Bringing Statistical Learning Machines Together for Hydro-Climatological Predictions - Case Study for Sacramento San Joaquin River Basin, California

Study region: Sacramento San Joaquin River Basin, California Study focus: The study forecasts the streamflow at a regional scale within SSJ river basin with largescale climate variables. The proposed approach eliminates the bias resulting from predefined indices at regional scale. The study was performed for eight unimpaired streamflow stations from 1962–2016. First, the Singular Valued Decomposition (SVD) teleconnections of the streamflow corresponding to 500 mbar geopotential height, sea surface temperature, 500 mbar specific humidity (SHUM500), and 500 mbar U-wind (U500) were obtained. Second, the skillful SVD teleconnections were screened non-parametrically. Finally, the screened teleconnections were used as the streamflow predictors in the non-linear regression models (K-nearest neighbor regression and data-driven support vector machine). New hydrological insights: The SVD results identified new spatial regions that have not been included in existing predefined indices. The nonparametric model indicated the teleconnections of SHUM500 and U500 being better streamflow predictors compared to other climate variables. The regression models were capable to apprehend most of the sustained low flows, proving the model to be effective for drought-affected regions. It was also observed that the proposed approach showed better forecasting skills with preprocessed large scale climate variables rather than using the predefined indices. The proposed study is simple, yet robust in providing qualitative streamflow forecasts that may assist water managers in making policy-related decisions when planning and managing watersheds

Relationship between Ocean-Atmospheric Climate Variables and Regional Streamflow of the Conterminous United States

Understanding the interconnections between oceanic-atmospheric climate variables and regional streamflow of the conterminous United States may aid in improving regional long lead-time streamflow forecasting. The current research evaluates the time-lagged relationship between streamflow of six geographical regions defined from National Climate Assessment and sea surface temperature (SST), 500-mbar geopotential height (Z500), 500-mbar specific humidity (SH500), and 500-mbar east-west wind (U500) of the Pacific and the Atlantic Ocean using singular value decomposition (SVD). The spatio-temporal correlation between streamflow and SST was developed first from SVD and thus obtained correlation was later associated with Z500, SH500, and U500 separately to evaluate the coupled interconnections between the climate variables. Furthermore, the associations between regional streamflow and the El Niño Southern Oscillation (ENSO), Pacific Decadal Oscillation, and Atlantic Multidecadal Oscillation were evaluated using the derivatives of continuous wavelet transform. Regional SVD analysis revealed significant teleconnection between several regions and climate variables. The warm phase of equatorial SST had shown a stronger correlation with the majority of streamflow. Both SVD and wavelet analyses concluded that the streamflow variability of the regions in close proximity to the Pacific Ocean was strongly associated with the ENSO. Improved knowledge of teleconnection of climate variables with regional streamflow variability may help in regional water management and streamflow prediction studies

Data Mining Climate Variability as an Indicator of U.S. Natural Gas

Anomalously cold winters with extreme storms strain natural gas (NG) markets due to heightened demand for heating and electricity generation. While extended weather forecasting has become an indicator for NG management, seasonal (2–3 month) prediction could mitigate the impact of extreme winters on the NG market for consumers and industry. Interrelated climate patterns of ocean and atmospheric circulation anomalies exhibit characteristics useful for developing effective seasonal outlooks of NG storage and consumption due to their influence on the persistence and intensity of extreme winter weather in North America. This study explores the connection between the Pacific-North American climate systems and the NG market in the U.S., connecting macro-scale oceanic and atmospheric processes to regional NG storage and consumption. Western Pacific sea surface temperatures and atmospheric pressure patterns describe significant variation in seasonal NG storage and consumption. Prediction of these coupled climate processes is useful for estimating NG storage and consumption; this could facilitate economic adaptation toward extreme winter weather conditions. Understanding the implicated impact of climate variability on NG is a crucial step toward economic adaptation to climate change

Winter Euro-Atlantic Climate Modes: Future Scenarios From a CMIP6 Multi-Model Ensemble

Dominant Euro-Atlantic modes of large-scale atmospheric variability significantly affect interannual-to-decadal Euro-Mediterranean climate fluctuations, especially in winter. Here, we investigate the robustness of historical and projected state and variability of such modes in a CMIP6 multi-model ensemble of historical and ssp585 future scenario simulations, focusing on the winter season. Results show overall good skills of the historical ensemble to reproduce the observed temporal, spectral and distributional properties of all considered modes. At the end of the 21st Century the ssp585 ensemble yields non-significant distributional changes for NAO, EAWR, and SCA indices and a transition to a baroclinic structure for EA, with persistent positive anomalies in the mid-troposphere enhancing globally-driven warming over the Euro-Mediterranean region. The hemispheric spatial correlation patterns with temperature and precipitation significantly change for all modes, that is, we observe a significant modulation of the teleconnections associated with each index

