Variability and Predictability of Central Asia River Flows: Antecedent Winter Precipitation and Large-Scale Teleconnections

2008 ◽  
Vol 9 (6) ◽  
pp. 1334-1349 ◽  
Author(s):  
Mathew A. Barlow ◽  
Michael K. Tippett
Keyword(s):  
Climate Variability ◽  
Central Asia ◽  
Moisture Transport ◽  
Large Scale ◽  
River Flow ◽  
Regional Scale ◽  
Warm Season ◽  
Cold Season ◽  
River Flows ◽  
Syr Darya

Abstract Warm season river flows in central Asia, which play an important role in local water resources and agriculture, are shown to be closely related to the regional-scale climate variability of the preceding cold season. The peak river flows occur in the warm season (April–August) and are highly correlated with the regional patterns of precipitation, moisture transport, and jet-level winds of the preceding cold season (November–March), demonstrating the importance of regional-scale variability in determining the snowpack that eventually drives the rivers. This regional variability is, in turn, strongly linked to large-scale climate variability and tropical sea surface temperatures (SSTs), with the circulation anomalies influencing precipitation through changes in moisture transport. The leading pattern of regional climate variability, as resolved in the operationally updated NCEP–NCAR reanalysis, can be used to make a skillful seasonal forecast for individual river flow stations. This ability to make predictions based on regional-scale climate data is of particular use in this data-sparse area of the world. The river flow is considered in terms of 24 stations in Uzbekistan and Tajikistan available for 1950–85, with two additional stations available for 1958–2003. These stations encompass the headwaters of the Amu Darya and Syr Darya, two of the main rivers of central Asia and the primary feeders of the catastrophically shrinking Aral Sea. Canonical correlation analysis (CCA) is used to forecast April–August flows based on the period 1950–85; cross-validated correlations exceed 0.5 for 10 of the stations, with a maximum of 0.71. Skill remains high even after 1985 for two stations withheld from the CCA: the correlation for 1986–2002 for the Syr Darya at Chinaz is 0.71, and the correlation for the Amu Darya at Kerki is 0.77. The forecast is also correlated to the normalized difference vegetation index (NDVI); maximum values exceed 0.8 at 8-km resolution, confirming the strong connection between hydrology and growing season vegetation in the region and further validating the forecast methodology.

Linkages of surface air temperature variations over Central Asia with large-scale climate patterns

2021 ◽  
Author(s):  
Yuanhuang Zhuang ◽  
Jingyong Zhang ◽  
Lingyun Wu
Keyword(s):  
Central Asia ◽  
Air Temperature ◽  
Large Scale ◽  
Warm Season ◽  
Surface Air Temperature ◽  
Cold Season ◽  
Temperature Variations ◽  
The North ◽  
Climate Patterns ◽  
Air Temperature Variations

Abstract In this study, we investigate the dominant modes of surface air temperature variations of the cold season (from November through to the next March) and the warm season (from May to September) over Central Asia, and their associations with large-scale climate patterns for the period of 1979–2016. The first two modes of the cold-season surface air temperature (CSAT) over Central Asia, obtained by empirical orthogonal function (EOF) analysis, feature the mono-pole structure and the north-south dipole pattern, respectively. For the warm-season surface air temperature (WSAT), the leading two EOF modes are characterized by the homogenous structure and the northwest-southeast seesaw pattern, respectively. Further analysis indicates that the large-scale atmospheric circulation anomalies play key roles in the CSAT and WSAT variations over Central Asia. The CSAT variation over Central Asia is closely related with the Scandinavia pattern (SCAND), the Arctic Oscillation (AO) and the North Atlantic Oscillation (NAO), while the WSAT variation is tightly tied to the East Atlantic/Western Russia pattern (EAWR) and the NAO. These large-scale climate patterns tend to cause the CSAT and WSAT anomalies over Central Asia via their effects on regional geopotential heights, warming advections and other processes. Our findings are expected to facilitate the improvement of understanding and predicting the CSAT and WSAT variations over Central Asia.

scholarly journals Variability of the Cold Season Climate in Central Asia. Part II: Hydroclimatic Predictability

