scholarly journals Impacts of regional climate and teleconnection on hydrological change in the Bosten Lake Basin, arid region of northwestern China

2017 ◽  
Vol 9 (1) ◽  
pp. 74-88 ◽  
Author(s):  
Huaijun Wang ◽  
Yingping Pan ◽  
Yaning Chen

Abstract This investigation examined effects of climate change, measured as annual, seasonal, and monthly air temperature and precipitation from 1958 to 2010, on water resources (i.e., runoff) in the Bosten Lake Basin. Additionally, teleconnections of hydrological changes to large-scale circulation indices including El Nino Southern Oscillation (ENSO), Arctic Oscillation (AO), North Atlantic Oscillation (NAO), Tibetan High (XZH), westerly circulation index (WI), and northern hemisphere polar vortex area index (VPA) were analyzed in our study. The results showed the following. (1) Annual and seasonal air temperature increased significantly in the Bosten Lake Basin. Precipitation exhibited an increasing trend, while the significance was less than that of temperature. Abrupt changes were observed in 1996 in mountain temperature and in 1985 in plain temperature. (2) Runoff varied in three stages, decreasing before 1986, increasing from 1987 to 2003, and decreasing after 2003. (3) Precipitation and air temperature have significant impacts on runoff. The hydrological processes in the Bosten Lake Basin were (statistically) significantly affected by the northern hemisphere polar vortex area index (VPA) and the Tibetan High (XZH). The results of this study are good indicators of local climate change, which can enhance human mitigation of climate warming in the Bosten Lake Basin.

2019 ◽  
Vol 12 (8) ◽  
pp. 3725-3743 ◽  
Author(s):  
Allison C. Michaelis ◽  
Gary M. Lackmann ◽  
Walter A. Robinson

Abstract. We present multi-seasonal simulations representative of present-day and future environments using the global Model for Prediction Across Scales – Atmosphere (MPAS-A) version 5.1 with high resolution (15 km) throughout the Northern Hemisphere. We select 10 simulation years with varying phases of El Niño–Southern Oscillation (ENSO) and integrate each for 14.5 months. We use analyzed sea surface temperature (SST) patterns for present-day simulations. For the future climate simulations, we alter present-day SSTs by applying monthly-averaged temperature changes derived from a 20-member ensemble of Coupled Model Intercomparison Project phase 5 (CMIP5) general circulation models (GCMs) following the Representative Concentration Pathway (RCP) 8.5 emissions scenario. Daily sea ice fields, obtained from the monthly-averaged CMIP5 ensemble mean sea ice, are used for present-day and future simulations. The present-day simulations provide a reasonable reproduction of large-scale atmospheric features in the Northern Hemisphere such as the wintertime midlatitude storm tracks, upper-tropospheric jets, and maritime sea-level pressure features as well as annual precipitation patterns across the tropics. The simulations also adequately represent tropical cyclone (TC) characteristics such as strength, spatial distribution, and seasonal cycles for most Northern Hemisphere basins. These results demonstrate the applicability of these model simulations for future studies examining climate change effects on various Northern Hemisphere phenomena, and, more generally, the utility of MPAS-A for studying climate change at spatial scales generally unachievable in GCMs.


Water ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 144 ◽  
Author(s):  
Rui Zhang ◽  
Zongxue Xu ◽  
Depeng Zuo ◽  
Chunguang Ban

Climate change poses potential challenges to sensitive areas, such as high-elevation regions. The Yarlung Zangbo River (YLZR) basin is located in the southeast of the Qinghai-Tibetan Plateau. It contains large amounts of snow and numerous glaciers that are vulnerable to climate change. Based on daily observational data at 17 meteorological stations in and around the YLZR basin during 1957–2015, the variability of precipitation, air temperature, and streamflow were analyzed. The nonparametric Mann–Kendall test, Sen’s slope estimate method, cross wavelet transform (XWT), and wavelet coherence (WTC) were used to identify the annual seasonal trends. the abrupt changes of precipitation and air temperature, and their associations with large-scale circulation. The results showed that the YLZR basin experienced an overall rapid warming and wetting during the study period, with an average warming rate of 0.33 °C/10 a and wetting rate of 4.25 mm/10a, respectively. Abrupt change points in precipitation and air temperature occurred around the 1970s and 1990s, respectively. The abrupt change points of three hydrological stations occurred around the late 1960s and the late 1990s, respectively. The precipitation, annual average temperature, and the streamflow of the three hydrological stations were negatively correlated with the Pacific decadal oscillation (PDO) and the multivariate El Niño-Southern Oscillation (ENSO) index (MEI), reaching a significant level of 0.05.


