scholarly journals Wintertime precipitation climate of Central Southwest Asia: Diagnostics and forecasting

2021 ◽  
Author(s):  
◽  
Sapna Rana
Keyword(s):  
Large Scale ◽  
Indian Subcontinent ◽  
Temporal Patterns ◽  
Winter Precipitation ◽  
Precipitation Variability ◽  
Human Society ◽  
Southwest Asia ◽  
Precipitation Estimates ◽  
Northwestern Region

<p>Central Southwest Asia (CSWA; 20°–47°N, 40°–85°E) is a water-scarce and a societally vulnerable region, prone to significant variations in precipitation during the winter months of November–April. Wintertime precipitation variations have a direct impact on CSWA's water resources, agricultural productivity, energy use, and human society. Because of the close relationship between climate and human well-being, an improved understanding of winter season precipitation and its variability over CSWA is of critical importance. However, due to multiple regional challenges (e.g. socio-political instability, extreme topographical heterogeneity, poor coverage of in situ stations, and others) analysis of precipitation in this region has been limited.  In an attempt to bridge the existing knowledge gap, this thesis aims to advance our understanding of CSWA's wintertime precipitation climate through three separate, but inter-related studies on 1) evaluation of multi-source gridded precipitation dataset, 2) investigation of spatial and temporal patterns of precipitation and its links with large-scale modes of climate variability, 3) development of a statistical forecast model. Additionally, precipitation evaluation is also relevant to the overlapping and important region of the Indian subcontinent; a detailed seasonal analysis for which is also presented.  First, the performance of several commonly used gridded precipitation products from multiple sources: gauge-based, satellite-derived, and reanalysis is analysed for all four seasons over the Indian Subcontinent. Results show that the degree of uncertainty in all precipitation estimates varies by region (e.g. topographic relief) and the type of precipitation (e.g. convective, orographic). At the seasonal scale, satellite-products perform better, while reanalyses generally overestimate precipitation. Greater discrepancies occur in areas with low gauge densities, owing to which a complete understanding of the accuracy and limitations of precipitation estimates is hampered for the northwestern region of the Indian subcontinent.  In an extension study, ten multi-source precipitation products are evaluated against an ensemble of four gauge-only datasets. This analysis is carried out for CSWA, which also includes the northwestern region of the Indian subcontinent. Spatial and temporal analysis of results shows that GPCC is a suitable observational dataset for studying long-term wintertime precipitation variations over CSWA. The satellite-derived TRMM 3B42-V7 is a potentially reliable alternative to gauge measurements, while the performance of MERRA reanalysis is satisfactory.  Further, the spatial-temporal patterns of wintertime precipitation variability over CSWA are explored. Three leading patterns are identified by empirical orthogonal function (EOF) analysis, and the associated time series are related to global SST and other large-scale atmospheric circulation fields. The leading patterns of winter precipitation are significantly linked with the El Niño–Southern Oscillation (ENSO); East Atlantic–Western Russia (EA-WR); Siberian High; North Pacific Oscillation (NPO); Scandinavian pattern; and the long-term warming of the Indian Ocean SST. The inter-decadal change of relationship between the first-mode of winter precipitation and ENSO is also investigated, which shows that CSWA precipitation variability was closely related to the extratropical EA-WR (tropical ENSO) teleconnection before (after) the 1980's.  Finally, the level and origin of seasonal forecast skill of wintertime precipitation anomalies over CSWA are examined using the statistical method of canonical correlation analysis (CCA). The preceding months’ (September–October) SST is used as predictors, and CCA experiments are performed for two sets of time periods, 1950/51–2014/15 and 1980/81–2014/15. For both prediction periods, the potential source of predictability originates largely from SST variations related to ENSO and the Pacific Decadal Oscillation (PDO). A higher (lower) correlation skill of 0.71 (0.38) is obtained between observations and cross-validated precipitation forecasts for the period 1980/81–2014/15 (1950/51–2014/15); which shows that ENSO played a dominant role in creating skillful predictions for CSWA wintertime precipitation in recent years.</p>

scholarly journals Wintertime precipitation climate of Central Southwest Asia: Diagnostics and forecasting

2021 ◽  
Author(s):  
◽  
Sapna Rana
Keyword(s):  
Large Scale ◽  
Indian Subcontinent ◽  
Temporal Patterns ◽  
Winter Precipitation ◽  
Precipitation Variability ◽  
Human Society ◽  
Southwest Asia ◽  
Precipitation Estimates ◽  
Northwestern Region

