Statistical–dynamical downscaling of present day and future precipitation regimes in the Aksu river catchment in Central Asia

A statistical–dynamical downscaling (SDD) approach is applied to determine present day and future high-resolution rainfall distributions in the catchment of the river Aksu at the southern slopes of the Tienshan Mountains, Central Asia. First, a circulation weather type (CWT) classification is employed to define typical lower atmospheric flow regimes from ERA-40 reanalysis data. Selected representatives of each CWT are dynamically downscaled with the regional climate model COSMO-CLM 4.8 at a horizontal grid resolution of 0.0625°, using the ERA-40 reanalysis data as boundary conditions. Finally, the simulated representatives are recombined to obtain a high-resolution rainfall climatology for present day climate. The methodology is also applied to ensemble simulations of three different scenarios of the global climate model ECHAM5/MPI-OM1 to derive projections of rainfall changes until 2100. Comparisons of downscaled seasonal and annual rainfall with observational data suggest that the statistical–dynamical approach is appropriate to capture the observed present-day precipitation climatology over the low lands and the first elevations of the Tienshan Mountains. On the other hand, a strong bias is found at higher altitudes, where precipitation is clearly underestimated by SDD. The application of SDD to the ECHAM5/MPI-OM1 ensemble reveals that precipitation changes by the end of the 21st century depend on the season. While for autumn an increase of seasonal precipitation is found for all simulations, a decrease in precipitation is obtained during winter for most parts of the Aksu catchment. The spread between different ECHAM5/MPI-OM1 ensemble members is strongest in spring, where trends of opposite sign are found. The largest changes in rainfall are simulated for the summer season, which also shows the most pronounced spatial heterogeneity. Most ECHAM5/MPI-OM1 realizations indicate a decrease of annual precipitation over large parts of the Tienshan, and an increase restricted to the southeast of the study area. These results provide a good basis for downscaling present-day and future rainfall distributions for hydrological purposes.

Are greenhouse gas signals of Northern Hemisphere winter extra-tropical cyclone activity dependent on the identification and tracking algorithm?

For Northern Hemisphere extra-tropical cyclone activity, the dependency of a potential anthropogenic climate change signal on the identification method applied is analysed. This study investigates the impact of the used algorithm on the changing signal, not the robustness of the climate change signal itself. Using one single transient AOGCM simulation as standard input for eleven state-of-the-art identification methods, the patterns of model simulated present day climatologies are found to be close to those computed from re-analysis, independent of the method applied. Although differences in the total number of cyclones identified exist, the climate change signals (IPCC SRES A1B) in the model run considered are largely similar between methods for all cyclones. Taking into account all tracks, decreasing numbers are found in the Mediterranean, the Arctic in the Barents and Greenland Seas, the mid-latitude Pacific and North America. Changing patterns are even more similar, if only the most severe systems are considered: the methods reveal a coherent statistically significant increase in frequency over the eastern North Atlantic and North Pacific. We found that the differences between the methods considered are largely due to the different role of weaker systems in the specific methods.

The variable link between PNA and NAO in observations and in multi-century CGCM simulations

The link between the Pacific/North American pattern (PNA) and the North Atlantic Oscillation (NAO) is investigated in reanalysis data (NCEP, ERA40) and multi-century CGCM runs for present day climate using three versions of the ECHAM model. PNA and NAO patterns and indices are determined via rotated principal component analysis on monthly mean 500 hPa geopotential height fields using the varimax criteria. On average, the multi-century CGCM simulations show a significant anti-correlation between PNA and NAO. Further, multi-decadal periods with significantly enhanced (high anti-correlation, active phase) or weakened (low correlations, inactive phase) coupling are found in all CGCMs. In the simulated active phases, the storm track activity near Newfoundland has a stronger link with the PNA variability than during the inactive phases. On average, the reanalysis datasets show no significant anti-correlation between PNA and NAO indices, but during the sub-period 1973–1994 a significant anti-correlation is detected, suggesting that the present climate could correspond to an inactive period as detected in the CGCMs. An analysis of possible physical mechanisms suggests that the link between the patterns is established by the baroclinic waves forming the North Atlantic storm track. The geopotential height anomalies associated with negative PNA phases induce an increased advection of warm and moist air from the Gulf of Mexico and cold air from Canada. Both types of advection contribute to increase baroclinicity over eastern North America and also to increase the low level latent heat content of the warm air masses. Thus, growth conditions for eddies at the entrance of the North Atlantic storm track are enhanced. Considering the average temporal development during winter for the CGCM, results show an enhanced Newfoundland storm track maximum in the early winter for negative PNA, followed by a downstream enhancement of the Atlantic storm track in the subsequent months. In active (passive) phases, this seasonal development is enhanced (suppressed). As the storm track over the central and eastern Atlantic is closely related to the NAO variability, this development can be explained by the shift of the NAO index to more positive values.

