Quantifying the relevance of atmospheric blocking for co-located temperature extremes in the Northern Hemisphere on (sub-)daily time scales

2012 ◽  
Vol 39 (12) ◽  
pp. n/a-n/a ◽  
Author(s):  
S. Pfahl ◽  
H. Wernli
Keyword(s):  
Time Scales ◽  
Northern Hemisphere ◽  
Temperature Extremes ◽  
Atmospheric Blocking ◽  
Daily Time

Projected changes in extreme precipitation at sub-daily and daily time scales

2019 ◽  
Vol 182 ◽  
pp. 103004 ◽  
Author(s):  
Alex Morrison ◽  
Gabriele Villarini ◽  
Wei Zhang ◽  
Enrico Scoccimarro
Keyword(s):  
Time Scales ◽  
Extreme Precipitation ◽  
Projected Changes ◽  
Daily Time

Northern hemisphere atmospheric response to changes of atlantic ocean SST on decadal time scales: a GCM experiment

1990 ◽  
Vol 4 (3) ◽  
pp. 157-174 ◽  
Author(s):  
Andreas Hense ◽  
Rita Glowienka-Hense ◽  
Hans von Storch ◽  
Ursula Stähler
Keyword(s):  
Atlantic Ocean ◽  
Time Scales ◽  
Northern Hemisphere ◽  
Atmospheric Response

scholarly journals Sub-daily runoff simulations with parameters inferred at the daily time scale

2015 ◽  
Vol 12 (8) ◽  
pp. 7437-7467 ◽  
Author(s):  
J. E. Reynolds ◽  
S. Halldin ◽  
C. Y. Xu ◽  
J. Seibert ◽  
A. Kauffeldt
Keyword(s):  
Time Series ◽  
Numerical Method ◽  
Time Scales ◽  
Time Scale ◽  
Input Data ◽  
Flood Forecasting ◽  
Euler Method ◽  
Time Stepping ◽  
Parameter Values ◽  
Daily Time

Abstract. Concentration times in small and medium-sized watersheds (~ 100–1000 km2) are commonly less than 24 h. Flood-forecasting models then require data at sub-daily time scales, but time-series of input and runoff data with sufficient lengths are often only available at the daily time scale, especially in developing countries. This has led to a search for time-scale relationships to infer parameter values at the time scales where they are needed from the time scales where they are available. In this study, time-scale dependencies in the HBV-light conceptual hydrological model were assessed within the generalized likelihood uncertainty estimation (GLUE) approach. It was hypothesised that the existence of such dependencies is a result of the numerical method or time-stepping scheme used in the models rather than a real time-scale-data dependence. Parameter values inferred showed a clear dependence on time scale when the explicit Euler method was used for modelling at the same time steps as the time scale of the input data (1–24 h). However, the dependence almost fully disappeared when the explicit Euler method was used for modelling in 1 h time steps internally irrespectively of the time scale of the input data. In other words, it was found that when an adequate time-stepping scheme was implemented, parameter sets inferred at one time scale (e.g., daily) could be used directly for runoff simulations at other time scales (e.g., 3 or 6 h) without any time scaling and this approach only resulted in a small (if any) model performance decrease, in terms of Nash–Sutcliffe and volume-error efficiencies. The overall results of this study indicated that as soon as sub-daily driving data can be secured, flood forecasting in watersheds with sub-daily concentration times is possible with model-parameter values inferred from long time series of daily data, as long as an appropriate numerical method is used.

scholarly journals How Predictable Are the Arctic and North Atlantic Oscillations? Exploring the Variability and Predictability of the Northern Hemisphere

2018 ◽  
Vol 31 (3) ◽  
pp. 997-1014 ◽  
Author(s):  
Daniela I. V. Domeisen ◽  
Gualtiero Badin ◽  
Inga M. Koszalka
Keyword(s):  
Time Scales ◽  
Northern Hemisphere ◽  
North Atlantic ◽  
Prediction Models ◽  
The Arctic ◽  
Ensemble Prediction ◽  
Atmospheric Conditions ◽  
Short Term ◽  
The North ◽  
The North Atlantic Oscillation

ABSTRACT The North Atlantic Oscillation (NAO) and the Arctic Oscillation (AO) describe the dominant part of the variability in the Northern Hemisphere extratropical troposphere. Because of the strong connection of these patterns with surface climate, recent years have shown an increased interest and an increasing skill in forecasting them. However, it is unclear what the intrinsic limits of short-term predictability for the NAO and AO patterns are. This study compares the variability and predictability of both patterns, using a range of data and index computation methods for the daily NAO and AO indices. Small deviations from Gaussianity are found along with characteristic decorrelation time scales of around one week. In the analysis of the Lyapunov spectrum it is found that predictability is not significantly different between the AO and NAO or between reanalysis products. Differences exist, however, between the indices based on EOF analysis, which exhibit predictability time scales around 12–16 days, and the station-based indices, exhibiting a longer predictability of 18–20 days. Both of these time scales indicate predictability beyond that currently obtained in ensemble prediction models for short-term predictability. Additional longer-term predictability for these patterns may be gained through local feedbacks and remote forcing mechanisms for particular atmospheric conditions.

Northern Hemisphere Atmospheric Blocking Representation in Global Climate Models: Twenty Years of Improvements?

