Precipitation in a warming world: Assessing projected hydro-climate changes in California and other Mediterranean climate regions.

In most Mediterranean climate (MedClim) regions around the world, global climate models (GCMs) consistently project drier futures. In California, however, projections of changes in annual precipitation are inconsistent. Analysis of daily precipitation in 30 GCMs reveals patterns in projected hydrometeorology over each of the five MedClm regions globally and helps disentangle their causes. MedClim regions, except California, are expected to dry via decreased frequency of winter precipitation. Frequencies of extreme precipitation, however, are projected to increase over the two MedClim regions of the Northern Hemisphere where projected warming is strongest. The increase in heavy and extreme precipitation is particularly robust over California, where it is only partially offset by projected decreases in low-medium intensity precipitation. Over the Mediterranean Basin, however, losses from decreasing frequency of low-medium-intensity precipitation are projected to dominate gains from intensifying projected extreme precipitation. MedClim regions are projected to become more sub-tropical, i.e. made dryer via pole-ward expanding subtropical subsidence. California's more nuanced hydrological future reflects a precarious balance between the expanding subtropical high from the south and the south-eastward extending Aleutian low from the north-west. These dynamical mechanisms and thermodynamic moistening of the warming atmosphere result in increased horizontal water vapor transport, bolstering extreme precipitation events

Precipitation regime change in Western North America: The role of Atmospheric Rivers.

Daily precipitation in California has been projected to become less frequent even as precipitation extremes intensify, leading to uncertainty in the overall response to climate warming. Precipitation extremes are historically associated with Atmospheric Rivers (ARs). Sixteen global climate models are evaluated for realism in modeled historical AR behavior and contribution of the resulting daily precipitation to annual total precipitation over Western North America. The five most realistic models display consistent changes in future AR behavior, constraining the spread of the full ensemble. They, moreover, project increasing year-to-year variability of total annual precipitation, particularly over California, where change in total annual precipitation is not projected with confidence. Focusing on three representative river basins along the West Coast, we show that, while the decrease in precipitation frequency is mostly due to non-AR events, the increase in heavy and extreme precipitation is almost entirely due to ARs. This research demonstrates that examining meteorological causes of precipitation regime change can lead to better and more nuanced understanding of climate projections. It highlights the critical role of future changes in ARs to Western water resources, especially over California

Spatial and temporal patterns of sea surface chlorophyll concentration and environmental forcing in the southern European Atlantic

Phytoplankton biomass dynamic integrates information about the characteristics of the pelagic ecosystem. Temporal and spatial patterns respond to physical processes. Also, phytoplankton abundance and its temporal dynamic largely determine the structure and dynamics of the food web. The southern European Atlantic (48 ºN – 36 ºS) presents differences in continental margin orientation, upwelling intensity, river runoff, a semi-enclosed oceanic domain (Bay of Biscay), and open oceanic waters to the west. Sea surface chlorophyll concentration (SSChl) monthly averages (from satellites) from 1998 to 2012 were analysed at 4x4 km resolution by Empirical Orthogonal Functions. The study area was regionalized according to rotated EOFs and temporal modes were used to resume the SSChl temporal variability in each region. The environmental forcing of temporal modes was analysed against environmental variables by means of Canonical Correspondence Analysis. More than 50% of the variability in oceanic regions was captured by the seasonal signal, with differences in the timing of the spring bloom and with the shape of the seasonal signal related with the latitudinal gradient and the ‘stagnation effect’ of the Bay of Biscay. In French and western Iberian shelves seasonality represented 50%. The difference between shelf and oceanic regions was due to mesoscale processes in shelf areas; i.e. river runoff in the French shelf and coastal upwelling in the western Iberian shelf. Shelf mesoscale processes impose short frequency variability on to the seasonal cycle and increase SSChl levels. The influence that these patterns of spatial and temporal dynamics have on the structure and dynamics of the rest of the food web can be perceived on the spatial patterns of fisheries catches