2021 ◽  
Author(s):  
Sally Jahn ◽  
Elke Hertig

<p>Air pollution and heat events present two major health risks, both already independently posing a significant threat to human health and life. High levels of ground-level ozone (O<sub>3</sub>) and air temperature often coincide due to the underlying physical relationships between both variables. The most severe health outcome is in general associated with the co-occurrence of both hazards (e.g. Hertig et al. 2020), since concurrent elevated levels of temperature and ozone concentrations represent a twofold exposure and can lead to a risk beyond the sum of the individual effects. Consequently, in the current contribution, a compound approach considering both hazards simultaneously as so-called ozone-temperature (o-t-)events is chosen by jointly analyzing elevated ground-level ozone concentrations and air temperature levels in Europe.</p><p>Previous studies already point to the fact that the relationship of underlying synoptic and meteorological drivers with one or both of these health stressors as well as the correlation between both variables vary with the location of sites and seasons (e.g. Otero et al. 2016; Jahn, Hertig 2020). Therefore, a hierarchical clustering analysis is applied to objectively divide the study domain in regions of homogeneous, similar ground-level ozone and temperature characteristics (o-t-regions). Statistical models to assess the synoptic and large-scale meteorological mechanisms which represent main drivers of concurrent o-t-events are developed for each identified o-t-region.</p><p>Compound elevated ozone concentration and air temperature events are expected to become more frequent due to climate change in many parts of Europe (e.g. Jahn, Hertig 2020; Hertig 2020). Statistical projections of potential frequency shifts of compound o-t-events until the end of the twenty-first century are assessed using the output of Earth System Models (ESMs) from the sixth phase of the Coupled Model Intercomparison Project (CMIP6).</p><p><em>Hertig, E. (2020) Health-relevant ground-level ozone and temperature events under future climate change using the example of Bavaria, Southern Germany. Air Qual. Atmos. Health. doi: 10.1007/s11869-020-00811-z</em></p><p><em>Hertig, E., Russo, A., Trigo, R. (2020) Heat and ozone pollution waves in Central and South Europe- characteristics, weather types, and association with mortality. Atmosphere. doi: 10.3390/atmos11121271</em></p><p><em>Jahn, S., Hertig, E. (2020) Modeling and projecting health‐relevant combined ozone and temperature events in present and future Central European climate. Air Qual. Atmos. Health. doi: 10.1007/s11869‐020‐009610</em></p><p><em>Otero N., Sillmann J., Schnell J.L., Rust H.W., Butler T. (2016) Synoptic and meteorological drivers of extreme ozone concentrations over Europe. Environ Res Lett. doi: 10.1088/ 1748-9326/11/2/024005</em></p>


2015 ◽  
Vol 8 ◽  
pp. 542
Author(s):  
José Edson Florentino de Morais ◽  
Thieres George Freire da Silva ◽  
Marcela Lúcia Barbosa ◽  
Wellington Jairo da Silva Diniz ◽  
Carlos André Alves de Souza ◽  
...  

