Sensitivity of river discharge to ENSO

El Nino Southern Oscillation (ENSO) has significant impacts on streamflows around the world. While many studies have assessed correlations, an assessment of the magnitude of this impact is lacking, and little is known of ENSO's impact on extreme discharges. We use a daily discharge dataset to provide a global assessment of the sensitivity of annual mean and flood discharges to ENSO, and a gridded climate dataset to assess the global impact of ENSO on precipitation and temperature. We find that, on average, for the stations studied ENSO has a greater impact on annual high-flow events than on mean annual discharge, especially in the extra-tropics. The quantification of ENSO impacts provides relevant information for water-management, allowing the identification of problem areas and providing a basis for risk assessments. Copyright 2010 by the American Geophysical Union

River salinity variations in response to discharge: examples from the western United States during the early 1900s

Major controls on river salinity (total dissolved solids) in the western United States are climate, geology, and human activity. Climate, in general, influences soil-river salinity via salt-balance variations. When climate becomes wetter, river discharge increases and soil-river salinity decreases; when climate becomes drier river discharge decreases and soil-river salinity increases. This study characterizes the river salinity response to discharge using statistical-dynamic methods. An exploratory analysis of river salinity, using early 1900s water quality surveys in the western United States, shows much river salinity variability is in response to storm and annual discharge. Presumably this is because river discharge is largely supported by surface flow

The species diversity × fire severity relationship is hump-shaped in semiarid yellow pine and mixed conifer forests

The combination of direct human influences and the effects of climate change are resulting in altered ecological disturbance regimes, and this is especially the case for wildfires. Many regions that historically experienced low–moderate severity fire regimes are seeing increased area burned at high severity as a result of interactions between high fuel loads and climate warming with a number of negative ecological effects. While ecosystem impacts of altered fire regimes have been examined in the literature, little is known of the effects of changing fire regimes on forest understory plant diversity even though understory taxa comprise the vast majority of forest plant species and play vital roles in overall ecosystem function. We examined understory plant diversity across gradients of wildfire severity in eight large wildfires in yellow pine and mixed conifer temperate forests of the Sierra Nevada, California, USA. We found a generally unimodal hump-shaped relationship between local (alpha) plant diversity and fire severity. High-severity burning resulted in lower local diversity as well as some homogenization of the flora at the regional scale. Fire severity class, post-fire litter cover, and annual precipitation were the best predictors of understory species diversity. Our research suggests that increases in fire severity in systems historically characterized by low and moderate severity fire may lead to plant diversity losses. These findings indicate that global patterns of increasing fire size and severity may have important implications for biodiversity

Climate, snow, and soil moisture data set for the Tuolumne and Merced river watersheds, California, USA

We present hourly climate data to force land surface process models and assessments over the Merced and Tuolumne watersheds in the Sierra Nevada, California, for the water year 2010–2014 period. Climate data (38 stations) include temperature and humidity (23), precipitation (13), solar radiation (8), and wind speed and direction (8), spanning an elevation range of 333 to 2987&thinsp;m. Each data set contains raw data as obtained from the source (Level 0), data that are serially continuous with noise and nonphysical points removed (Level 1), and, where possible, data that are gap filled using linear interpolation or regression with a nearby station record (Level 2). All stations chosen for this data set were known or documented to be regularly maintained and components checked and calibrated during the period. Additional time-series data included are available snow water equivalent records from automated stations (8) and manual snow courses (22), as well as distributed snow depth and co-located soil moisture measurements (2–6) from four locations spanning the rain–snow transition zone in the center of the domain. Spatial data layers pertinent to snowpack modeling in this data set are basin polygons and 100&thinsp;m resolution rasters of elevation, vegetation type, forest canopy cover, tree height, transmissivity, and extinction coefficient. All data are available from online data repositories (https://doi.org/10.6071/M3FH3D).</p

Dynamical origin of low-frequency variability in a highly nonlinear midlatitude coupled model

