scholarly journals Can local climate variability be explained by weather patterns? A multi-station evaluation for the Rhine basin

2016 ◽  
Vol 20 (10) ◽  
pp. 4283-4306 ◽  
Author(s):  
Aline Murawski ◽  
Gerd Bürger ◽  
Sergiy Vorogushyn ◽  
Bruno Merz
Keyword(s):  
General Circulation ◽  
Evaluation Criteria ◽  
Circulation Model ◽  
Climate Data ◽  
Stochastic Weather Generator ◽  
Sea Level Pressure ◽  
Local Climate ◽  
Weather Patterns ◽  
Rhine Basin ◽  
Weather Pattern

Abstract. To understand past flood changes in the Rhine catchment and in particular the role of anthropogenic climate change in extreme flows, an attribution study relying on a proper GCM (general circulation model) downscaling is needed. A downscaling based on conditioning a stochastic weather generator on weather patterns is a promising approach. This approach assumes a strong link between weather patterns and local climate, and sufficient GCM skill in reproducing weather pattern climatology. These presuppositions are unprecedentedly evaluated here using 111 years of daily climate data from 490 stations in the Rhine basin and comprehensively testing the number of classification parameters and GCM weather pattern characteristics. A classification based on a combination of mean sea level pressure, temperature, and humidity from the ERA20C reanalysis of atmospheric fields over central Europe with 40 weather types was found to be the most appropriate for stratifying six local climate variables. The corresponding skill is quite diverse though, ranging from good for radiation to poor for precipitation. Especially for the latter it was apparent that pressure fields alone cannot sufficiently stratify local variability. To test the skill of the latest generation of GCMs from the CMIP5 ensemble in reproducing the frequency, seasonality, and persistence of the derived weather patterns, output from 15 GCMs is evaluated. Most GCMs are able to capture these characteristics well, but some models showed consistent deviations in all three evaluation criteria and should be excluded from further attribution analysis.

scholarly journals Can local climate variability be explained by weather patterns? A multi-station evaluation for the Rhine basin

2016 ◽  
Author(s):  
Aline Murawski ◽  
Gerd Bürger ◽  
Sergiy Vorogushyn ◽  
Bruno Merz
Keyword(s):  
Climate Variability ◽  
General Circulation ◽  
Large Scale ◽  
Synoptic Situation ◽  
Stochastic Weather Generator ◽  
Local Climate ◽  
Weather Patterns ◽  
Rhine Basin ◽  
Weather Pattern ◽  
Temperature And Humidity

Abstract. For understanding past flood changes in the Rhine catchment and in particular for quantifying the role of anthropogenic climate change for extreme flows, an attribution study relying on a proper GCM (General Circulation Model) downscaling is needed. A downscaling based on conditioning a stochastic weather generator on weather patterns is a promising approach given, among others, a strong link between weather patterns and local climate, and sufficient GCM skill in reproducing weather pattern climatology. To test the first requirement, an objective classification scheme is applied and different classification variables, spatial domains and number of classes are evaluated. To this end, 111 years of daily climate data from 500 stations in the Rhine basin are used. A classification based on a combination of mean sea level pressure, temperature, and humidity from the ERA20C reanalysis for a relatively small spatial domain over Central Europe with overall 40 weather type classes is found most appropriate for stratifying six local climate variables. The skill in explaining local climate variability is very different, from high for radiation to low for precipitation. Especially local precipitation and humidity are governed by processes that are not completely represented by the large-scale distribution of pressure, temperature and humidity. Before applying the weather pattern based downscaling approach, it should therefore be investigated whether the link between the large-scale synoptic situation and the local climate variable of interest is strong enough for the given purpose. Our analysis suggests that it is advantageous to incorporate additional classification variables besides pressure fields. The use of temperature results in a very good stratification of weather patterns throughout the year. Hence, there is no need to provide different classifications for each season. To test the skill of the latest generation of GCMs in reproducing the frequency, seasonality, and persistence of the derived weather patterns, output from 15 GCMs from the CMIP5 ensemble is evaluated. Most GCMs are able to capture these characteristics well, but some models showed consistent deviations in all three evaluation criteria and should be excluded from further attribution analysis.

scholarly journals Temperature and rainfall estimates for past 18 000 years in Owens Valley, California with a coupled catchment–lake model

2015 ◽  
Vol 12 (7) ◽  
pp. 6505-6539 ◽  
Author(s):  
Z. Yu ◽  
W. Dong ◽  
P. Jiang
Keyword(s):  
General Circulation ◽  
Regional Climate ◽  
Circulation Model ◽  
Climate Data ◽  
Owens Valley ◽  
Climatic Fluctuations ◽  
Closed Basin ◽  
The Past ◽  
Lake Model ◽  
Physically Based

Abstract. Closed-basin lakes are intricately linked to the hydrological systems and are very sensitive recorders of local hydro-climatic fluctuations. Lake records in closed-basins are usually used to investigate the paleoclimate condition which is critical for understanding the past and predicting the future. In this study, a physically based catchment–lake model was developed to extract quantitative paleoclimate information including temperature and rainfall over the past 18 000 years (ka) from lake records in a hydrologically closed basin in the Owens River Valley, California, US. The initial model inputs were prepared based on current regional climate data, boundary conditions from the General Circulation Model, and fossil proxy data. The inputs subsequently were systematically varied in order to produce the observed lake levels. In this way, a large number of possible paleoclimatic combinations can quickly narrow the possible range of paleoclimatic combinations that could have produced the paleolake level and extension. Finally, a quantitative time-series of paleoclimate information for those key times was obtained.