<p>Central Southwest Asia (CSWA; 20°–47°N, 40°–85°E) is a water-scarce and a societally vulnerable region, prone to significant variations in precipitation during the winter months of November–April. Wintertime precipitation variations have a direct impact on CSWA's water resources, agricultural productivity, energy use, and human society. Because of the close relationship between climate and human well-being, an improved understanding of winter season precipitation and its variability over CSWA is of critical importance. However, due to multiple regional challenges (e.g. socio-political instability, extreme topographical heterogeneity, poor coverage of in situ stations, and others) analysis of precipitation in this region has been limited.  In an attempt to bridge the existing knowledge gap, this thesis aims to advance our understanding of CSWA's wintertime precipitation climate through three separate, but inter-related studies on 1) evaluation of multi-source gridded precipitation dataset, 2) investigation of spatial and temporal patterns of precipitation and its links with large-scale modes of climate variability, 3) development of a statistical forecast model. Additionally, precipitation evaluation is also relevant to the overlapping and important region of the Indian subcontinent; a detailed seasonal analysis for which is also presented.  First, the performance of several commonly used gridded precipitation products from multiple sources: gauge-based, satellite-derived, and reanalysis is analysed for all four seasons over the Indian Subcontinent. Results show that the degree of uncertainty in all precipitation estimates varies by region (e.g. topographic relief) and the type of precipitation (e.g. convective, orographic). At the seasonal scale, satellite-products perform better, while reanalyses generally overestimate precipitation. Greater discrepancies occur in areas with low gauge densities, owing to which a complete understanding of the accuracy and limitations of precipitation estimates is hampered for the northwestern region of the Indian subcontinent.  In an extension study, ten multi-source precipitation products are evaluated against an ensemble of four gauge-only datasets. This analysis is carried out for CSWA, which also includes the northwestern region of the Indian subcontinent. Spatial and temporal analysis of results shows that GPCC is a suitable observational dataset for studying long-term wintertime precipitation variations over CSWA. The satellite-derived TRMM 3B42-V7 is a potentially reliable alternative to gauge measurements, while the performance of MERRA reanalysis is satisfactory.  Further, the spatial-temporal patterns of wintertime precipitation variability over CSWA are explored. Three leading patterns are identified by empirical orthogonal function (EOF) analysis, and the associated time series are related to global SST and other large-scale atmospheric circulation fields. The leading patterns of winter precipitation are significantly linked with the El Niño–Southern Oscillation (ENSO); East Atlantic–Western Russia (EA-WR); Siberian High; North Pacific Oscillation (NPO); Scandinavian pattern; and the long-term warming of the Indian Ocean SST. The inter-decadal change of relationship between the first-mode of winter precipitation and ENSO is also investigated, which shows that CSWA precipitation variability was closely related to the extratropical EA-WR (tropical ENSO) teleconnection before (after) the 1980's.  Finally, the level and origin of seasonal forecast skill of wintertime precipitation anomalies over CSWA are examined using the statistical method of canonical correlation analysis (CCA). The preceding months’ (September–October) SST is used as predictors, and CCA experiments are performed for two sets of time periods, 1950/51–2014/15 and 1980/81–2014/15. For both prediction periods, the potential source of predictability originates largely from SST variations related to ENSO and the Pacific Decadal Oscillation (PDO). A higher (lower) correlation skill of 0.71 (0.38) is obtained between observations and cross-validated precipitation forecasts for the period 1980/81–2014/15 (1950/51–2014/15); which shows that ENSO played a dominant role in creating skillful predictions for CSWA wintertime precipitation in recent years.</p>

Climate Change Analysis using Satellite Data

2017 ◽  
Vol 14 (1) ◽  
pp. 25-39
Author(s):  
Kamsali Nagaraja Balakrishnan Manikiam
Keyword(s):  
Climate Change ◽  
Satellite Data ◽  
Indian Subcontinent ◽  
Biosphere Reserve ◽  
Soil Condition ◽  
Wave Radiation ◽  
Change Analysis ◽  
Precipitation Estimates ◽  
Quantitative Precipitation Estimates