2016 ◽  
Vol 29 (24) ◽  
pp. 8823-8840 ◽  
Author(s):  
Paolo Davini ◽  
Fabio D’Andrea
Keyword(s):  
Northern Hemisphere ◽  
General Circulation ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Model ◽  
Weather Prediction ◽  
Global Climate Models ◽  
Main Concern ◽  
Atmospheric Blocking ◽  
Atlantic Sector

Abstract The correct simulation of midlatitude atmospheric blocking has always been a main concern since the earliest days of numerical modeling of Earth’s atmosphere. To this day blocking represents a considerable source of error for general circulation models from both a numerical weather prediction and a climate perspective. In the present work, 20 years of global climate model (GCM) developments are analyzed from the special point of view of Northern Hemisphere atmospheric blocking simulation. Making use of a series of equivalent metrics, three generations of GCMs are compared. This encompasses a total of 95 climate models, many of which are different—successive—versions of the same model. Results from model intercomparison projects AMIP1 (1992), CMIP3 (2007), and CMIP5 (2012) are taken into consideration. Although large improvements are seen over the Pacific Ocean, only minor advancements have been achieved over the Euro-Atlantic sector. Some of the most recent GCMs still exhibit the same negative bias as 20 years ago in this region, associated with large geopotential height systematic errors. Some individual models, nevertheless, have improved and do show good performances in both sectors. Negligible differences emerge among ocean-coupled or atmosphere-only simulations, suggesting weak relevance of sea surface temperature biases. Conversely, increased horizontal resolution seems to be able to alleviate the Euro-Atlantic blocking bias.

scholarly journals Comparison of Global Precipitation Estimates across a Range of Temporal and Spatial Scales

2016 ◽  
Vol 29 (21) ◽  
pp. 7773-7795 ◽  
Author(s):  
Maria Gehne ◽  
Thomas M. Hamill ◽  
George N. Kiladis ◽  
Kevin E. Trenberth
Keyword(s):  
Time Scales ◽  
Large Scale ◽  
Global Climate ◽  
Spatial Scales ◽  
Rain Gauge ◽  
Random Errors ◽  
Climate Data ◽  
Precipitation Estimates ◽  
Global Precipitation ◽  
Daily Time

Abstract Characteristics of precipitation estimates for rate and amount from three global high-resolution precipitation products (HRPPs), four global climate data records (CDRs), and four reanalyses are compared. All datasets considered have at least daily temporal resolution. Estimates of global precipitation differ widely from one product to the next, with some differences likely due to differing goals in producing the estimates. HRPPs are intended to produce the best snapshot of the precipitation estimate locally. CDRs of precipitation emphasize homogeneity over instantaneous accuracy. Precipitation estimates from global reanalyses are dynamically consistent with the large-scale circulation but tend to compare poorly to rain gauge estimates since they are forecast by the reanalysis system and precipitation is not assimilated. Regional differences among the estimates in the means and variances are as large as the means and variances, respectively. Even with similar monthly totals, precipitation rates vary significantly among the estimates. Temporal correlations among datasets are large at annual and daily time scales, suggesting that compensating bias errors at annual and random errors at daily time scales dominate the differences. However, the signal-to-noise ratio at intermediate (monthly) time scales can be large enough to result in high correlations overall. It is shown that differences on annual time scales and continental regions are around 0.8 mm day−1, which corresponds to 23 W m−2. These wide variations in the estimates, even for global averages, highlight the need for better constrained precipitation products in the future.

scholarly journals Spatiotemporal Variability and Trends in Extreme Temperature Events in Finland over the Recent Decades: Influence of Northern Hemisphere Teleconnection Patterns

2018 ◽  
Vol 2018 ◽  
pp. 1-17 ◽  
Author(s):  
Masoud Irannezhad ◽  
Hamid Moradkhani ◽  
Bjørn Kløve
Keyword(s):  
Northern Hemisphere ◽  
Extreme Temperature ◽  
Cold Temperature ◽  
Spatiotemporal Variability ◽  
The Arctic ◽  
Temperature Extremes ◽  
Warm Temperature ◽  
Teleconnection Patterns ◽  
The North ◽  
Temperature Indices

Fifteen temperature indices recommended by the ETCCDI (Expert Team on Climate Change Detection and Indices) were applied to evaluate spatiotemporal variability and trends in annual intensity, frequency, and duration of extreme temperature statistics in Finland during 1961–2011. Statistically significant relationships between these high-resolution (10 km) temperature indices and seven influential Northern Hemisphere teleconnection patterns (NHTPs) for the interannual climate variability were also identified. During the study period (1961–2011), warming trends in extreme temperatures were generally manifested by statistically significant increases in cold temperature extremes rather than in the warm temperature extremes. As expected, warm days and nights became more frequent, while fewer cold days and nights occurred. The frequency of frost and icing days also decreased. Finland experienced more (less) frequent warm (cold) temperature extremes over the past few decades. Interestingly, significant lengthening in cold spells was observed over the upper part of northern Finland, while no clear changes are found in warm spells. Interannual variations in the temperature indices were significantly associated with a number of NHTPs. In general, warm temperature extremes show significant correlations with the East Atlantic and the Scandinavia patterns and cold temperature extremes with the Arctic Oscillation and the North Atlantic Oscillation patterns.

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