Evaluation of atmospheric thermal radiation algorithms for daylight hours

Existing simple but theoretically based clear-sky models for longwave down-welling radiation (LDR_c) and cloud impact algorithms transforming them to all-sky radiation (LDR) are checked against locally calibrated empirical algorithms. They are evaluated for daylight hours based on measurements in regionally differing climates of Germany. The Prata clear-sky scheme is additionally tested with adjusted coefficients so that LDR_c converges against a realistic emissivity for a completely dry atmosphere. This version is characterised by an improved modelled variance. Compared with locally calibrated schemes, bias and root mean square error (RMSE) of the more theoretical clear-sky schemes do not differ significantly and yield even better results at a mountain site. In contrast, the locally calibrated algorithms yield biases up to 9% and an increase in RMSE between 6% and 67%, if applied for other sites. For daylight hours, the cloud impact on LDR can be calculated via the ratio of observed to clear-sky global irradiation (CMF_sol). With CMF_sol, the Crawford and Duchon scheme reveals the lowest bias and a decrease in RMSE by 22% against the next best performing algorithms. Compared with synoptic cloud observations as input, the bias is reduced by 9 to 28 W m^?2 and the scattering of the residuals decreases by 20% to 30%. Based on published results for also non-European sites, it is inferred that the more theoretically based LDR_c schemes and cloud impact evaluated via CMF_sol are universally applicable and perform at least in the order of magnitude of locally calibrated empirical algorithms.     

A reconstructed dynamic Indian monsoon index extended back to 1880

The authors present a reconstruction of summer (June–July–August) mean dynamic Indian monsoon index (DIMI) back to 1880 based on a large number of historical surface observation data as well as information from the upper air data. The reconstruction shows a satisfying skill in terms of both the value of reduction of error and an evaluation against other independent monsoon indices. The skill of reconstruction increases over time with more predictor data (in particular upper-level data) becoming available. A comparison with the observed all Indian summer monsoon rainfall index (AIRI) shows a high consistence in both inter-decadal and inter-annual variability. The reconstruction shows stronger than normal monsoon during the 1880s, 1915–1925 (around 1920) and 1930–1945 (around 1940) as the AIRI. The El Nino/Southern Oscillation (ENSO)—monsoon relationship is reasonably captured in the reconstruction. Powers concentrating within quasi-biennial band stand out in the reconstruction as well as in the AIRI. A comparison of the reconstruction against an atmospheric general circulation model simulation with specified SST and external forcing agents spanning 1901–1999 indicates a slightly higher reproducibility of monsoon circulation than monsoon rainfall in terms of interannual variability. The relationship between the Asian continent warming and the ENSO–monsoon connection is also discussed by using the new dynamic index.     

Effects of land cover change on the tropical circulation in a GCM

Multivariate statistics are used to investigate sensitivity of the tropical atmospheric circulation to scenario-based global land cover change (LCC), with the largest changes occurring in the tropics. Three simulations performed with the fully coupled Parallel Climate Model (PCM) are compared: (1) a present day control run; (2) a simulation with present day land cover and Intergovernmental Panel on Climate Change (IPCC) Special Report on Emission Scenarios (SRES) A2 greenhouse gas (GHG) projections; and (3) a simulation with SRES A2 land cover and GHG projections. Dimensionality of PCM data is reduced by projection onto a priori specified eigenvectors, consisting of Rossby and Kelvin waves produced by a linearized, reduced gravity model of the tropical circulation. A Hotelling T ² test is performed on projection amplitudes. Effects of LCC evaluated by this method are limited to diabatic heating. A statistically significant and recurrent signal is detected for 33% of all tests performed for various combinations of parameters. Taking into account uncertainties and limitations of the present methodology, this signal can be interpreted as a Rossby wave response to prescribed LCC. The Rossby waves are shallow, large-scale motions, trapped at the equator and most pronounced in boreal summer. Differences in mass and flow fields indicate a shift of the tropical Walker circulation patterns with an anomalous subsidence over tropical South America.     

