ALBERT

Notes: Abstract  Palaeodata in synthesis form are needed as benchmarks for the Palaeoclimate Modelling Intercomparison Project (PMIP). Advances since the last synthesis of terrestrial palaeodata from the last glacial maximum (LGM) call for a new evaluation, especially of data from the tropics. Here pollen, plant-macrofossil, lake-level, noble gas (from groundwater) and δ18O (from speleothems) data are compiled for 18±2 ka (14C), 32 °N–33 °S. The reliability of the data was evaluated using explicit criteria and some types of data were re-analysed using consistent methods in order to derive a set of mutually consistent palaeoclimate estimates of mean temperature of the coldest month (MTCO), mean annual temperature (MAT), plant available moisture (PAM) and runoff (P-E). Cold-month temperature (MAT) anomalies from plant data range from −1 to −2 K near sea level in Indonesia and the S Pacific, through −6 to −8 K at many high-elevation sites to −8 to −15 K in S China and the SE USA. MAT anomalies from groundwater or speleothems seem more uniform (−4 to −6 K), but the data are as yet sparse; a clear divergence between MAT and cold-month estimates from the same region is seen only in the SE USA, where cold-air advection is expected to have enhanced cooling in winter. Regression of all cold-month anomalies against site elevation yielded an estimated average cooling of −2.5 to −3 K at modern sea level, increasing to ≈−6 K by 3000 m. However, Neotropical sites showed larger than the average sea-level cooling (−5 to −6 K) and a non-significant elevation effect, whereas W and S Pacific sites showed much less sea-level cooling (−1 K) and a stronger elevation effect. These findings support the inference that tropical sea-surface temperatures (SSTs) were lower than the CLIMAP estimates, but they limit the plausible average tropical sea-surface cooling, and they support the existence of CLIMAP-like geographic patterns in SST anomalies. Trends of PAM and lake levels indicate wet LGM conditions in the W USA, and at the highest elevations, with generally dry conditions elsewhere. These results suggest a colder-than-present ocean surface producing a weaker hydrological cycle, more arid continents, and arguably steeper-than-present terrestrial lapse rates. Such linkages are supported by recent observations on freezing-level height and tropical SSTs; moreover, simulations of “greenhouse” and LGM climates point to several possible feedback processes by which low-level temperature anomalies might be amplified aloft.

Notes: Abstract.  The LMD AGCM was iteratively coupled to the global BIOME1 model in order to explore the role of vegetation-climate interactions in response to mid-Holocene (6000 y BP) orbital forcing. The sea-surface temperature and sea-ice distribution used were present-day and CO2 concentration was pre-industrial. The land surface was initially prescribed with present-day vegetation. Initial climate “anomalies” (differences between AGCM results for 6000 y BP and control) were used to drive BIOME1; the simulated vegetation was provided to a further AGCM run, and so on. Results after five iterations were compared to the initial results in order to identify vegetation feedbacks. These were centred on regions showing strong initial responses. The orbitally induced high-latitude summer warming, and the intensification and extension of Northern Hemisphere tropical monsoons, were both amplified by vegetation feedbacks. Vegetation feedbacks were smaller than the initial orbital effects for most regions and seasons, but in West Africa the summer precipitation increase more than doubled in response to changes in vegetation. In the last iteration, global tundra area was reduced by 25% and the southern limit of the Sahara desert was shifted 2.5 °N north (to 18 °N) relative to today. These results were compared with 6000 y BP observational data recording forest-tundra boundary changes in northern Eurasia and savana-desert boundary changes in northern Africa. Although the inclusion of vegetation feedbacks improved the qualitative agreement between the model results and the data, the simulated changes were still insufficient, perhaps due to the lack of ocean-surface feedbacks.

Notes: Abstract Biome models allow the results of experiments with atmospheric general circulation models to be translated into global maps of potential natural vegetation. The use of biome models as a diagnostic tool for palaeoclimate simulations can yield maps that are directly comparable with palaeoecological (pollen and plant macrofossil) records provided these records are “biomized”, i.e. assigned to biomes in a consistent way. This article describes a method for the objective biomization of pollen samples based on fuzzy logic. Pollen types (taxa) are assigned to one or more plant functional types (PFTs), then affinity scores are calculated for each biome in turn based on its list of characteristic PFTs. The pollen sample is assigned to the biome to which it has the highest affinity, subject to a tie-breaking rule. Modern pollen data from surface samples, reflecting present vegetation across Europe, are used to validate the method. Pollen data from dated sediment cores are then used to reconstruct European vegetation patterns for 6 ka. The reconstruction shows systematic differences from present that are consistent with previous interpretations. The method has proved robust with respect to human impacts on vegetation, and provides a rational way to interpret combinations of pollen types that do not have present-day analogs. The method demands minimal prior information and is therefore equally suitable for use in other regions with richer floras, and/or lower densities of available modern and fossil pollen samples, than Europe.

Notes: Abstract. Biome models allow the results of experiments with atmospheric general circulation models to be translated into global maps of potential natural vegetation. The use of biome models as a diagnostic tool for palaeoclimate simulations can yield maps that are directly comparable with palaeoecological (pollen and plant macrofossil) records provided these records are "biomized", i.e. assigned to biomes in a consistent way. This article describes a method for the objective biomization of pollen samples based on fuzzy logic. Pollen types (taxa) are assigned to one or more plant functional types (PFTs), then affinity scores are calculated for each biome in turn based on its list of characteristic PFTs. The pollen sample is assigned to the biome to which it has the highest affinity, subject to a tie-breaking rule. Modern pollen data from surface samples, reflecting present vegetation across Europe, are used to validate the method. Pollen data from dated sediment cores are then used to reconstruct European vegetation patterns for 6 ka. The reconstruction shows systematic differences from present that are consistent with previous interpretations. The method has proved robust with respect to human impacts on vegetation, and provides a rational way to interpret combinations of pollen types that do not have present-day analogs. The method demands minimal prior information and is therefore equally suitable for use in other regions with richer floras, and/or lower densities of available modern and fossil pollen samples, than Europe.

Notes: Abstract The static properties of an arc near a plane surface have been analyzed by extending Maecker's method to bi-cylindrical coordinates. A direct numerical solution was also carried out. The general method of Phillips was then used to predict the transient properties. Experimental data was taken on the static and dynamic properties of arcs burning near dry and wet surfaces. Agreement with theory was much better for dry surfaces, suggesting that humidity in the arc greatly affects the static and dynamic properties.