2019 ◽  
Vol 32 (18) ◽  
pp. 6015-6033 ◽  
Author(s):  
Lars Gerlitz ◽  
Eva Steirou ◽  
Christoph Schneider ◽  
Vincent Moron ◽  
Sergiy Vorogushyn ◽  
...  
Keyword(s):  
Central Asia ◽  
Snow Cover ◽  
Large Scale ◽  
Cold Season ◽  
Hadley Cell ◽  
Quasi Biennial Oscillation ◽  
Large Variability ◽  
Forecast Performance ◽  
Eurasian Snow Cover ◽  
Eurasian Snow

Abstract Central Asia (CA) is subjected to a large variability of precipitation. This study presents a statistical model, relating precipitation anomalies in three subregions of CA in the cold season (November–March) with various predictors in the preceding October. Promising forecast skill is achieved for two subregions covering 1) Uzbekistan, Turkmenistan, Kyrgyzstan, Tajikistan, and southern Kazakhstan and 2) Iran, Afghanistan, and Pakistan. ENSO in October is identified as the major predictor. Eurasian snow cover and the quasi-biennial oscillation further improve the forecast performance. To understand the physical mechanisms, an analysis of teleconnections between these predictors and the wintertime circulation over CA is conducted. The correlation analysis of predictors and large-scale circulation indices suggests a seasonal persistence of tropical circulation modes and a dynamical forcing of the westerly circulation by snow cover variations over Eurasia. An EOF analysis of pressure and humidity patterns allows separating the circulation variability over CA into westerly and tropical modes and confirms that the identified predictors affect the respective circulation characteristics. Based on the previously established weather type classification for CA, the predictors are investigated with regard to their effect on the regional circulation. The results suggest a modification of the Hadley cell due to ENSO variations, with enhanced moisture supply from the Arabian Gulf during El Niño. They further indicate an influence of Eurasian snow cover on the wintertime Arctic Oscillation (AO) and Northern Hemispheric Rossby wave tracks. Positive anomalies favor weather types associated with dry conditions, while negative anomalies promote the formation of a quasi-stationary trough over CA, which typically occurs during positive AO conditions.

scholarly journals Multi-decadal river flow variations in France

2014 ◽  
Vol 18 (2) ◽  
pp. 691-708 ◽  
Author(s):  
J. Boé ◽  
F. Habets
Keyword(s):  
Soil Moisture ◽  
Large Scale ◽  
River Flow ◽  
Decadal Variability ◽  
Internal Variability ◽  
Spring Precipitation ◽  
Main Mode ◽  
River Flows ◽  
Decadal Variations ◽  
The Impact

Abstract. In this article, multi-decadal variations in the French hydroclimate are investigated, with a specific focus on river flows. Based on long observed series, it is shown that river flows in France generally exhibit large multi-decadal variations in the instrumental period (defined in this study as the period from the late 19th century to the present), especially in spring. Differences of means between 21 yr periods of the 20th century as large as 40% are indeed found for many gauging stations. Multi-decadal spring river flow variations are associated with variations in spring precipitation and temperature. These multi-decadal variations in precipitation are themselves found to be driven by large-scale atmospheric circulation, more precisely by a multi-decadal oscillation in a sea level pressure dipole between western Europe and the eastern Atlantic. It is suggested that the Atlantic Multidecadal Variability, the main mode of multi-decadal variability in the North Atlantic–Europe sector, controls those variations in large-scale circulation and is therefore the main ultimate driver of multi-decadal variations in spring river flows. Potential multi-decadal variations in river flows in other seasons, and in particular summer, are also noted. As they are not associated with significant surface climate anomalies (i.e. temperature, precipitation) in summer, other mechanisms are investigated based on hydrological simulations. The impact of climate variations in spring on summer soil moisture, and the impact of soil moisture in summer on the runoff-to-precipitation ratio, could potentially play a role in multi-decadal summer river flow variations. The large amplitude of the multi-decadal variations in French river flows suggests that internal variability may play a very important role in the evolution of river flows during the next decades, potentially temporarily limiting, reversing or seriously aggravating the long-term impacts of anthropogenic climate change.