Interannual prediction of the Paraná River

Interannual‐to‐decadal predictability of the Paraná river in South America is investigated by extracting near‐cyclic components in summer‐season streamflows at Corrientes over the period 1904–1997. It is found that oscillatory components with periods of about 2–5, 8 and 17 years are accompanied by statistically significant changes in monthly streamflow. Autoregressive predictive models are constructed for each component. Cross‐validated categorical hindcasts based on the 8‐yr predicted component are found to yield some skill up to four years in advance for below‐average flows. A prediction based upon the 8‐ and 17‐yr components including data up to 1999 suggests increased probability of below‐average flows until 2006

El Niño Modulations Over The Past Seven Centuries (Letter to the editor)

postprin

Epochs of Phase Coherence between ENSO and Indian Monsoon

We present a modern method used in nonlinear time series analysis to investigate the relation of two oscillating systems with respect to their phases, independently of their amplitudes. We study the difference of the phase dynamics between El Niño/Southern Oscillation (ENSO) and the Indian Monsoon on inter‐annual time scales. We identify distinct epochs, especially two intervals of phase coherence, 1886–1908 and 1964–1980, corroborating earlier findings from a new point of view. A significance test shows that the coherence is very unlikely to be the result of stochastic fluctuations. We also detect so far unknown periods of coupling which are invisible to linear methods. These findings suggest that the decreasing correlation during the last decades might be a typical epoch of the ENSO/Monsoon system having occurred repeatedly. The high time resolution of the method enables us to present an interpretation of how volcanic radiative forcing could cause the coupling. us to present an interpretation of how volcanic radiative forcing could cause the coupling

Predicting and Downscaling ENSO Impacts on Intraseasonal Precipitation Statistics in California: The 1997/98 Event

Three long-range forecasting methods have been evaluated for prediction and downscaling of seasonal and intraseasonal precipitation statistics in California. Full-statistical, hybrid-dynamical–statistical and full-dynamical approaches have been used to forecast El Niño–Southern Oscillation (ENSO)–related total precipitation, daily precipitation frequency, and average intensity anomalies during the January–March season. For El Niño winters, the hybrid approach emerges as the best performer, while La Niña forecasting skill is poor. The full-statistical forecasting method features reasonable forecasting skill for both La Niña and El Niño winters. The performance of the full-dynamical approach could not be evaluated as rigorously as that of the other two forecasting schemes. Although the full-dynamical forecasting approach is expected to outperform simpler forecasting schemes in the long run, evidence is presented to conclude that, at present, the full-dynamical forecasting approach is the least viable of the three, at least in California. The authors suggest that operational forecasting of any intraseasonal temperature, precipitation, or streamflow statistic derivable from the available records is possible now for ENSO-extreme years

Operational forecasting of daily summer maximum and minimum temperatures in the Valencia Region

Extreme-temperature events have a great impact on human society. Thus, knowledge of summer temperatures can be very useful both for the general public and for organizations whose workers operate in the open. An accurate forecasting of summer maximum and minimum temperatures could help to predict heatwave conditions and permit the implementation of strategies aimed at minimizing the negative effects that high temperatures have on human health. The objective of this work is to evaluate the skill of the regional atmospheric and modelling system (RAMS) model in determining daily summer maximum and minimum temperatures in the Valencia Region. For this, we have used the real-time configuration of this model currently running at the Centro de Estudios Ambientales de Mediterráneo Foundation. This operational system is run twice a day, and both runs have a 3-day forecast range. To carry out the verification of the model in this work, the information generated by the system has been broken into individual simulation days for a specific daily run of the model. Moreover, we have analysed the summer forecast period from 1 June to 31 August for 2007, 2008, 2009 and 2010. The results indicate good agreement between observed and simulated maximum temperatures, with RMSE in general near 2 °C both for coastal and inland stations. For this parameter, the model shows a negative bias around −1.5 °C in the coast, while the opposite trend is observed inland. In addition, RAMS also shows good results in forecasting minimum temperatures for coastal locations, with bias lower than 1 °C and RMSE below 2 °C. However, the model presents some difficulties for this parameter inland, where bias higher than 3 °C and RMSE of about 4 °C have been found. Besides, there is little difference in both temperatures forecasted within the two daily RAMS cycles and that RAMS is very stable in maintaining the forecast performance at least for three forecast days