Author Posting. © American Meteorological Society 2006. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Climate 19 (2006): 6391–6408, doi:10.1175/JCLI3976.1.A novel mechanism of decadal midlatitude coupled variability, which crucially depends on the nonlinear dynamics of both the atmosphere and the ocean, is presented. The coupled model studied involves quasigeostrophic atmospheric and oceanic components, which communicate with each other via a constant-depth oceanic mixed layer. A series of coupled and uncoupled experiments show that the decadal coupled mode is active across parameter ranges that allow the bimodality of the atmospheric zonal flow to coexist with oceanic turbulence. The latter is most intense in the regions of inertial recirculation (IR). Bimodality is associated with the existence of two distinct anomalously persistent zonal-flow modes, which are characterized by different latitudes of the atmospheric jet stream. The IR reorganizations caused by transitions of the atmosphere from its high- to low-latitude state and vice versa create sea surface temperature anomalies that tend to induce transition to the opposite atmospheric state. The decadal–interdecadal time scale of the resulting oscillation is set by the IR adjustment; the latter depends most sensitively on the oceanic bottom drag. The period T of the nonlinear oscillation is 7–25 yr for the range of parameters explored, with the most realistic parameter values yielding T ≈ 20 yr. Aside from this nonlinear oscillation, an interannual Rossby wave mode is present in all coupled experiments. This coupled mode depends neither on atmospheric bimodality, nor on ocean eddy dynamics; it is analogous to the mode found previously in a channel configuration. Its time scale in the model with a closed ocean basin is set by cross-basin wave propagation and equals 3–5 yr for a basin width comparable with the North Atlantic.This research was supported by NSF Grant OCE-02-221066 (all coauthors) and DOE Grant DE-FG-03-01ER63260 (MG and SK)

How Close Do We Live to Water? A Global Analysis of Population Distance to Freshwater Bodies

Traditionally, people have inhabited places with ready access to fresh water. Today, over 50% of the global population lives in urban areas, and water can be directed via tens of kilometres of pipelines. Still, however, a large part of the world's population is directly dependent on access to natural freshwater sources. So how are inhabited places related to the location of freshwater bodies today? We present a high-resolution global analysis of how close present-day populations live to surface freshwater. We aim to increase the understanding of the relationship between inhabited places, distance to surface freshwater bodies, and climatic characteristics in different climate zones and administrative regions. Our results show that over 50% of the world's population lives closer than 3 km to a surface freshwater body, and only 10% of the population lives further than 10 km away. There are, however, remarkable differences between administrative regions and climatic zones. Populations in Australia, Asia, and Europe live closest to water. Although populations in arid zones live furthest away from freshwater bodies in absolute terms, relatively speaking they live closest to water considering the limited number of freshwater bodies in those areas. Population distributions in arid zones show statistically significant relationships with a combination of climatic factors and distance to water, whilst in other zones there is no statistically significant relationship with distance to water. Global studies on development and climate adaptation can benefit from an improved understanding of these relationships between human populations and the distance to fresh water

Warming of Central European lakes and their response to the 1980s climate regime shift

Lake surface water temperatures (LSWTs) are sensitive to atmospheric warming and have previously been shown to respond to regional changes in the climate. Using a combination of in situ and simulated surface temperatures from 20 Central European lakes, with data spanning between 50 and ∼100 years, we investigate the long-term increase in annually averaged LSWT. We demonstrate that Central European lakes are warming most in spring and experience a seasonal variation in LSWT trends. We calculate significant LSWT warming during the past few decades and illustrate, using a sequential t test analysis of regime shifts, a substantial increase in annually averaged LSWT during the late 1980s, in response to an abrupt shift in the climate. Surface air temperature measurements from 122 meteorological stations situated throughout Central Europe demonstrate similar increases at this time. Climatic modification of LSWT has numerous consequences for water quality and lake ecosystems. Quantifying the response of LSWT increase to large-scale and abrupt climatic shifts is essential to understand how lakes will respond in the future