A climate classification: Mediterranean, monsoon and westerlies climates

2020 ◽  
Author(s):  
Xin-Gang Dai ◽  
Ping Wang
Keyword(s):  
Tibetan Plateau ◽  
Central Asia ◽  
Moisture Transport ◽  
Seasonal Cycle ◽  
Large Scale ◽  
Mediterranean Climate ◽  
Climate Classification ◽  
Dry Land ◽  
Temperature And Precipitation ◽  
Wet Climate

<p>This study aims to develop a large-scale climate classification for investigating the mechanisms of global climate formation in the surface. There are three types of large-scale climates, i.e., monsoon, Mediterranean and westerlies, corresponding respectively to collocation of temperature and precipitation at in-phase, anti-phase and out of phase, during seasonal cycle. The first one is called proper collocation, and the latter two are named as improper collocation, hereafter. The collocations are coupled with different seasonal moisture transport pattern with moisture divergence. Northward/southward moisture transport accompanies a moisture convergence/divergence with more/less precipitation in the season leading to different climate type. As an example, the climate around Tibetan Plateau can be attributed to four regimes, i.e., East Asia monsoon, South Asia monsoon, Central Asia and westerlies regimes, despite of the Köppen climate classification. The Central Asia regime refers to the dry climate in middle and southern part of the area, while the dry land belt with the westerlies regime extends from northern Central Asia throughout the northwestern China. The proper collocation between temperature and precipitation leads to a warm-wet climate over monsoon zones in warm season (May-October), whereas the improper one leads a hot-dry climate in Mediterranean climate areas and the dry land with the westerlies climate regime. By contrast, a mild-wet climate is in Mediterranean or quasi-Mediterranean climate areas in comparison with cold-dry climate in Asian monsoon zone during cold season (November to April). The improper collocation results in land degradation or even desertification in Mediterranean climate areas and the dry land with the westerlies regime with insufficient precipitation and over-evenly distribution of the precipitation during seasonal cycle. The improper collocation is actually made by improper dynamical and thermal dynamical collocation in regional moisture circulation associated with seasonal change of mid-latitude stationary waves in wave number and phase, which is virtually forced by large mountains and land-sea thermal contrast in the surface. Besides, analysis manifests that there exists mutually engagement between the seasonal changes in some properties of the mean moisture flows over monsoon and non-monsoon areas across Tibetan Plateau in Eurasian continent. It implies a dynamical coupling existed in large-scale moisture patterns over the earth surface.</p><p>Keywords: Large-scale climate classification, monsoon, westerlies, Mediterranean climate, Tibetan Plateau</p>

scholarly journals Proxy-Based Northern Hemisphere Surface Temperature Reconstructions: Sensitivity to Method, Predictor Network, Target Season, and Target Domain

2005 ◽  
Vol 18 (13) ◽  
pp. 2308-2329 ◽  
Author(s):  
S. Rutherford ◽  
M. E. Mann ◽  
T. J. Osborn ◽  
K. R. Briffa ◽  
P D. Jones ◽  
...  
Keyword(s):  
Northern Hemisphere ◽  
Large Scale ◽  
Warm Season ◽  
Cold Season ◽  
Target Domain ◽  
Proxy Data ◽  
Mean Temperature ◽  
Reconstructed Temperature ◽  
Temperature Reconstructions ◽  
Methodological Considerations

Abstract Results are presented from a set of experiments designed to investigate factors that may influence proxy-based reconstructions of large-scale temperature patterns in past centuries. The factors investigated include 1) the method used to assimilate proxy data into a climate reconstruction, 2) the proxy data network used, 3) the target season, and 4) the spatial domain of the reconstruction. Estimates of hemispheric-mean temperature are formed through spatial averaging of reconstructed temperature patterns that are based on either the local calibration of proxy and instrumental data or a more elaborate multivariate climate field reconstruction approach. The experiments compare results based on the global multiproxy dataset used by Mann and coworkers, with results obtained using the extratropical Northern Hemisphere (NH) maximum latewood tree-ring density set used by Briffa and coworkers. Mean temperature reconstructions are compared for the full NH (Tropics and extratropics, land and ocean) and extratropical continents only, withvarying target seasons (cold-season half year, warm-season half year, and annual mean). The comparisons demonstrate dependence of reconstructions on seasonal, spatial, and methodological considerations, emphasizing the primary importance of the target region and seasonal window of the reconstruction. The comparisons support the generally robust nature of several previously published estimates of NH mean temperature changes in past centuries and suggest that further improvements in reconstructive skill are most likely to arise from an emphasis on the quality, rather than quantity, of available proxy data.

scholarly journals “Beyond Weather Regimes”: Descriptors Monitoring Atmospheric Centers of Action. A case study for Aotearoa New Zealand

