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

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

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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

Western Indian Ocean marine and terrestrial records of climate variability: a review and new concepts on land-ocean interactions since AD 1660

We examine the relationship between three tropical and two subtropical western Indian Ocean coral oxygen isotope time series to surface air temperatures (SAT) and rainfall over India, tropical East Africa and southeast Africa. We review established relationships, provide new concepts with regard to distinct rainfall seasons, and mean annual temperatures. Tropical corals are coherent with SAT over western India and East Africa at interannual and multidecadal periodicities. The subtropical corals correlate with Southeast African SAT at periodicities of 16–30 years. The relationship between the coral records and land rainfall is more complex. Running correlations suggest varying strength of interannual teleconnections between the tropical coral oxygen isotope records and rainfall over equatorial East Africa. The relationship with rainfall over India changed in the 1970s. The subtropical oxygen isotope records are coherent with South African rainfall at interdecadal periodicities. Paleoclimatological reconstructions of land rainfall and SAT reveal that the inferred relationships generally hold during the last 350 years. Thus, the Indian Ocean corals prove invaluable for investigating land–ocean interactions during past centuries

Soil moisture-Temperature Coupling: A multiscale observational Analysis

[1] Land-atmospheric interactions are complex and variable in space and time. On average soil moisture-temperature coupling is expected to be stronger in transition zones between wet and dry climates. During heatwaves anomalously high coupling may be found in areas of soil moisture deficit and high atmospheric demand of water. Here a new approach is applied to satellite andin situobservations towards the characterization of regions of intense soil moisture-temperature coupling, both in terms of climatology and anomalies during heatwaves. The resulting average summertime couplinghot spotsreflect intermediate climatic regions in agreement with previous studies. Results at heatwave-scale suggest a minor role of soil moisture deficit during the heatwave of 2006 in California but an important one in the 2003 event in Western Europe. Progress towards near-real time satellite products may allow the application of the approach to aid prediction and management of warm extremes

Downscaling ECMWF seasonal precipitation forecasts in Europe using the RCA model

The operational performance and usefulness of regional climate models at seasonal time scales are assessed by downscaling an ensemble of global seasonal forecasts. The Rossby Centre RCA regional model was applied to downscale a five-member ensemble from the ECMWF System3 global model in the European Atlantic domain for the period 1981–2001. One month lead time global and regional precipitation predictions were compared over Europe—and particularly over Spain—focusing the study in SON (autumn) dry events. A robust tercile-based probabilistic validation approach was applied to compare the forecasts from global and regional models, obtaining significant skill in both cases, but over a wider area for the later. Finally, we also analyse the performance of a mixed ensemble combining both forecasts

Future Atmospheric Rivers and Impacts on Precipitation: Overview of the ARTMIP Tier 2 High‐Resolution Global Warming Experiment

Atmospheric rivers (ARs) are long, narrow synoptic scale weather features important for Earth’s hydrological cycle typically transporting water vapor poleward, delivering precipitation important for local climates. Understanding ARs in a warming climate is problematic because the AR response to climate change is tied to how the feature is defined. The Atmospheric River Tracking Method Intercomparison Project (ARTMIP) provides insights into this problem by comparing 16 atmospheric river detection tools (ARDTs) to a common data set consisting of high resolution climate change simulations from a global atmospheric general circulation model. ARDTs mostly show increases in frequency and intensity, but the scale of the response is largely dependent on algorithmic criteria. Across ARDTs, bulk characteristics suggest intensity and spatial footprint are inversely correlated, and most focus regions experience increases in precipitation volume coming from extreme ARs. The spread of the AR precipitation response under climate change is large and dependent on ARDT selection

Monthly sunspot number time series analysis and its modeling through autoregressive artificial neural network

This study reports a statistical analysis of monthly sunspot number time series and observes non homogeneity and asymmetry within it. Using Mann-Kendall test a linear trend is revealed. After identifying stationarity within the time series we generate autoregressive AR(p) and autoregressive moving average (ARMA(p,q)). Based on minimization of AIC we find 3 and 1 as the best values of p and q respectively. In the next phase, autoregressive neural network (AR-NN(3)) is generated by training a generalized feedforward neural network (GFNN). Assessing the model performances by means of Willmott's index of second order and coefficient of determination, the performance of AR-NN(3) is identified to be better than AR(3) and ARMA(3,1).Comment: 17 pages, 4 figure

Low-frequency variability of the Indian monsoon-ENSO relationship and the tropical Atlantic : the "Weakening" of the 1980s and 1990s

Author Posting. © American Meteorological Society, 2007. 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 20 (2007): 4255-4266, doi:10.1175/JCLI4254.1The Indian monsoon–El Niño–Southern Oscillation (ENSO) relationship, according to which a drier than normal monsoon season precedes peak El Niño conditions, weakened significantly during the last two decades of the twentieth century. In this work an ensemble of integrations of an atmospheric general circulation model (AGCM) coupled to an ocean model in the Indian Basin and forced with observed sea surface temperatures (SSTs) elsewhere is used to investigate the causes of such a weakening. The observed interdecadal variability of the ENSO–monsoon relationship during the period 1950–99 is realistically simulated by the model and a dominant portion of the variability is associated with changes in the tropical Atlantic SSTs in boreal summer. In correspondence to ENSO, the tropical Atlantic SSTs display negative anomalies south of the equator in the last quarter of the twentieth century and weakly positive anomalies in the previous period. Those anomalies in turn produce heating anomalies, which excite a Rossby wave response in the Indian Ocean in both the model and the reanalysis data, impacting the time-mean monsoon circulation. The proposed mechanism of remote response of the Indian rainfall to tropical Atlantic sea surface temperatures is further tested forcing the AGCM coupled to the ocean model in the Indian Basin with climatological SSTs in the Atlantic Ocean and observed anomalies elsewhere. In this second ensemble the ENSO–monsoon relationship is characterized by a stable and strong anticorrelation through the whole second half of the twentieth century.The experiments in this paper were performed as a contribution to the ENSEMBLES project funded by the European Commission’s 6th Framework Programme, Contract GOCE-CT-2003-50553