Recent times have witnessed increasing impact of industrialization and urban growth on environment. In addition, the potential climate changes and possible adverse impacts on the economy and society at large are causing concern. In India, one of the major concerns is the variability of monsoon rainfall and effects on agriculture and water management. The various parameters associated with environment and climate change need to be monitored and analyzed. The effects of global warming on the Indian subcontinent vary from the submergence of low-lying islands, frequent flooding, coastal degradation and melting of glaciers in the Indian Himalayas. Indian satellites INSAT and IRS launched in early 1980s heralded the era of Space observations. The IRS satellites are providing observations of parameters such as land use/cover, forest, water bodies, crops etc. while INSAT provides quantitative products such as Cloud Motion Vectors (CMVs), Quantitative Precipitation Estimates (QPEs), Outgoing Long-wave Radiation (OLR), Vertical Temperature Profiles (VTPRs), Sea Surface Temperature. The satellite data is operationally used for generating long term database on vegetation, soil condition, rainfall, groundwater etc.. Some of the unique studies are Biosphere Reserve Monitoring, Mapping of

scholarly journals Impacts of Pacific SSTs on Atmospheric Circulations Leading to California Winter Precipitation Variability: A Diagnostic Modeling

Atmosphere ◽  
2018 ◽  
Vol 9 (11) ◽  
pp. 455 ◽  
Author(s):  
Boksoon Myoung ◽  
Sang-Wook Yeh ◽  
Jinwon Kim ◽  
Menas Kafatos
Keyword(s):  
Regression Model ◽  
El Niño ◽  
Large Scale ◽  
El Nino ◽  
Southern Oscillation ◽  
Winter Precipitation ◽  
Precipitation Variability ◽  
Tropical Pacific ◽  
Mirror Image ◽  
Western Tropical Pacific

One of the primary meteorological causes of the winter precipitation deficits and droughts in California (CA) is anomalous developments and maintenance of upper-tropospheric ridges over the northeastern Pacific. In order to understand and find the key factors controlling the winter precipitation variability in CA, the present study examines two dominant atmospheric modes of the 500 hPa geopotential height in the Northern Hemisphere using an Empirical Orthogonal Function (EOF) and their associated large-scale circulation patterns for the last 41 winters (1974/75–2014/15). Explaining 17.5% of variability, the second mode (EOF2) shows strong anti-cyclonic circulations in the North Pacific and cyclonic circulations in the eastern USA and mid-latitude North Atlantic, similar to the atmospheric circulation observed in the 2013/14 drought of CA. EOF2 is tightly and significantly correlated with CA winter precipitation. EOF2 is associated with warm western‒cool eastern tropical Pacific, resembling a mirror image of canonical El Niño events. In particular, it is found that, since the mid-1990s, sea surface temperatures (SSTs) in the western tropical Pacific have been more tightly correlated with EOF2 and with the variability of CA precipitation. A diagnostic regression model based on the west‒east SST difference in the tropical Pacific developed for two recent decades (1994/95–2014/15) has been found to capture the slow-moving interannual variability of the CA winter precipitation (about 50%). The regression model performs well, especially for the central and northern CA precipitation, where the impacts of El Niño Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) on precipitation are indecisive. Our results emphasize the significant role of the western tropical Pacific SST forcing in the recent past, and in turn on CA droughts and potentially other precipitation extremes.

scholarly journals Radar-Based Precipitation Climatology in Germany—Developments, Uncertainties and Potentials

Atmosphere ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 217 ◽  
Author(s):  
Jennifer Kreklow ◽  
Björn Tetzlaff ◽  
Benjamin Burkhard ◽  
Gerald Kuhnt
Keyword(s):  
Ground Truth ◽  
Winter Precipitation ◽  
Rain Gauge ◽  
Rain Gauge Data ◽  
Weather Radars ◽  
Hourly Rainfall ◽  
Gauge Data ◽  
Precipitation Estimates ◽  
Quantitative Precipitation Estimates

Precipitation is a crucial driver for many environmental processes and weather radars are capable of providing precipitation information with high spatial and temporal resolution. However, radar-based quantitative precipitation estimates (QPE) are also subject to various potential uncertainties. This study explored the development, uncertainties and potentials of the hourly operational German radar-based and gauge-adjusted QPE called RADOLAN and its reanalyzed radar climatology dataset named RADKLIM in comparison to ground-truth rain gauge data. The precipitation datasets were statistically analyzed across various time scales ranging from annual and seasonal aggregations to hourly rainfall intensities in regard to their capability to map long-term precipitation distribution, to detect low intensity rainfall and to capture heavy rainfall. Moreover, the impacts of season, orography and distance from the radar on long-term precipitation sums were examined in order to evaluate dataset performance and to describe inherent biases. Results revealed that both radar products tend to underestimate total precipitation sums and particularly high intensity rainfall. However, our analyses also showed significant improvements throughout the RADOLAN time series as well as major advances through the climatologic reanalysis regarding the correction of typical radar artefacts, orographic and winter precipitation as well as range-dependent attenuation.

