geomagnetic field model

2013 ◽  
Vol 55 (6) ◽  
Author(s):  
Monika Korte ◽  
Vincent Lesur
Keyword(s):  
Magnetic Field ◽  
Secular Variation ◽  
Global Model ◽  
Time Interval ◽  
Night Time ◽  
Core Field ◽  
Repeat Station ◽  
Station Data ◽  
Long Term Trends

<p>Geomagnetic repeat station surveys with local variometers for improved data reductions have been carried out in Germany for about ten years. For nearly the same time interval the satellites Ørsted and CHAMP have provided a good magnetic field data coverage of the whole globe. Recent global field models based on these satellite data together with geomagnetic observatory data provide an improved description of the core field and secular variation. We use the latest version of the GFZ Reference Internal Magnetic Model to compare the magnetic field evolution predicted by that model between 2001 and 2010 to the independent repeat station data collected over the same time interval in Germany. Estimates of crustal bias at the repeat station locations are obtained as averages of the residuals, and the scatter or trend around each average provides information about influences in the data from field sources not (fully) described by the global model. We find that external magnetic field signal in the order of several nT, including long-term trends, remains both in processed annual mean and quiet night time repeat station data. We conclude that the geomagnetic core field secular variation in this area is described to high accuracy (better than 1 nT/yr) by the global model. Weak long-term trends in the residuals between repeat station data and the model might indicate induced lithospheric anomalies, but more data are necessary for a robust analysis of such signals characterized by very unfavorable signal-to-noise ratio.</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 Validation of Hourly Global Horizontal Irradiance for Two Satellite-Derived Datasets in Northeast Iraq

2018 ◽  
Vol 10 (10) ◽  
pp. 1651 ◽  
Author(s):  
Bikhtiyar Ameen ◽  
Heiko Balzter ◽  
Claire Jarvis ◽  
Etienne Wey ◽  
Claire Thomas ◽  
...  
Keyword(s):  
Climate Data ◽  
Clearness Index ◽  
Clear Sky ◽  
Station Data ◽  
Data Points ◽  
Recorded Data ◽  
Monitoring Service ◽  
Sky Conditions ◽  
Station Location

Several sectors need global horizontal irradiance (GHI) data for various purposes. However, the availability of a long-term time series of high quality in situ GHI measurements is limited. Therefore, several studies have tried to estimate GHI by re-analysing climate data or satellite images. Validation is essential for the later use of GHI data in the regions with a scarcity of ground-recorded data. This study contributes to previous studies that have been carried out in the past to validate HelioClim-3 version 5 (HC3v5) and the Copernicus Atmosphere Monitoring Service, using radiation service version 3 (CRSv3) data of hourly GHI from satellite-derived datasets (SDD) with nine ground stations in northeast Iraq, which have not been used previously. The validation is carried out with station data at the pixel locations and two other data points in the vicinity of each station, which is something that is rarely seen in the literature. The temporal and spatial trends of the ground data are well captured by the two SDDs. Correlation ranges from 0.94 to 0.97 in all-sky and clear-sky conditions in most cases, while for cloudy-sky conditions, it is between 0.51–0.72 and 0.82–0.89 for the clearness index. The bias is negative for most of the cases, except for three positive cases. It ranges from −7% to 4%, and −8% to 3% for the all-sky and clear-sky conditions, respectively. For cloudy-sky conditions, the bias is positive, and differs from one station to another, from 16% to 85%. The root mean square error (RMSE) ranges between 12–20% and 8–12% for all-sky and clear-sky conditions, respectively. In contrast, the RMSE range is significantly higher in cloudy-sky conditions: above 56%. The bias and RMSE for the clearness index are nearly the same as those for the GHI for all-sky conditions. The spatial variability of hourly GHI SDD differs only by 2%, depending on the station location compared to the data points around each station. The variability of two SDDs is quite similar to the ground data, based on the mean and standard deviation of hourly GHI in a month. Having station data at different timescales and the small number of stations with GHI records in the region are the main limitations of this analysis.

scholarly journals Historical variability in Northern Hemisphere spring snow-covered area

1997 ◽  
Vol 25 ◽  
pp. 340-346 ◽  
Author(s):  
Ross D. Brown
Keyword(s):  
Soviet Union ◽  
Great Plains ◽  
Former Soviet Union ◽  
Spring Temperature ◽  
Temperature Trends ◽  
Snow Covered Area ◽  
Covered Area ◽  
Short Period ◽  
Snow Cover Duration

Observed and reconstructed snow-cover duration data from stations covering southern Canada, the Great Plains, the former Soviet Union and China were used to reconstruct spring snow-covered area over North America (NA) and Eurasia from 1915 to 1985. A combination of nine regions from NA and five from Eurasia were able to explain 81% and 67%, respectively, of the variance in satellite-derived sprint; snow-covered area (SCA) for each continent. The results suggested sprint; SCA had decreased significantly in Eurasia this century, but there was no evidence of a similar long-term decrease in NA spring SCA. Considerable caution should be used when interpreting these results because of the short period of calibration, and because of the less-than-optimal distribution of station data. Nonetheless, the reconstructed results are consistent with observed spring-temperature trends, which show a significant increase over Eurasia, but none Over NA.

Long term water temperature trends in Austrian rivers

1995 ◽  
Vol 40 (1) ◽  
pp. 83-96 ◽  
Author(s):  
B. W. WEBB ◽  
F. NOBILIS
Keyword(s):  
Water Temperature ◽  
Temperature Trends
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