2021 ◽  
pp. 1-50
Author(s):  
Benjamin Pohl ◽  
Andrew Lorrey ◽  
Andrew Sturman ◽  
Hervé Quénol ◽  
James Renwick ◽  
...  
Keyword(s):  
New Zealand ◽  
Climate Variability ◽  
Large Scale ◽  
Scale Effects ◽  
Southern Oscillation ◽  
Regional Scale ◽  
Future Research ◽  
Weather Regimes ◽  
Aotearoa New Zealand

AbstractThis paper introduces a set of descriptors applied to weather regimes, that allow for a detailed monitoring of the location and intensity of their atmospheric centers of action (e.g. troughs and ridges) and the gradients between them, when applicable. Descriptors are designed to document the effect of climate variability and change in modulating the character of daily weather regimes, rather than merely their occurrence statistics.As a case study, the methodology is applied to Aotearoa New Zealand (ANZ), using ERA5 ensemble reanalysis data for the period 1979-2019. Here, we analyze teleconnections between the regimes and their descriptors, and large-scale climate variability. Results show a significant modulation of centers of action by the phase of the Southern Annular Mode, with a strong relationship identified with the latitude of atmospheric ridges. Significant associations with El Niño Southern Oscillation are also identified. Modes of large-scale variability have a stronger influence on the regimes’ intrinsic features than their occurrence. This demonstrates the usefulness of such descriptors, which help understand the relationship between mid-latitude transient perturbations and large-scale modes of climate variability.In future research, this methodological framework will be applied to analyze (i) low-frequency changes in weather regimes under climate change, in line with the southward shift of storm tracks, and (ii) regional-scale effects on the climate of ANZ, resulting from interaction with its topography.

scholarly journals Combined Effects of Impervious Surface Change and Large-Scale Afforestation on the Surface Urban Heat Island Intensity of Beijing, China Based on Remote Sensing Analysis

2020 ◽  
Vol 12 (23) ◽  
pp. 3906
Author(s):  
Na Yao ◽  
Conghong Huang ◽  
Jun Yang ◽  
Cecil C. Konijnendijk van den Bosch ◽  
Lvyi Ma ◽  
...  
Keyword(s):  
Urban Heat Island ◽  
Large Scale ◽  
Forest Cover ◽  
Warm Season ◽  
Cold Season ◽  
Combined Effects ◽  
Heat Island ◽  
Plain Area ◽  
Urban Heat ◽  
Surface Urban Heat Island

Urban heat island (UHI) attenuation is an essential aspect for maintaining environmental sustainability at a local, regional, and global scale. Although impervious surfaces (IS) and green spaces have been confirmed to have a dominant effect on the spatial differentiation of the urban land surface temperature (LST), comprehensive temporal and quantitative analysis of their combined effects on LST and surface urban heat island intensity (SUHII) changes is still partly lacking. This study took the plain area of Beijing, China as an example. Here, rapid urbanization and a large-scale afforestation project have caused distinct IS and vegetation cover changes within a small range of years. Based on 8 scenes of Landsat 5 TM/7ETM/8OLI images (30 m × 30 m spatial resolution), 920 scenes of EOS-Aqua-MODIS LST images (1 km × 1 km spatial resolution), and other data/information collected by different approaches, this study characterized the interrelationship of the impervious surface area (ISA) dynamic, forest cover increase, and LST and SUHII changes in Beijing’s plain area during 2009–2018. An innovative controlled regression analysis and scenario prediction method was used to identify the contribution of ISA change and afforestation to SUHII changes. The results showed that percent ISA and forest cover increased by 6.6 and 10.0, respectively, during 2009–2018. SUHIIs had significant rising tendencies during the decade, according to the time division of warm season days (summer days included) and cold season nights (winter nights included). LST changes during warm season days responded positively to a regionalized ISA increase and negatively to a regionalized forest cover increase. However, during cold season nights, LST changes responded negatively to a slight regionalized ISA increase, but positively to an extensive regionalized ISA increase, and LST variations responded negatively to a regionalized forest cover increase. The effect of vegetation cooling was weaker than ISA warming on warm season days, but the effect of vegetation cooling was similar to that of ISA during cold season nights. When it was assumed that LST variations were only caused by the combined effects of ISA changes and the planting project, it was found that 82.9% of the SUHII rise on warm season days (and 73.6% on summer days) was induced by the planting project, while 80.6% of the SUHII increase during cold season nights (and 78.9% during winter nights) was caused by ISA change. The study presents novel insights on UHI alleviation concerning IS and green space planning, e.g., the importance of the joint planning of IS and green spaces, season-oriented UHI mitigation, and considering the thresholds of regional IS expansion in relation to LST changes.