Understanding the characteristics of droughts over Eastern Africa in past and future climates

Drought poses a threat to socio-economic activities across eastern Africa and its river basins. While there are indications that global warming may continue to enhance evaporation and intensify droughts at all scales, most drought projections over eastern Africa are based on rainfall alone and are limited to meteorological droughts. The present study combines rainfall and Potential Evapotranspiration (PET) to examine the characteristics of meteorological and hydrological droughts in present and future climates at the regional and river basin scales. To accomplish that we have applied five objectives; i) Study the temporal and spatial characteristics of eastern Africa droughts modes, ii) Investigate how some atmospheric teleconnections influence the characteristics of the Africa droughts modes, iii) Examine the influence of 1.5°C and 2°C global warming levels on drought modes in eastern Africa under two future climate scenarios, RCP 4.5 and RCP8.5 iv) Assess how increases in global warming will influence drought characteristics over eastern African river basins. v) Examine the potential impacts of climate change and land use change on water availability in the Rufiji River basin (RRB), Tanzania, with an emphasis of hydrological droughts in this basin. Different types of datasets, including gridded and station observation datasets, regional climate model simulations (CORDEX: Coordinated Regional Climate Downscaling Experiment) and hydrological simulations (SWAT: Soil and Water Assessment Tool), were analysed for the study. The meteorological drought were characterised using two indices (i.e. Standardized Precipitation Evapotranspiration Index, SPEI; Standardized Precipitation Index, SPI) at 3- and 12-month scales, while the hydrological droughts were characterised using four indices (i.e. soil water index, SWI; Surface Runoff Index, RFI; Water Yield Index, WYI; and Stream Flow index, SFI). The study combined principal component analysis (PCA) with wavelet analysis to identify the spatio-temporal structure of four dominant drought modes over the region. It also used wavelet coherence to quantify the influence of four atmospheric teleconnections (i.e. El Niño Southern Oscillation, ENSO; Indian Ocean Dipole, IOD; Tropical Atlantic Dipole Index, TADI; and Quasi-Biennial Oscillation, QBO) on the drought modes. The study also projects the characteristics of future droughts over eastern Africa and its major river basins at different global warming levels (GWLs). Series of hydrological simulations were used to assess the sensitivity of future droughts to four land use change scenarios (i.e. increase in forestry, shrubs, cropland and agriculture) over the Rufiji River Basin (RRB), a prominent river basin in eastern Africa. Although eastern Africa have been documented with several drought studies, the application of a combination of PCA, Wavelet analysis, wavelet coherence and Self Organizing Maps provides more comprehensive representation of droughts in the region using SPEI/SPI derived from both models and observations The results of the study show that the four drought modes, which have their core areas over different parts of eastern Africa, account for more than 45% of drought variability in the region. All the drought modes are strongly coupled with either ENSO or IOD indices (or both); but, in addition, one of the modes is also strongly coupled with the TADI. CORDEX models give a realistic simulation of the relevant climate variables for calculating drought indices over eastern Africa and the river basins. However, the ensemble mean struggles to reproduce the spatial distribution and frequency of drought intensity in the region. The CORDEX simulations project no changes in the spatial structure of the drought modes but suggest an increase in SPEI drought intensity and frequency over the hotspots of the drought modes and elsewhere in the region. The magnitude of the increase, which varies over the drought mode hotspots, increases with increasing GWLs. The projections also show that the increase in intensity and frequency of drought can be attributed more to increased PET than to reduced precipitation. In contrast to the SPEI projection, the SPI projection shows a weak change in intensity and frequency of droughts, and the magnitude of the increase does not vary with the GWLs. Over the river basins, the SPEI projections are more robust than the SPI projections. Over the RRB, the future projections of some hydrological drought indices (i.e. RFI and SFI) follow the change in the SPEI projections, while others (i.e. SWI and WYI) follow that of SPI. Among the four land use scenarios considered, only forestry and shrubs show a substantial change in the hydrological drought indices. The results of the study thus give valuable insight into the characteristics of future droughts in eastern Africa and provide a useful guide to the effectiveness of using land cover to reduce the severity of hydrological droughts over river basins in the region. However, resolution of CORDEX dataset (50km, i.e. 0.44deg) could be among the potential limitation as it is too low to capture the influence of local-scale processes (e.g. sea breeze, mountain induced circulations) on drought over the region