The study of artificial intelligence for predicting land use changes in an arid ecosystem

Journal of Geographical Sciences - During the 21st century, artificial intelligence methods have been broadly applied in geosciences to simulate complex dynamic ecosystems, but the use of...     

Identifying Nonstationarity in Turbulence Series

Because of rapid forcing by varying cloud and sky conditions, turbulence time series collected in the atmospheric surface layer over land may often be nonstationary. The meteorological community, however, has no consensus definition of what nonstationarity is and, thus, no consensus method for how to identify it. This study, therefore, adopts definitions for first-order and second-order stationarity taken from the time series analysis literature and implements new analysis techniques and probabilistic tests to quantify first-order and second-order nonstationarity. First-order nonstationarity manifests as a change in the series mean; second-order nonstationarity, as a change in the variance. The analysis identifies nonstationarity in surface-level turbulent temperature and water vapour series collected during two sample days with solar forcing influenced by cirrus and cirrostratus clouds, but that nonstationarity is not as severe as expected despite the rapid thermal forcing by these clouds. On the other hand, even with negligible cloud forcing, both sample days exhibited severe nonstationarity at night.     

Uncertainty, learning and ambiguity in economic models on climate policy: some classical results and new directions

We present how uncertainty and learning are classically studied in economic models. Specifically, we study a standard expected utility model with two sequential decisions, and consider two particular cases of this model to illustrate how uncertainty and learning may affect climate policy. While uncertainty has generally a negative effect on welfare, learning has always a positive, and thus opposite, effect. The effects of both uncertainty and learning on decisions are less clear. Neither uncertainty nor learning can be used as a general argument to increase or reduce emissions today without studying the specific intertemporal costs and benefits. Considering limits in applying the expected utility framework to climate change problems, we then consider a more recent framework with ambiguity-aversion which accounts for situations of imprecise or multiple probability distributions. We discuss both the impact of ambiguity-aversion on decisions and difficulties in applying such a non-expected utility framework to a dynamic context.     

Observing upper troposphere–lower stratosphere climate with radio occultation data from the CHAMP satellite

High quality observations of the atmosphere are particularly required for monitoring global climate change. Radio occultation (RO) data, using Global Navigation Satellite System (GNSS) signals, are well suited for this challenge. The special climate utility of RO data arises from their long-term stability due to their self-calibrated nature. The German research satellite CHAllenging Minisatellite Payload for geoscientific research (CHAMP) continuously records RO profiles since August 2001 providing the first opportunity to create RO based climatologies for a multi-year period of more than 5 years. A period of missing CHAMP data from July 3, 2006 to August 8, 2006 can be bridged with RO data from the GRACE satellite (Gravity Recovery and Climate Experiment). We have built seasonal and zonal mean climatologies of atmospheric (dry) temperature, microwave refractivity, geopotential height and pressure with 10° latitudinal resolution. We show representative results with focus on dry temperatures and compare them with analysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF). Although we have available only about 150 CHAMP profiles per day (compared to millions of data entering the ECMWF analyses) the overall agreement between 8 and 30 km altitude is in general very good with systematic differences <0.5 K in most parts of the domain. Pronounced systematic differences (exceeding 2 K) in the tropical tropopause region and above Antarctica in southern winter can almost entirely be attributed to errors in the ECMWF analyses. Errors resulting from uneven sampling in space and time are a potential error source for single-satellite climatologies. The average CHAMP sampling error for seasonal zonal means is <0.2 K, higher values occur in restricted regions and time intervals which can be clearly identified by the sampling error estimation approach we introduced (which is based on ECMWF analysis fields). The total error of this new type of temperature climatologies is estimated to be <0.5 K below 30 km. The recently launched Taiwan/U.S. FORMOSAT-3/COSMIC constellation of 6 RO satellites started to provide thousands of RO profiles per day, but already now the single-satellite CHAMP RO climatologies improve upon modern operational climatologies in the upper troposphere–lower stratosphere and can act as absolute reference climatologies for validation of more bias-sensitive climate datasets and models.     

