An overview of climate change in Iran: facts and statistics

Daneshvar, Mohammad Reza Mansouri; Ebrahimi, Majid; Nejadsoleymani, Hamid

doi:10.1186/s40068-019-0135-3

Cited by 201 publications

(78 citation statements)

References 46 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Moreover, understanding soil microbiology along with past climate change can be very valuable to predict effects of future changes. Long-term studies forecast overall reduced precipitation in this region 63 , 64 , suggesting that similar changes in the soil microbiota may develop as already archived in the loess-paleosol sequences under study.…”

Section: Discussionmentioning

confidence: 55%

Evidence for signatures of ancient microbial life in paleosols

Frindte

Lehndorff

Vlaminck

et al. 2020

Sci Rep

View full text Add to dashboard Cite

Loess-paleosol sequences are terrestrial archives of past climate change. They may host traces of ancient microbial life, but little information is available on the recovery of microbial biomarkers from such deposits. We hypothesized that microbial communities in soil horizons up to an age of 127 kyr carry information related to past environments. We extracted DNA from a loess-paleosol sequence near Toshan, Northern Iran, with 26 m thick deposits showing different degrees of soil development, performed quantitative PCR and 16S rRNA gene amplicon sequencing. Periods of soil formation archived within the loess sediment led to higher diversity and bacterial abundance in the paleosol horizons. Community composition fluctuated over the loess-paleosol sequence and was mainly correlated with age and depth, (ADONIS R2 < 0.14, P ≤ 0.002), while responses to paleosol soil traits were weaker. Phyla like Bacteriodetes, Proteobacteria or Acidobacteria were more prevalent in paleosol horizons characterized by intense soil formation, while weakly developed paleosols or loess horizons hosted a higher percentage and diversity of Actinobacteria. Taken together, our findings indicate that the microbial community in loess-paleosol sequences carries signatures of earlier environmental conditions that are preserved until today.

show abstract

Section: Discussionmentioning

confidence: 55%

Evidence for signatures of ancient microbial life in paleosols

Frindte

Lehndorff

Vlaminck

et al. 2020

Sci Rep

View full text Add to dashboard Cite

show abstract

“…The highest precipitation amount occurs near the Caspian Sea, north of Iran. Precipitation amounts along the Zagros and Alborz Mountains are higher than in the other regions [36]. Not surprisingly, the lowest precipitation amount occurs in the desert areas.…”

Section: Spatial and Temporal Distributions Of The Climate Variablesmentioning

confidence: 77%

Improving Princeton Forcing Dataset over Iran Using the Delta-Ratio Method

Zhang

Tang

Liu

et al. 2020

Water

View full text Add to dashboard Cite

In this study, we corrected the bias in the Princeton forcing dataset, i.e., precipitation, maximum and minimum temperatures, and wind speed, by adjusting its long-term mean monthly climatology to match observations for the period 1988–2012 using the delta-ratio method. To this end, we collected meteorological data from 97 stations covering the domain of Iran. We divided Iran into three climatic zones based on the De Martonne classification, i.e., Arid, Humid, and Per-Humid zones, and then applied the delta-ratio method for each climatic zone separately to adjust the bias. After adjustment, the new datasets were compared to the observations in 1958–1987. Results based on four skill scores, including the Nash Sutcliffe efficiency (NSE), percent bias (PBIAS), root-mean-square error (RMSE), and R2, indicate that the adjustment greatly improved the quality of the gridded dataset, specifically, precipitation, maximum temperature, and wind speed. For example, NSE for annual precipitation during the validation time period increased from −0.03 to 0.72, PBIAS reduced from 29.2% to 6.6%, RMSE decreased by 182.44 mm, and R2 increased from 0.06 to 0.75. Assessing the results in different climatic zones of Iran reveals that precipitation improved more significantly in the Per-Humid zone followed by the Humid zone, while maximum temperature improved better in the Arid areas. For wind speed, the values improved comparably in the three climate zones. However, the delta values for monthly minimum temperature calculated during the adjustment time period cannot be applied in the validation time period, due to the fact that the Princeton climate data cannot follow the behavior of minimum temperature during the validation phase. In short, we showed that a simple bias adjustment approach, along with minimum observed station data, can significantly improve the performance of global gridded datasets.

show abstract

“…In the last decades, the Iranian urbanization has potentially changed the Middle East climate by the release of total greenhouse gas emissions nearly to 616,741 million tons of CO 2 (Mansouri Daneshvar et al 2019) and with the high contribution of urbanized people to total population nearly to 70% (Mansouri Daneshvar and Hussein Abadi 2017). Urban expansions in Iran and population growth since the 1970s have influenced to natural land degradation, the variation of surface reflectance, and waste generation concerning climate change effects (Amiri and Eslamian 2010).…”

Section: Introductionmentioning

confidence: 99%

Assessment of urban sprawl effects on regional climate change using a hybrid model of factor analysis and analytical network process in the Mashhad city, Iran

Daneshvar¹,

Rabbani²,

Shirvani

2019

Environ Syst Res

Self Cite

View full text Add to dashboard Cite

Background: Urban sprawl, as an unsustainable urban expansion, relates to direct and indirect impacts on regional climate change in urbanized regions. In this paper, the effect of urban sprawl on regional climate change has been studied using a hybrid factor analysis (FA) and analytical network process (ANP) model in Mashhad city, Iran. The methodology was divided into two main parts based on the identification of 18 urban sprawl characteristics and six climatic parameters during three time-windows of 1996, 2006, and 2016. Results: Based on the FA, a set of chosen sprawl characteristics were reduced into five factors with a maximized total variance of the loading variables and were weighted by ANP super-matrix. Results of urban sprawl index (USI) indicated that Mashhad city had experienced rapid horizontal growth by values from 0.47 to 1.74 within 1996-2016, revealing an indication of unsustainable urban sprawl during the last decades. Based on the correlation test, a positive relation between four climatic parameters (surface temperature, surface long-wave flux, total ozone, and black carbon density) and urban sprawl was observed (R from 0.827 to 0.981). In parallel, a negative relationship between two climatic parameters (total precipitation and convective precipitation) and urban sprawl was estimated (R from − 0.691 to − 0.805). Conclusions:The result confirmed the possible effects of urban sprawl on climatic variations. This outcome relates to a chain of urban sprawl effects on growth of construction, transportation, the assumption of fuels and subsequently high emission of greenhouse gasses such as ozone concentration, long-wave flux, and carbon density in the urban atmosphere.

show abstract

An overview of climate change in Iran: facts and statistics

Cited by 201 publications

References 46 publications

Evidence for signatures of ancient microbial life in paleosols

Evidence for signatures of ancient microbial life in paleosols

Improving Princeton Forcing Dataset over Iran Using the Delta-Ratio Method

Assessment of urban sprawl effects on regional climate change using a hybrid model of factor analysis and analytical network process in the Mashhad city, Iran

Contact Info

Product

Resources

About