Pluvial Risk Research Articles

Robust Changes in North America's Hydroclimate Variability and Predictability

AbstractClimate change adaptation planning requires a robust understanding of the projected change in hydroclimate variability and predictability. We use two large ensemble data sets to quantify the projected change in land hydroclimate variability and its potential predictability. Additionally, we use a “reddened El Niño‐Southern Oscillation (ENSO)” framework that partitions annually averaged root‐zone soil moisture variability into ENSO, land surface memory, and internal variability to understand drivers of the changes in hydroclimate variability and predictability. Even when global warming is projected to increase ENSO and its teleconnected precipitation variability over North America, we find that the corresponding change in soil moisture variability is relatively small and even decreases. This counter‐intuitive result occurs since there is also a concurrent projected reduction in land surface memory due to global warming, which leads to reduced year‐to‐year persistence of soil moisture variability. Further, we find that regional mean state land surface (soil moisture) changes primarily drive future drought and pluvial risks, suggesting that infrastructure planning can incorporate robust mean state changes despite uncertainty in the variability projections. For the regions and in the models where the ENSO signal increases, we also find a concomitant shift in the frequency of drought and pluvial events, with higher power on inter‐annual time scales but less power on decadal time scales, enhancing inter‐annual hydroclimate predictability.

Assessing the Governance Context Support for Creating a Pluvial Flood Risk Map with Climate Change Scenarios: The Flemish Subnational Case

Climate change has increased pluvial flood risks in cities around the world. To mitigate floods, pluvial risk maps with climate change scenarios have been developed to help major urban areas adapt to a changing climate. In some cases, subnational governments have played a key role to develop these maps. However, governance research about the role of subnational governments in geospatial data development in urban water transitions has received little attention. To address this gap, this research applies the Governance Assessment Tool as an evaluative framework to increase our understanding of the governance factors that support the development of pluvial flood risk maps at the subnational level. For this research, we selected the region of Flanders in Belgium. This region is considered among the frontrunners when it comes to the creation of a pluvial flood risk map with climate change scenarios. Data have been collected through in-depth interviews with steering committee actors involved in the development process of the map. The research identified that the current governance context is supportive of the creation of the flood risk map. The government of Flanders plays a key role in this process. The most supportive qualities of the governance context are those related to the degree of fragmentation (extent and coherence), while the less supportive ones are those related to the “quest for control” (flexibility and intensity). Under this governance context, government actors play the primary role. The Flemish government led the maps’ creation process and it was supported by the lower governmental levels. As the provincial government was an important actor to increase local participation, collaboration with private and non-governmental actors in the steering committee was more limited. The financial resources were also limited and the process required a continuous development of trust. Yet, the Flemish Environmental Agency, with the use of technology, was able to increase such trust during the process.

Hydroclimate variability in Scandinavia over the last millennium – insights from a climate model–proxy data comparison

Abstract. The integration of climate proxy information with general circulation model (GCM) results offers considerable potential for deriving greater understanding of the mechanisms underlying climate variability, as well as unique opportunities for out-of-sample evaluations of model performance. In this study, we combine insights from a new tree-ring hydroclimate reconstruction from Scandinavia with projections from a suite of forced transient simulations of the last millennium and historical intervals from the CMIP5 and PMIP3 archives. Model simulations and proxy reconstruction data are found to broadly agree on the modes of atmospheric variability that produce droughts–pluvials in the region. Despite these dynamical similarities, large differences between simulated and reconstructed hydroclimate time series remain. We find that the GCM-simulated multi-decadal and/or longer hydroclimate variability is systematically smaller than the proxy-based estimates, whereas the dominance of GCM-simulated high-frequency components of variability is not reflected in the proxy record. Furthermore, the paleoclimate evidence indicates in-phase coherencies between regional hydroclimate and temperature on decadal timescales, i.e., sustained wet periods have often been concurrent with warm periods and vice versa. The CMIP5–PMIP3 archive suggests, however, out-of-phase coherencies between the two variables in the last millennium. The lack of adequate understanding of mechanisms linking temperature and moisture supply on longer timescales has serious implications for attribution and prediction of regional hydroclimate changes. Our findings stress the need for further paleoclimate data–model intercomparison efforts to expand our understanding of the dynamics of hydroclimate variability and change, to enhance our ability to evaluate climate models, and to provide a more comprehensive view of future drought and pluvial risks.

Increased Drought and Pluvial Risk over California due to Changing Oceanic Conditions

Abstract This study evaluates wintertime drought and pluvial risk over California through a Bayesian analysis of the upper and lower quartile of PRISM-based precipitation from 1901 to 2015. Risk is evaluated for different time windows to estimate the impact of interannual and decadal-to-multidecadal Pacific and Atlantic variability [positive and negative phases of ENSO, Pacific decadal oscillation (PDO), and Atlantic multidecadal oscillation (AMO)]. The impact of increasing trends in global sea surface temperature (SST) on drought and pluvial risk is also examined with idealized experimental runs from three climate models [GFDL Atmospheric Model version 2.1 (AM2.1), CCM3, and GFS]. The results show that the influence of oceanic conditions on drought risk in California is significant but has changed with higher risk in the last half century, especially in Southern California. The influence of oceanic conditions on pluvial risk has also been significant, especially during the warm phase of the Pacific Ocean, but increases over the last century are small compared to drought. Results from the idealized climate model experiments show that natural variability likely played a major role in the observed changes in risk, with the global SST increasing trend possibly tempering the increases regionally but not significantly over California. Despite evolving preferential oceanic conditions for a pluvial event during the 2015/16 winter (positive phase of ENSO and PDO), California received an 11% winter precipitation surplus, which was not sufficient for drought recovery. The seasonal and longer-term outlook for negative phases of ENSO and PDO implies that drought risk will be elevated in Southern California for the next decade.

The amplitude of decadal to multidecadal variability in precipitation simulated by state‐of‐the‐art climate models

We assess the magnitude of decadal to multidecadal (D2M) variability in Climate Model Intercomparison Project 5 (CMIP5) simulations that will be used to understand, and plan for, climate change as part of the Intergovernmental Panel on Climate Change's 5th Assessment Report. Model performance on D2M timescales is evaluated using metrics designed to characterize the relative and absolute magnitude of variability at these frequencies. In observational data, we find that between 10% and 35% of the total variance occurs on D2M timescales. Regions characterized by the high end of this range include Africa, Australia, western North America, and the Amazon region of South America. In these areas D2M fluctuations are especially prominent and linked to prolonged drought. D2M fluctuations account for considerably less of the total variance (between 5% and 15%) in the CMIP5 archive of historical (1850–2005) simulations. The discrepancy between observation and model based estimates of D2M prominence reflects two features of the CMIP5 archive. First, interannual components of variability are generally too energetic. Second, decadal components are too weak in several key regions. Our findings imply that projections of the future lack sufficient decadal variability, presenting a limited view of prolonged drought and pluvial risk.