Geology of the Niederlausitz Lignite district, Germany

One of the largest brown coal producing districts in the world is the Miocene of Niederlausitz Lignite area in the southeastern part of Germany. Production is in a range of 320 million t/yr. The resources of the first (shallowest) Miocene seam have nearly been exhausted and it is now mainly the second seam which is being mined. A fourth is being explored. The third Miocene and the Oligocene seam, Calau, are unminable. All brown coal is mined in open pits. The rank of brown coal of the second Miocene seam ranges from fuel coal to coking coal. Its heat value (dry) from 22.2 to 23.5 MJ, its ash content (dry) from 6% to 13%, its moisture from 57% to 59%, and its seam thickness from 10 to 12 m. Due to the close relationship between swamp facies and the main coal quality parameters, the coal quality can be directly determined from the drill log.The Oligocene and Miocene brown coal formation was synchronous with the alpine orogenesis and the seafloor spreading of the North Atlantic Ocean, which both caused north and east oriented migrations of the labile basement of central Europe. Periods of compression alternated with longer periods of isostatic subsidence and sedimentation. Additionally, the trends of thickness and facies of sediments were controlled by a block system in the basement of the brown coal district of Niederlausitz, uplifting, subsiding, collapsing, rotating or spreading.The second Lower Miocene seam is situated at sea level in the north of the Niederlausitz area and rises to the south to +150 to +180 m above sea level, due to considerable widespread subsidence and uplifting since the Lower Miocene. Horizontal tectonic movements were caused by the collapse of asymmetric grabens with slight tendency to rotation. Regional shear movements led to block faulting followed by volcanism. Counter-clockwise rotation of the basement blocks is assumed, a hypothesis supported by recent tension measurements and seismic observations. Ice cover in the Pleistocene caused wide destruction zones, narrow and deep channels and intensively folded or imbricated seam structures. Some gravity-induced plastic structures were also formed.     

Geothermobarometry of a stilpnomelane–garnet-bearing metapegmatite: P–T constraints on the Eo-Alpine metamorphic overprint of the Austroalpine nappes north of the Tauern Window

The Ordovician Kellerjochgneiss (Schwaz Augengneiss) is a polymetamorphic orthogneiss-bearing unit and is part of the Austroalpine basement nappes north of the Tauern Window. Within the Kellerjochgneiss a small, strongly deformed metapegmatite dike occurs. The pegmatite crosscuts the gneiss discordantly and contains the mineral assemblage muscovite 1,2+plagioclase+K-feldspar+chlorite+quartz+garnet 1 (Alm_67–76Andr_0.9–2Sps_17–28Prp_0.4–5)+garnet 2 (Grs_36–46Alm_24–32Andr_8–21Sps_15–17Prp_0–1)±stilpnomelane±biotite±clinozoisite. The magmatic protolith assemblage is comprised of relict K-feldspar, quartz and garnet 1. Textural observations indicate that biotite and muscovite cores (muscovite 1) are either part of the magmatic- or an earlier (Variscan?) metamorphic assemblage. Geothermobarometry of the metapegmatite was done on the latest-stage (Eo-Alpine) mineral assemblage garnet 2+muscovite 2+chlorite+stilpnomelane+plagioclase+quartz. Calculations of H₂O-absent intersections in the system [KCNFMAS] with the multi-equilibrium program THERMOCALC v.3.1 yielded P–T estimates of 4.4 to 6.7 kbar and 321°C to 376°C. Calculations of the P–T conditions by using the assemblage muscovite 2+chlorite+stilpnomelane+quartz yielded slightly higher pressures of 6.4 to 7.2 kbar at temperatures of 310–325°C. Correlating these P–T data with geochronological data from the neighbouring lithologies (Kellerjochgneiss, Innsbruck Quartzphyllite, Wildschönau Schists) and with structural investigations from these units indicate that the P–T estimates obtained in this investigation represent the Eo-Alpine metamorphic overprint. Hence, these unusual rocks provide important information on the Eo-Alpine P–T conditions since most samples studied from the investigated Austroalpine basement nappes north of the Tauern Window rarely contain mineral assemblages suitable for geothermobarometry.