O aumento na ocorrência de eventos climáticos extremos nas últimas décadas é uma forte evidência das mudanças climáticas. Em regiões Semiáridas, onde a pressão de desertificação tem se intensificado, são esperadas diminuição da disponibilidade de água e maior ocorrência de períodos seca, e, consequentemente, efeitos na resposta fisiológica das plantas. Assim, objetivou-se analisar os impactos dos cenários de mudanças climáticas sobre a duração do ciclo fenológico e a demanda de água do sorgo forrageiro e do feijão-caupi cultivados no Estado de Pernambuco. Foram utilizados os valores mensais da normal climatológica brilho solar, temperatura do ar, umidade relativa do ar e velocidade do vento de dez municípios. Considerou-se um aumento de 1,8°C (Cenário B2) e 4,0°C (Cenário A1F1) na temperatura do ar e um decréscimo de 5,0% dos valores absolutos de umidade relativa do ar, além do aumento de 22% na resistência estomática e de 4% no índice de área foliar. Com base nessas informações foram gerados três cenários: situação atual e projeções futuras para B2 e A1F1. Os resultados revelaram uma redução média de 11% (B2) e 20% (A1F1), e de 10% (B2) e 17% (A1F1) na duração do ciclo, e de 4% (B2) e 8% (A1F1), e 2% (B2) e 5% (A1F1) na demanda de água acumulada para o sorgo forrageiro e feijão-caupi, respectivamente. Conclui-se que a magnitude das reduções da duração do ciclo e a demanda de água simulada para as culturas do sorgo forrageiro e do feijão-caupi variaram espaço-temporalmente no Estado de Pernambuco com os cenários de mudanças climáticas.ABSTRACT The increase in the occurrence of extreme weather events in recent decades is a strong evidence of climate change. In semiarid regions, where the pressure of desertification has intensified, are expected to decrease in the availability of water and higher occurrence of drought periods, and, consequently, effects on physiological response of plants. Thus, the objective of analyzing the impacts of climate change scenarios on the duration of phenological cycle and water demand of forage sorghum and cowpea, grown in the State of Pernambuco. Monthly values were used normal climatological solar brightness, air temperature, relative humidity and wind speed of ten municipalities. It was considered an increase of 1.8° C (B2 Scenario) and 4.0° C (A1F1 Scenario) on air temperature and a decrease of 5.0% of the absolute values of relative humidity, in addition to the 22% increase in stomatal resistance and 4% in leaf area index. Based on this information were generated three scenarios: current situation and future projections for B2, A1F1. The results revealed an average reduction of 11% (B2) and 20% (A1F1), and 10% (B2) and 17% (A1F1) for the duration of the cycle, and 4% (B2) and 8% (A1F1), and 2% (B2) and 5% (A1F1) in accumulated water demand for forage sorghum and cowpea, respectively. It is concluded that the magnitude of the reductions in the duration of the cycle and the simulated water demand for crops of forage sorghum and cowpea ranged space-temporarily in the State of Pernambuco with climate change scenarios.


2021 ◽  
Author(s):  
Pallavi Goswami ◽  
Arpita Mondal ◽  
Christoph Rüdiger ◽  
Tim J. Peterson

<p>Large-scale climate processes such as the El Nino Southern Oscillation (ENSO), Indian Ocean Dipole (IOD) and Southern Annular Mode (SAM) influence the hydro-climatology of Southeast Australia (SEA). In the present study, we show that low-flow events in many catchments in SEA are significantly influenced by variability in these climate drivers. Extreme value distributions and Generalised Linear Models (GLMs) are used here to model low-flow characteristics such as intensity, duration and frequency with respect to these climate drivers. Further, we study how the future projections of ENSO, IOD and SAM are likely to evolve under climate change by examining the projected values of their representative indices and how they will impact low-flow events in the region. It is found that the future dry phases of these climate drivers are likely to be more dry than those in the historic period. This in turn is expected to lead to intensification of low-flow events in the future, resulting in lower availability of fresh water during occurrences of the dry phases of these climate drivers. Thus, climate change in the future is expected to significantly influence future low-flow events in the region thereby making it even more crucial for water managers to adequately manage and ensure water availability.</p><p><br>Keywords: low-flows, ENSO, IOD, SAM, Extreme Value Theory, Generalised Linear Models, Southeast Australia, CMIP5, RCP8.5.</p>


2019 ◽  
Author(s):  
Allison C. Michaelis ◽  
Gary M. Lackmann ◽  
Walter A. Robinson