Present-Day Atmospheric Simulations Using GISS ModelE: Comparison to In Situ, Satellite, and Reanalysis Data

2006 ◽  
Vol 19 (2) ◽  
pp. 153-192 ◽  
Author(s):  
Gavin A. Schmidt ◽  
Reto Ruedy ◽  
James E. Hansen ◽  
Igor Aleinov ◽  
Nadine Bell ◽  
...  
Keyword(s):  
General Circulation ◽  
Circulation Model ◽  
Reanalysis Data ◽  
Full Description ◽  
Marine Stratocumulus ◽  
Sea Level Pressure ◽  
In Situ Data ◽  
Basic Physics ◽  
Goddard Institute

Abstract A full description of the ModelE version of the Goddard Institute for Space Studies (GISS) atmospheric general circulation model (GCM) and results are presented for present-day climate simulations (ca. 1979). This version is a complete rewrite of previous models incorporating numerous improvements in basic physics, the stratospheric circulation, and forcing fields. Notable changes include the following: the model top is now above the stratopause, the number of vertical layers has increased, a new cloud microphysical scheme is used, vegetation biophysics now incorporates a sensitivity to humidity, atmospheric turbulence is calculated over the whole column, and new land snow and lake schemes are introduced. The performance of the model using three configurations with different horizontal and vertical resolutions is compared to quality-controlled in situ data, remotely sensed and reanalysis products. Overall, significant improvements over previous models are seen, particularly in upper-atmosphere temperatures and winds, cloud heights, precipitation, and sea level pressure. Data–model comparisons continue, however, to highlight persistent problems in the marine stratocumulus regions.

Sensitivity of Satellite-Derived Tropospheric Temperature Trends to the Diurnal Cycle Adjustment

2016 ◽  
Vol 29 (10) ◽  
pp. 3629-3646 ◽  
Author(s):  
Carl A. Mears ◽  
Frank J. Wentz
Keyword(s):  
General Circulation ◽  
Second Harmonic ◽  
Circulation Model ◽  
Global Scale ◽  
Alternative Methods ◽  
Tropospheric Temperature ◽  
Climate Data ◽  
Microwave Sounding Unit ◽  
Microwave Sounding

Abstract Temperature sounding microwave radiometers flown on polar-orbiting weather satellites provide a long-term, global-scale record of upper-atmosphere temperatures, beginning in late 1978 and continuing to the present. The focus of this paper is the midtropospheric measurements made by the Microwave Sounding Unit (MSU) channel 2 and the Advanced Microwave Sounding Unit (AMSU) channel 5. Previous versions of the Remote Sensing Systems (RSS) dataset have used a diurnal climatology derived from general circulation model output to remove the effects of drifting local measurement time. This paper presents evidence that this previous method is not sufficiently accurate and presents several alternative methods to optimize these adjustments using information from the satellite measurements themselves. These are used to construct a number of candidate climate data records using measurements from 15 MSU and AMSU satellites. The new methods result in improved agreement between measurements made by different satellites at the same time. A method is chosen based on an optimized second harmonic adjustment to produce a new version of the RSS dataset, version 4.0. The new dataset shows substantially increased global-scale warming relative to the previous version of the dataset, particularly after 1998. The new dataset shows more warming than most other midtropospheric data records constructed from the same set of satellites. It is also shown that the new dataset is consistent with long-term changes in total column water vapor over the tropical oceans, lending support to its long-term accuracy.

Topographic and Atmospheric Influences on Precipitation Variability over a Mountainous Watershed

1995 ◽  
Vol 34 (1) ◽  
pp. 68-87 ◽  
Author(s):  
Gregory L. Johnson ◽  
Clayton L. Hanson
Keyword(s):  
General Circulation ◽  
Grid Point ◽  
Geographic Location ◽  
Circulation Model ◽  
Principal Component ◽  
Precipitation Pattern ◽  
Storm Events ◽  
Local Climate ◽  
Radiosonde Station ◽  
Mountainous Watershed

Abstract Using rotated principal component analysis (PCA), unique, orthogonal spatial patterns of daily and monthlyprecipitation on a well-instrumented, mountainous watershed in Idaho are examined for their relationship totopography, geographic location, and atmospheric variability. Precipitation pattern and homogeneous precipitationregion differences between daily and monthly timescales and between winter and summer Seasons were identifiedusing the rotated PCA procedure. In general, monthly data produced regional boundaries more closely alignedwith topography, reflecting the integration of many storm events on monthly timescales. Spatial fields, derivedfrom mapping rotated component loadings at 46 precipitation stations on a 234-kmz watershed, were found tobe highly correlated with topography and geographic location. The eight-year time series of the components forspecific watershed regions were found to be moderately related to linear combinations of meteorological variablesderived from a single radiosonde station approximately 50 km from the waterhed. This would indicate thepotential usefulness of data from a single location, such as a general circulation model grid point, to provideclues about spatial pattern changes and regional precipitation fluctuations even on a small watershed, if sufficientinformation about local climate (i.e., topographic influences) is first established.

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