scholarly journals Nesting Effects of Climate and Local Drivers on Long-Term Subalpine Fires in the Alps

2021 ◽  
Author(s):  
Christopher Carcaillet ◽  
Benjamin Boulley ◽  
Frédérique Carcaillet
Keyword(s):  
Biomass Burning ◽  
Large Scale ◽  
Fire History ◽  
Fire Regime ◽  
Western Alps ◽  
Biomass Combustion ◽  
Human Society ◽  
The Holocene ◽  
Soil Charcoal

Abstract Background: The present article questions the relative importance of local- and large-scale processes on the long-term dynamics of fire in the subalpine belt in the western Alps. The study is based on soil charcoal dating and identification, several study sites in contrasting environmental conditions, and sampling of soil charcoal along the elevation gradient of each site. Based on local differences in biomass combustion, we hypothesize that local-scale processes have driven the fire history, while combustion homogeneity supports the hypothesis of the importance of large-scale processes, especially the climate. Results: The results show that biomass burning during the Holocene resulted from the nesting effects of climate, land use, and altitude, but was little influenced by topography (slope exposure: north versus south), soil (dryness, pH, depth), and vegetation. The mid-Holocene (6500–2700 cal BP) was an important period for climatic biomass burning in the subalpine ecosystems of the western Alps, while fires from about 2500 years ago appear much more episodic, prompting us to speculate that human society has played a vital role in their occurrence. Conclusion: Our working hypothesis assuming that the strength of mountain natural and local drivers should offset the effects of regional climate is not validated. The homogeneity of the fire regime between sites thus underscore that climate was the main driver during the Holocene of the western Alps. Long-term subalpine fires are controlled by climate at millennial scale. Local conditions count for little in determining variability at the century scale. The mid-Holocene was a chief period for climatic biomass burning in the subalpine zone, while fires during the late Holocene appear much more episodic, prompting the assumption that societal drivers has exercised key roles on their control.

scholarly journals Unraveling Long-Term Flood Risk Dynamics Across the Murray-Darling Basin Using a Large-Scale Hydraulic Model and Satellite Data

2022 ◽  
Vol 3 ◽  
Author(s):  
Serena Ceola ◽  
Alessio Domeneghetti ◽  
Guy J. P. Schumann
Keyword(s):  
Flood Risk ◽  
Large Scale ◽  
Flood Hazard ◽  
Spatial Scales ◽  
Mitigation Strategies ◽  
Economic Losses ◽  
Human Society ◽  
Murray Darling Basin ◽  
Flooded Areas

River floods are one of the most devastating extreme hydrological events, with oftentimes remarkably negative effects for human society and the environment. Economic losses and social consequences, in terms of affected people and human fatalities, are increasing worldwide due to climate change and urbanization processes. Long-term dynamics of flood risk are intimately driven by the temporal evolution of hazard, exposure and vulnerability. Although needed for effective flood risk management, a comprehensive long-term analysis of all these components is not straightforward, mostly due to a lack of hydrological data, exposure information, and large computational resources required for 2-D flood model simulations at adequately high resolution over large spatial scales. This study tries to overcome these limitations and attempts to investigate the dynamics of different flood risk components in the Murray-Darling basin (MDB, Australia) in the period 1973–2014. To this aim, the LISFLOOD-FP model, i.e., a large-scale 2-D hydrodynamic model, and satellite-derived built-up data are employed. Results show that the maximum extension of flooded areas decreases in time, without revealing any significant geographical transfer of inundated areas across the study period. Despite this, a remarkable increment of built-up areas characterizes MDB, with larger annual increments across not-flooded locations compared to flooded areas. When combining flood hazard and exposure, we find that the overall extension of areas exposed to high flood risk more than doubled within the study period, thus highlighting the need for improving flood risk awareness and flood mitigation strategies in the near future.

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