scholarly journals Modeling Long-Term Temporal Variation of Dew Formation in Jordan and Its Link to Climate Change

Water ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 2186 ◽  
Author(s):  
Nahid Atashi ◽  
Dariush Rahimi ◽  
Mustafa Al Kuisi ◽  
Anwar Jiries ◽  
Henri Vuollekoski ◽  
...  
Keyword(s):  
Climate Change ◽  
Mediterranean Climate ◽  
Climate Change Impacts ◽  
Dust Storms ◽  
Arid Climate ◽  
Seasonal Patterns ◽  
Climate Zones ◽  
The Past ◽  
Dew Formation

In this study, we performed model simulations to investigate the spatial, seasonal, and annual dew yield during 40 years (1979–2018) at ten locations reflecting the variation of climate and environmental conditions in Jordan. In accordance with the climate zones in Jordan, the dew formation had distinguished characteristics features with respect to the yield, seasonal variation, and spatial variation. The highest water dew yield (an overall annual mean cumulative dew yield as high as 88 mm) was obtained for the Mountains Heights Plateau, which has a Mediterranean climate. The least dew yield (as low as 19 mm) was obtained in Badia, which has an arid climate. The dew yield had a decreasing trend in the past 40 years due to climate change impacts such as increased desertification and the potential of sand and dust storms in the region. In addition, increased anthropogenic air pollution slows down the conversion of vapor to liquid phase change, which also impacts the potential of dew formation. The dew yield showed three distinguished seasonal patterns reflecting the three climates in Jordan. The Mountains Heights Plateau (Mediterranean climate) has the highest potential for dew harvesting (especially during the summer) than Badia (semi-arid climate).

scholarly journals A 1-km global dataset of historical (1979–2017) and future (2020–2100) Köppen-Geiger climate classification and bioclimatic variables

2021 ◽  
Author(s):  
Diyang Cui ◽  
Shunlin Liang ◽  
Dongdong Wang ◽  
Zheng Liu
Keyword(s):  
Climate Change ◽  
Regional Scale ◽  
Climate Change Impacts ◽  
Global Scale ◽  
Climatic Conditions ◽  
Distribution Models ◽  
Climate Classification ◽  
Climate Zones ◽  
Bioclimatic Variables

Abstract. The Köppen-Geiger climate classification scheme provides an effective and ecologically meaningful way to characterize climatic conditions and has been widely applied in climate change studies. The Köppen-Geiger climate maps currently available are limited by relatively low spatial resolution, poor accuracy, and noncomparable time periods. Comprehensive assessment of climate change impacts requires a more accurate depiction of fine-grained climatic conditions and continuous long-term time coverage. Here, we present a series of improved 1-km Köppen-Geiger climate classification maps for ten historical periods in 1979–2017 and four future periods in 2020–2099 under RCP2.6, 4.5, 6.0, and 8.5. The historical maps are derived from multiple downscaled observational datasets and the future maps are derived from an ensemble of bias-corrected downscaled CMIP5 projections. In addition to climate classification maps, we calculate 12 bioclimatic variables at 1-km resolution, providing detailed descriptions of annual averages, seasonality, and stressful conditions of climates. The new maps offer higher classification accuracy and demonstrate the ability to capture recent and future projected changes in spatial distributions of climate zones. On regional and continental scales, the new maps show accurate depictions of topographic features and correspond closely with vegetation distributions. We also provide a heuristic application example to detect long-term global-scale area changes of climate zones. This high-resolution dataset of Köppen-Geiger climate classification and bioclimatic variables can be used in conjunction with species distribution models to promote biodiversity conservation and to analyze and identify recent and future interannual or interdecadal changes in climate zones on a global or regional scale. The dataset referred to as KGClim, is publicly available at http://doi.org/10.5281/zenodo.4546140 for historical climate and http://doi.org/10.5281/zenodo.4542076 for future climate.

scholarly journals Epidemic malaria and warmer temperatures in recent decades in an East African highland