Pediastrum species as potential indicators of lake-level change in tropical South America

We explored the potential for using Pediastrum (Meyen), a genus of green alga commonly found in palaeoecological studies, as a proxy for lake-level change in tropical South America. The study site, Laguna La Gaiba (LLG) (17°45′S, 57°40′W), is a broad, shallow lake located along the course of the Paraguay River in the Pantanal, a 135,000-km2 tropical wetland located mostly in western Brazil, but extending into eastern Bolivia. Fourteen surface sediment samples were taken from LLG across a range of lake depths (2-5.2 m) and analyzed for Pediastrum. We found seven species, of which P. musteri (Tell et Mataloni), P. argentiniense (Bourr. et Tell), and P. cf. angulosum (Ehrenb.) ex Menegh. were identified as potential indicators of lake level. Results of the modern dataset were applied to 31 fossil Pediastrum assemblages spanning the early Holocene (12.0 kyr BP) to present to infer past lake level changes qualitatively. Early Holocene (12.0-9.8 kyr BP) assemblages do not show a clear signal, though abundance of P. simplex (Meyen) suggests relatively high lake levels. Absence of P. musteri, characteristic of deep, open water, and abundance of macrophyte-associated taxa indicate lake levels were lowest from 9.8 to 3.0 kyr BP. A shift to wetter conditions began at 4.4 kyr BP, indicated by the appearance of P. musteri, though inferred lake levels did not reach modern values until 1.4 kyr BP. The Pediastrum-inferred mid-Holocene lowstand is consistent with lower precipitation, previously inferred using pollen from this site, and is also in agreement with evidence for widespread drought in the South American tropics during the middle Holocene. An inference for steadily increasing lake level from 4.4 kyr BP to present is consistent with diatom-inferred water level rise at Lake Titicaca, and demonstrates coherence with the broad pattern of increasing monsoon strength from the late Holocene until present in tropical South America.

A 45 kyr palaeoclimate record from the lowland interior of tropical South America

We present a well-dated, high-resolution, ~ 45 kyr lake sediment record reflecting regional temperature and precipitation change in the continental interior of the Southern Hemisphere (SH) tropics of South America. The study site is Laguna La Gaiba (LLG), a large lake (95 km2) hydrologically-linked to the Pantanal, an immense, seasonally-flooded basin and the world's largest tropical wetland (135,000 km2). Lake-level changes at LLG are therefore reflective of regional precipitation. We infer past fluctuations in precipitation at this site through changes in: i) pollen-inferred extent of flood-tolerant forest; ii) relative abundance of terra firme humid tropical forest versus seasonally-dry tropical forest pollen types; and iii) proportions of deep- versus shallow-water diatoms. A probabilistic model, based on plant family and genus climatic optima, was used to generate quantitative estimates of past temperature from the fossil pollen data. Our temperature reconstruction demonstrates rising temperature (by 4 °C) at 19.5 kyr BP, synchronous with the onset of deglacial warming in the central Andes, strengthening the evidence that climatic warming in the SH tropics preceded deglacial warming in the Northern Hemisphere (NH) by at least 5 kyr. We provide unequivocal evidence that the climate at LLG was markedly drier during the last glacial period (45.0–12.2 kyr BP) than during the Holocene, contrasting with SH tropical Andean and Atlantic records that demonstrate a strengthening of the South American summer monsoon during the global Last Glacial Maximum (~ 21 kyr BP), in tune with the ~ 20 kyr precession orbital cycle. Holocene climate conditions occurred as early as 12.8–12.2 kyr BP, when increased precipitation in the Pantanal catchment caused heightened flooding and rising lake levels in LLG. In contrast to this strong geographic variation in LGM precipitation across the continent, expansion of tropical dry forest between 10 and 3 kyr BP at LLG strengthens the body of evidence for widespread early–mid Holocene drought across tropical South America.