Abstract. We present multi-seasonal simulations representative of present-day and future thermodynamic environments using the global Model for Prediction Across Scales-Atmosphere (MPAS) version 5.1 with high resolution (15 km) throughout the Northern Hemisphere. We select ten simulation years with varying phases of El Niño-Southern Oscillation (ENSO) and integrate each for 14.5 months. We use analysed sea surface temperature (SST) patterns for present-day simulations. For the future climate simulations, we alter present-day SSTs by applying monthly-averaged temperature changes derived from a 20-member ensemble of Coupled Model Intercomparison Project Phase 5 (CMIP5) general circulation models (GCMs) following the Representative Concentration Pathway (RCP) 8.5 emissions scenario. Daily sea ice fields, obtained from the monthly-averaged CMIP5 ensemble mean sea ice, are used for present-day and future simulations. The present-day simulations provide a reasonable reproduction of large-scale atmospheric features in the Northern Hemisphere such as the wintertime midlatitude storm tracks, upper-tropospheric jets, and maritime sea-level pressure features as well as annual precipitation patterns across the tropics. The simulations also adequately represent tropical cyclone (TC) characteristics such as strength, spatial distribution, and seasonal cycles for most of Northern Hemispheric basins. These results demonstrate the applicability of these model simulations for future studies examining climate change effects on various Northern Hemispheric phenomena, and, more generally, the utility of MPAS for studying climate change at spatial scales generally unachievable in GCMs.


2020 ◽  
Vol 33 (24) ◽  
pp. 10743-10754
Author(s):  
Hongdou Fan ◽  
Lin Wang ◽  
Yang Zhang ◽  
Youmin Tang ◽  
Wansuo Duan ◽  
...  

AbstractBased on 36-yr hindcasts from the fifth-generation seasonal forecast system of the European Centre for Medium-Range Weather Forecasts (SEAS5), the most predictable patterns of the wintertime 2-m air temperature (T2m) in the extratropical Northern Hemisphere are extracted via the maximum signal-to-noise (MSN) empirical orthogonal function (EOF) analysis, and their associated predictability sources are identified. The MSN EOF1 captures the warming trend that amplifies over the Arctic but misses the associated warm Arctic–cold continent pattern. The MSN EOF2 delineates a wavelike T2m pattern over the Pacific–North America region, which is rooted in the tropical forcing of the eastern Pacific-type El Niño–Southern Oscillation (ENSO). The MSN EOF3 shows a wavelike T2m pattern over the Pacific–North America region, which has an approximately 90° phase difference from that associated with MSN EOF2, and a loading center over midlatitude Eurasia. Its sources of predictability include the central Pacific-type ENSO and Eurasian snow cover. The MSN EOF4 reflects T2m variability surrounding the Tibetan Plateau, which is plausibly linked to the remote forcing of the Arctic sea ice. The information on the leading predictable patterns and their sources of predictability is further used to develop a calibration scheme to improve the prediction skill of T2m. The calibrated prediction skill in terms of the anomaly correlation coefficient improves significantly over midlatitude Eurasia in a leave-one-out cross-validation, implying a possible way to improve the wintertime T2m prediction in the SEAS5.


2012 ◽  
Vol 6 (4) ◽  
pp. 3317-3348 ◽  
Author(s):  
C. Brutel-Vuilmet ◽  
M. Ménégoz ◽  
G. Krinner

Abstract. The 20th century seasonal Northern Hemisphere land snow cover as simulated by available CMIP5 model output is compared to observations. On average, the models reproduce the observed snow cover extent very well, but the significant trend towards a~reduced spring snow cover extent over the 1979–2005 is underestimated. We show that this is linked to the simulated Northern Hemisphere extratropical land warming trend over the same period, which is underestimated, although the models, on average, correctly capture the observed global warming trend. There is a good linear correlation between hemispheric seasonal spring snow cover extent and boreal large-scale annual mean surface air temperature in the models, supported by available observations. This relationship also persists in the future and is independent of the particular anthropogenic climate forcing scenario. Similarly, the simulated linear correlation between the hemispheric seasonal spring snow cover extent and global mean annual mean surface air temperature is stable in time. However, the sensitivity of the Northern Hemisphere spring snow cover to global mean surface air temperature changes is underestimated at present because of the underestimate of the boreal land temperature change amplification.