2010 ◽  
Vol 278 (1712) ◽  
pp. 1661-1669 ◽  
Author(s):  
David Alonso ◽  
Menno J. Bouma ◽  
Mercedes Pascual
Keyword(s):  
Climate Change ◽  
East Africa ◽  
Nonlinear Response ◽  
Climate Change Impacts ◽  
Human Model ◽  
Recent Past ◽  
East African ◽  
Highly Nonlinear ◽  
The Impact

Climate change impacts on malaria are typically assessed with scenarios for the long-term future. Here we focus instead on the recent past (1970–2003) to address whether warmer temperatures have already increased the incidence of malaria in a highland region of East Africa. Our analyses rely on a new coupled mosquito–human model of malaria, which we use to compare projected disease levels with and without the observed temperature trend. Predicted malaria cases exhibit a highly nonlinear response to warming, with a significant increase from the 1970s to the 1990s, although typical epidemic sizes are below those observed. These findings suggest that climate change has already played an important role in the exacerbation of malaria in this region. As the observed changes in malaria are even larger than those predicted by our model, other factors previously suggested to explain all of the increase in malaria may be enhancing the impact of climate change.

scholarly journals Satellites, Self-reports, and Submersion: Exposure to Floods in Bangladesh

2015 ◽  
Vol 105 (5) ◽  
pp. 232-236 ◽  
Author(s):  
Raymond Guiteras ◽  
Amir Jina ◽  
A. Mushfiq Mobarak
Keyword(s):  
Climate Change ◽  
Economic Activity ◽  
Climate Change Impacts ◽  
Objective Data ◽  
Short Term ◽  
Temperature And Precipitation ◽  
Flood Exposure ◽  
Self Reports ◽  
Term Variation

A burgeoning “Climate-Economy” literature has uncovered many effects of changes in temperature and precipitation on economic activity, but has made considerably less progress in modeling the effects of other associated phenomena, like natural disasters. We develop new, objective data on floods, focusing on Bangladesh. We show that rainfall and self-reported exposure are weak proxies for true flood exposure. These data allow us to study adaptation, giving accurate measures of both long-term averages and short term variation in exposure. This is important in studying climate change impacts, as people will not only experience new exposures, but also experience them differently.

Assessment of alpine summit flora in Kashmir Himalaya and its implications for long-term monitoring of climate change impacts

2020 ◽  
Vol 17 (8) ◽  
pp. 1974-1988
Author(s):  
Maroof Hamid ◽  
Anzar Ahmad Khuroo ◽  
Akhtar Hussain Malik ◽  
Rameez Ahmad ◽  
Chandra Prakash Singh
Keyword(s):  
Climate Change ◽  
Climate Change Impacts ◽  
Kashmir Himalaya ◽  
Long Term Monitoring ◽  
Term Monitoring

scholarly journals Statistics and Analysis of the Relations between Rainstorm Floods and Earthquakes

2016 ◽  
Vol 2016 ◽  
pp. 1-13
Author(s):  
Baodeng Hou ◽  
Yongxiang Wu ◽  
Jianhua Wang ◽  
Kai Wu ◽  
Weihua Xiao
Keyword(s):  
Climate Change ◽  
Input Data ◽  
Computational Results ◽  
Occurrence Time ◽  
The Past ◽  
The Earth ◽  
Water Vapors ◽  
Transmission Zone ◽  
Chinese Scholars

The frequent occurrence of geophysical disasters under climate change has drawn Chinese scholars to pay their attention to disaster relations. If the occurrence sequence of disasters could be identified, long-term disaster forecast could be realized. Based on the Earth Degassing Effect (EDE) which is valid, this paper took the magnitude, epicenter, and occurrence time of the earthquake, as well as the epicenter and occurrence time of the rainstorm floods as basic factors to establish an integrated model to study the correlation between rainstorm floods and earthquakes. 2461 severe earthquakes occurred in China or within 3000 km from China and the 169 heavy rainstorm floods occurred in China over the past 200+ years as the input data of the model. The computational results showed that although most of the rainstorm floods have nothing to do with the severe earthquakes from a statistical perspective, some floods might relate to earthquakes. This is especially true when the earthquakes happen in the vapor transmission zone where rainstorms lead to abundant water vapors. In this regard, earthquakes are more likely to cause big rainstorm floods. However, many cases of rainstorm floods could be found after severe earthquakes with a large extent of uncertainty.

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