Downscaling large-scale climate variability using a regional climate model: the case of ENSO over Southern Africa

2012 ◽  
Vol 40 (5-6) ◽  
pp. 1141-1168 ◽  
Author(s):  
Damien Boulard ◽  
Benjamin Pohl ◽  
Julien Crétat ◽  
Nicolas Vigaud ◽  
Thanh Pham-Xuan
1999 ◽  
Vol 104 (D16) ◽  
pp. 19015-19025 ◽  
Author(s):  
A. M. Joubert ◽  
J. J. Katzfey ◽  
J. L. McGregor ◽  
K. C. Nguyen

2011 ◽  
Vol 37 (7-8) ◽  
pp. 1335-1356 ◽  
Author(s):  
Julien Crétat ◽  
Clémence Macron ◽  
Benjamin Pohl ◽  
Yves Richard

2015 ◽  
Vol 3 (12) ◽  
pp. 7231-7245
Author(s):  
F. F. Hattermann ◽  
S. Huang ◽  
O. Burghoff ◽  
P. Hoffmann ◽  
Z. W. Kundzewicz

Abstract. In our first study on possible flood damages under climate change in Germany, we reported that a considerable increase in flood related losses can be expected in future, warmer, climate. However, the general significance of the study was limited by the fact that outcome of only one Global Climate Model (GCM) was used as large scale climate driver, while many studies report that GCM models are often the largest source of uncertainty in impact modeling. Here we show that a much broader set of global and regional climate model combinations as climate driver shows trends which are in line with the original results and even give a stronger increase of damages.


2019 ◽  
Author(s):  
Evelyn Jäkel ◽  
Johannes Stapf ◽  
Manfred Wendisch ◽  
Marcel Nicolaus ◽  
Wolfgang Dorn ◽  
...  

Abstract. For large scale and long term Arctic climate simulations appropriate parameterization of the surface albedo are required. Therefore, the sea ice surface (SIS) albedo parameterization of the coupled regional climate model HIRHAM–NAOSIM was examined against measurements performed during the joint ACLOUD (Arctic CLoud Observations Using airborne mea-surements during polar Day) and PASCAL (Physical feedbacks of Arctic boundary layer, Sea ice, Cloud and AerosoL) cam-paigns which were performed in May/June 2017 north of Svalbard. The SIS albedo parameterization was tested using measured quantities of the prognostic variables surface temperature and snow depth to calculate the surface albedo and the individual fractions of the ice surface subtypes (snow covered ice, bare ice, and melt ponds) derived from digital camera images taken onboard of the Polar 5/6 aircraft. Based on data gained during 12 flights, it was found that the range of parameterized SIS albedo for individual days is smaller than that of the measurements. This was attributed to the biased functional dependence of the SIS albedo parameterization on temperature. Furthermore, a temporal bias was observed with higher values compared to the modeled SIS albedo (0.88 compared to 0.84 for 29 May 2017) in the beginning of the campaign, and an opposite trend towards the end of the campaign (0.67 versus 0.83 for 25 June 2017). Furthermore, the surface type fraction parameterization was tested against the camera image product which revealed an agreement within 1 %. An adjustment of the variables, defining the parameterized SIS albedo, and additionally accounting for the cloud cover could reduce the root mean squared error from 0.14 to 0.04 for cloud free/broken cloud situations and from 0.06 to 0.05 for overcast conditions.


2010 ◽  
Vol 34 (1) ◽  
pp. 59-74 ◽  
Author(s):  
C.J.R. Williams ◽  
D.R. Kniveton ◽  
R. Layberry

To date, a number of studies have focused on the influence of sea surface temperature (SST) on global and regional rainfall variability, with the majority of these focusing on certain ocean basins — eg, the Pacific, North Atlantic and Indian Ocean. In contrast, relatively less work has been done on the influence of the central South Atlantic, particularly in relation to rainfall over southern Africa. Previous work by the authors, using reanalysis data and general circulation model (GCM) experiments, has suggested that cold SST anomalies in the central southern Atlantic Ocean are linked to an increase in rainfall extremes across southern Africa. In this paper we present results from idealized regional climate model (RCM) experiments forced with both positive and negative SST anomalies in the southern Atlantic Ocean. These experiments reveal an unexpected response of rainfall over southern Africa. In particular, it was found that SST anomalies of opposite sign can cause similar rainfall responses in the model experiments, with isolated increases in rainfall over central southern Africa as well as a large region of drying over the Mozambique Channel. The purpose of this paper is to highlight this finding and explore explanations for the behaviour of the climate model. It is suggested that the observed changes in rainfall might result from the redistribution of energy (associated with upper-level changes to Rossby waves) or, of more concern, model error, and therefore the paper concludes that the results of idealized regional climate models forced with SST anomalies should be viewed cautiously.


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