scholarly journals Trends for snow cover and river flows in the Pamirs (Central Asia)

2012 ◽  
Vol 9 (1) ◽  
pp. 29-64 ◽  
Author(s):  
P. Chevallier ◽  
B. Pouyaud ◽  
M. Mojaïsky ◽  
M. Bolgov ◽  
O. Olsson ◽  
...  
Keyword(s):  
Soviet Union ◽  
Central Asia ◽  
Snow Cover ◽  
River Flow ◽  
Water Cycle ◽  
High Sensitivity ◽  
Aral Sea ◽  
Mountain Range ◽  
River Flows ◽  
The Soviet Union

Abstract. In the often discussed Aral Sea basin (Central Asia), water availability depends essentially on the high mountains located in its eastern part, especially from the Pamir Alay Range where the Vakhsh and Pyandj Rivers, the main tributaries of the Amu Darya River, flow. In this region, the cryosphere, glaciers, and snow cover significantly impact the water cycle and the flow regime, which could be deeply modified by climate change. The present study, part of a project funded by the EU FP6, analyzes the hydrological situation in six benchmark basins covering areas between 1800 and 8400 km2, essentially located in Tajikistan, with a variety of topographical situations, precipitation amounts, and glacierized areas. Four types of parameter are discussed: temperature, glaciers, snow cover, and river flows. Two time periods are considered: (i) a long time series ending in the 1990s with the collapse of the Soviet Union and based on field observations and data collection; (ii) a May 2000 to May 2002 interval, using scarce monitored data and satellite information to follow snow cover dynamics. The results confirm the global homogeneous trend of temperature increase in the mountain range and its impacts on the surface water regimes. Concerning the snow cover, significant differences are noted regarding the location, the elevation, the orientation and the morphology of the respective basins. Finally the expected changes in the flow river regime are regulated by the combination of the snow cover dynamics and the increasing trend of the air temperature. It confirms the high sensitivity of this region to the warming as identified by the 4rd IPCC Assessment Report.

scholarly journals Tropical Cyclone Landfall Frequency and Large-Scale Environmental Impacts along Karstic Coastal Regions (Yucatan Peninsula, Mexico)

2020 ◽  
Vol 10 (17) ◽  
pp. 5815
Author(s):  
Victor H. Rivera-Monroy ◽  
Luis M. Farfán ◽  
Luis Brito-Castillo ◽  
Jorge Cortés-Ramos ◽  
Eduardo González-Rodríguez ◽  
...  
Keyword(s):  
Large Scale ◽  
Vegetation Change ◽  
Yucatan Peninsula ◽  
Regional Scale ◽  
Warm Season ◽  
Slow Motion ◽  
Eastern Coast ◽  
Environmental Damage ◽  
Chl A ◽  
Yucatán Peninsula

Tropical cyclones (TCs) are natural systems that develop over ocean basins and are key components of the atmospheric activity during the warm season. However, there are still knowledge gaps about the combined positive and negative TC impacts on the structure and function of coastal socio-ecosystems. Using remote sensing tools, we analyzed the frequency, trajectory, and intensity of 1894 TCs from 1851–2019 to identify vulnerable “hotspots” across the Yucatan Peninsula (YP), Mexico. A total of 151 events hit the YP, with 96% of landings on the eastern coast. We focused on three major hurricanes (Emily and Wilma, 2005; Dean, 2007) and one tropical storm (Stan, 2005) to determine the impacts on cumulative precipitation, vegetation change, and coastal phytoplankton (Chl-a) distribution across the YP. Despite a short inland incursion, Wilma’s environmental damage was coupled to strong winds (157–241 km/h), slow motion (4–9 km/h), and heavy precipitation (up to 770 mm). Because of an extensive footprint, Wilma caused more vegetation damage (29%) than Dean (20%), Emily (7%), and Stan (2%). All TCs caused a Chl-a increase associated to submarine discharge and upwelling off the peninsula coastlines. Disaster risk along the coast underscores negative economic impacts and positive ecological benefits at the regional scale.

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