Search Results

You are looking at 1 - 3 of 3 items for

  • Author or Editor: Jörg Trentmann x
  • User-accessible content x
Clear All Modify Search
Uwe Pfeifroth, Jörg Trentmann, Andreas H. Fink, and Bodo Ahrens

Abstract

Precipitation plays a major role in the energy and water cycles of the earth. Because of its variable nature, consistent observations of global precipitation are challenging. Satellite-based precipitation datasets present an alternative to in situ–based datasets in areas sparsely covered by ground stations. These datasets are a unique tool for model evaluations, but the value of satellite-based precipitation datasets depends on their application and scale. Numerous validation studies considered monthly or daily time scales, while less attention is given to subdaily scales. In this study subdaily satellite-based rainfall data are analyzed in West Africa, a region with strong diurnal variability. Several satellite-based precipitation datasets are validated, including Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA), TRMM 3G68 products, Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN), and Climate Prediction Center (CPC) morphing technique (CMORPH) data. As a reference, highly resolved in situ data from the African Monsoon Multidisciplinary Analysis–Couplage de l’Atmosphere Tropical et du Cycle Hydrologique (AMMA-CATCH) are used. As a result, overall the satellite products capture the diurnal cycles of precipitation and its variability as observed on the ground reasonably well. CMORPH and TMPA data show overall good results. For locally induced convective rainfall in the evening most satellite data show slight delays in peak precipitation of up to 2 h.

Full access
Alexander Loew, Axel Andersson, Jörg Trentmann, and Marc Schröder

Abstract

Earth system models are indispensable tools in climate studies. The Coupled Model Intercomparison Project (CMIP) is a coordinated effort of the Earth system modeling community to intercompare existing models. An accurate simulation of surface solar radiation fluxes is of major importance for the accuracy of simulations of the near-surface climate in Earth system models. The present study provides a quantitative assessment of the accuracy and multidecadal changes of surface solar radiation fluxes for model results from two phases of CMIP. The entire archives of phase 5 of CMIP (CMIP5) and its predecessor phase 3 (CMIP3) are analyzed for present-day climate conditions. A relative model ranking is provided, and its uncertainty is quantified using different global observational records. It is shown that the choice of an observational dataset can have a major influence on relative model ranking between CMIP models. However the multidecadal variability of surface solar radiation fluxes, also known as global “dimming” or “brightening,” is largely underestimated by the CMIP models.

Full access
Pieter Groenemeijer, Christian Barthlott, Ulrich Corsmeier, Jan Handwerker, Martin Kohler, Christoph Kottmeier, Holger Mahlke, Andreas Wieser, Andreas Behrendt, Sandip Pal, Marcus Radlach, Volker Wulfmeyer, and Jörg Trentmann

Abstract

Measurements of a convective storm cluster in the northern Black Forest in southwest Germany have revealed the development of a warm and dry downdraft under its anvil cloud that had an inhibiting effect on the subsequent development of convection. These measurements were made on 12 July 2006 as part of the field campaign Prediction, Identification and Tracking of Convective Cells (PRINCE) during which a number of new measurement strategies were deployed. These included the collocation of a rotational Raman lidar and a Doppler lidar on the summit of the highest mountain in the region (1164 m MSL) as well as the deployment of teams carrying radiosondes to be released in the vicinity of convective storms. In addition, an aircraft equipped with sensors for meteorological variables and dropsondes was in operation and determined that the downdraft air was approximately 1.5 K warmer, 4 g kg−1 drier, and therefore 3 g m−3 less dense than the air at the same altitude in the storm’s surroundings. The Raman lidar detected undulating aerosol-rich layers in the preconvective environment and a gradual warming trend of the lower troposphere as the nearby storm system evolved. The Doppler lidar both detected a pattern of convergent radial winds under a developing convective updraft and an outflow emerging under the storm’s anvil cloud. The dryness of the downdraft air indicates that it had subsided from higher altitudes. Its low density reveals that its development was not caused by negative thermal buoyancy, but was rather due to the vertical mass flux balance accompanying the storm’s updrafts.

Full access