Pollen-based differentiation of Amazonian rainforest communities and implications for lowland palaeoecology in tropical South America

An ongoing controversy in Amazonian palaeoecology is the manner in which Amazonian rainforest communities have responded to environmental change over the last glacial–interglacial cycle. Much of this controversy results from an inability to identify the floristic heterogeneity exhibited by rainforest communities within fossil pollen records. We apply multivariate (Principal Components Analysis) and classification (Unweighted Pair Group with Arithmetic Mean Agglomerative Classification) techniques to floral-biometric, modern pollen trap and lake sediment pollen data situated within different rainforest communities in the tropical lowlands of Amazonian Bolivia. Modern pollen rain analyses from artificial pollen traps show that evergreen terra firme (well-drained), evergreen terra firme liana, evergreen seasonally inundated, and evergreen riparian rainforests may be readily differentiated, floristically and palynologically. Analogue matching techniques, based on Euclidean distance measures, are employed to compare these pollen signatures with surface sediment pollen assemblages from five lakes: Laguna Bella Vista, Laguna Chaplin, and Laguna Huachi situated within the Madeira-Tapajós moist forest ecoregion, and Laguna Isirere and Laguna Loma Suarez, which are situated within forest patches in the Beni savanna ecoregion. The same numerical techniques are used to compare rainforest pollen trap signatures with the fossil pollen record of Laguna Chaplin.

Pollen-based biome reconstructions for Latin America at 0, 6000 and 18000 radiocarbon years

The biomisation method is used to reconstruct Latin American vegetation at 6000±500 and 18 000±1000 radiocarbon years before present (14C yr BP) from pollen data. Tests using modern pollen data from 381 samples derived from 287 locations broadly reproduce potential natural vegetation. The strong temperature gradient associated with the Andes is recorded by a transition from high altitude cool grass/shrubland and cool mixed forest to mid-altitude cool temperate rain forest, to tropical dry, seasonal and rain forest at low altitudes. Reconstructed biomes from a number of sites do not match the potential vegetation due to local factors such as human impact, methodological artefacts and mechanisms of pollen representivity of the parent vegetation.

Generalised Bayesian cloud detection for satellite imagery. part 2: technique and validation for day-time imagery

Numerical Weather Prediction (NWP) fields are used to assist the detection of cloud in satellite imagery. Simulated observations based on NWP are used within a framework based on Bayes' theorem to calculate a physically-based probability of each pixel with an imaged scene being clear or cloudy. Different thresholds can be set on the probabilities to create application-specific cloud masks. Here, the technique is shown to be suitable for daytime applications over land and sea, using visible and near-infrared imagery, in addition to thermal infrared. We use a validation dataset of difficult cloud detection targets for the Spinning Enhanced Visible and Infrared Imager (SEVIRI) achieving true skill scores of 89% and 73% for ocean and land, respectively using the Bayesian technique, compared to 90% and 70%, respectively for the threshold-based techniques associated with the validation dataset.