2021 ◽  
Author(s):  
Juliana Jaen ◽  
Toralf Renkwitz ◽  
Jorge L. Chau ◽  
Maosheng He ◽  
Peter Hoffmann ◽  
...  

Abstract. Specular meteor radars (SMRs) and partial reflection radars (PRRs) have been observing mesospheric winds for more than a solar cycle over Germany (~54 °N) and northern Norway (~69 °N). This work investigates the mesospheric mean zonal wind and the zonal mean geostrophic zonal wind from the Microwave Limb Sounder (MLS) over these two regions between 2004 and 2020. Our study focuses on the summer when strong planetary waves are absent and the stratospheric and tropospheric conditions are relatively stable. We establish two definitions of the summer length according to the zonal wind reversals: (1) the mesosphere and lower thermosphere summer length (MLT-SL) using SMR and PRR winds, and (2) the mesosphere summer length (M-SL) using PRR and MLS. Under both definitions, the summer begins around April and ends around mid-September. The largest year to year variability is found in the summer beginning in both definitions, particularly at high-latitudes, possibly due to the influence of the polar vortex. At high-latitudes, the year 2004 has a longer summer length compared to the mean value for MLT-SL, as well as 2012 for both definitions. The M-SL exhibits an increasing trend over the years, while MLT-SL does not have a well-defined trend. We explore a possible influence of solar activity, as well as large-scale atmospheric influences (e.g. quasi-biennial oscillations (QBO), El Niño-southern oscillation (ENSO), major sudden stratospheric warming events). We complement our work with an extended time series of 31 years at mid-latitudes using only PRR winds. In this case, the summer length shows a breakpoint, suggesting a non-uniform trend, and periods similar to those known for ENSO and QBO.


Author(s):  
Rasmus Benestad

What are the local consequences of a global climate change? This question is important for proper handling of risks associated with weather and climate. It also tacitly assumes that there is a systematic link between conditions taking place on a global scale and local effects. It is the utilization of the dependency of local climate on the global picture that is the backbone of downscaling; however, it is perhaps easiest to explain the concept of downscaling in climate research if we start asking why it is necessary. Global climate models are our best tools for computing future temperature, wind, and precipitation (or other climatological variables), but their limitations do not let them calculate local details for these quantities. It is simply not adequate to interpolate from model results. However, the models are able to predict large-scale features, such as circulation patterns, El Niño Southern Oscillation (ENSO), and the global mean temperature. The local temperature and precipitation are nevertheless related to conditions taking place over a larger surrounding region as well as local geographical features (also true, in general, for variables connected to weather/climate). This, of course, also applies to other weather elements. Downscaling makes use of systematic dependencies between local conditions and large-scale ambient phenomena in addition to including information about the effect of the local geography on the local climate. The application of downscaling can involve several different approaches. This article will discuss various downscaling strategies and methods and will elaborate on their rationale, assumptions, strengths, and weaknesses. One important issue is the presence of spontaneous natural year-to-year variations that are not necessarily directly related to the global state, but are internally generated and superimposed on the long-term climate change. These variations typically involve phenomena such as ENSO, the North Atlantic Oscillation (NAO), and the Southeast Asian monsoon, which are nonlinear and non-deterministic. We cannot predict the exact evolution of non-deterministic natural variations beyond a short time horizon. It is possible nevertheless to estimate probabilities for their future state based, for instance, on projections with models run many times with slightly different set-up, and thereby to get some information about the likelihood of future outcomes. When it comes to downscaling and predicting regional and local climate, it is important to use many global climate model predictions. Another important point is to apply proper validation to make sure the models give skillful predictions. For some downscaling approaches such as regional climate models, there usually is a need for bias adjustment due to model imperfections. This means the downscaling doesn’t get the right answer for the right reason. Some of the explanations for the presence of biases in the results may be different parameterization schemes in the driving global and the nested regional models. A final underlying question is: What can we learn from downscaling? The context for the analysis is important, as downscaling is often used to find answers to some (implicit) question and can be a means of extracting most of the relevant information concerning the local climate. It is also important to include discussions about uncertainty, model skill or shortcomings, model validation, and skill scores.


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