Sustainable agricultural intensification or Jevons paradox? The role of public governance in tropical South America

The process of global deforestation calls for urgent attention, particularly in South America where deforestation rates have failed to decline over the past 20 years. The main direct cause of deforestation is land conversion to agriculture. We combine data from the FAO and the World Bank for six tropical Southern American countries over the period 1970–2006, estimate a panel data model accounting for various determinants of agricultural land expansion and derive elasticities to quantify the effect of the different independent variables. We investigate whether agricultural intensification, in conjunction with governance factors, has been promoting agricultural expansion, leading to a ‘‘Jevons paradox’’. The paradox occurs if an increase in the productivity of one factor (here agricultural land) leads to its increased, rather than decreased, utilization. We find that for high values of our governance indicators a Jevons paradox exists even for moderate levels of agricultural productivity, leading to an overall expansion of agricultural area. Agricultural expansion is also positively related to the level of service on external debt and population growth, while its association with agricultural exports is only moderate. Finally, we find no evidence of an environmental Kuznets curve, as agricultural area is ultimately positively correlated to per-capita income levels.

A 27 day persistence model of near-Earth solar wind conditions: a long lead-time forecast and a benchmark for dynamical models

Geomagnetic activity has long been known to exhibit approximately 27 day periodicity, resulting from solar wind structures repeating each solar rotation. Thus a very simple near-Earth solar wind forecast is 27 day persistence, wherein the near-Earth solar wind conditions today are assumed to be identical to those 27 days previously. Effective use of such a persistence model as a forecast tool, however, requires the performance and uncertainty to be fully characterized. The first half of this study determines which solar wind parameters can be reliably forecast by persistence and how the forecast skill varies with the solar cycle. The second half of the study shows how persistence can provide a useful benchmark for more sophisticated forecast schemes, namely physics-based numerical models. Point-by-point assessment methods, such as correlation and mean-square error, find persistence skill comparable to numerical models during solar minimum, despite the 27 day lead time of persistence forecasts, versus 2–5 days for numerical schemes. At solar maximum, however, the dynamic nature of the corona means 27 day persistence is no longer a good approximation and skill scores suggest persistence is out-performed by numerical models for almost all solar wind parameters. But point-by-point assessment techniques are not always a reliable indicator of usefulness as a forecast tool. An event-based assessment method, which focusses key solar wind structures, finds persistence to be the most valuable forecast throughout the solar cycle. This reiterates the fact that the means of assessing the “best” forecast model must be specifically tailored to its intended use.

Analysis of precipitation climatology simulated by high resolution coupled global models over the South America

The results of coupled high resolution global models (CGCMs) over South America are discussed. HiGEM1.2 and HadGEM1.2 simulations, with horizontal resolution of ~90 and 135 km, respectively, are compared. Precipitation estimations from CMAP (Climate Prediction Center—Merged Analysis of Precipitation), CPC (Climate Prediction Center) and GPCP (Global Precipitation Climatology Project) are used for validation. HiGEM1.2 and HadGEM1.2 simulated seasonal mean precipitation spatial patterns similar to the CMAP. The positioning and migration of the Intertropical Convergence Zone and of the Pacific and Atlantic subtropical highs are correctly simulated by the models. In HiGEM1.2 and HadGEM1.2, the intensity and locations of the South Atlantic Convergence Zone are in agreement with the observed dataset. The simulated annual cycles are in phase with estimations of rainfall for most of the six regions considered. An important result is that HiGEM1.2 and HadGEM1.2 eliminate a common problem of coarse resolution CGCMs, which is the simulation of a semiannual cycle of precipitation due to the semiannual solar forcing. Comparatively, the use of high resolution in HiGEM1.2 reduces the dry biases in the central part of Brazil during austral winter and spring and in most part of the year over an oceanic box in eastern Uruguay.

Which of satellite- or model-based estimates is closer to reality for aerosol indirect forcing?

In their contribution to PNAS, Penner et al. (1) used a climate model to estimate the radiative forcing by the aerosol first indirect effect (cloud albedo effect) in two different ways: first, by deriving a statistical relationship between the logarithm of cloud droplet number concentration, ln Nc, and the logarithm of aerosol optical depth, ln AOD (or the logarithm of the aerosol index, ln AI) for present-day and preindustrial aerosol fields, a method that was applied earlier to satellite data (2), and, second, by computing the radiative flux perturbation between two simulations with and without anthropogenic aerosol sources. They find a radiative forcing that is a factor of 3 lower in the former approach than in the latter [as Penner et al. (1) correctly noted, only their “inline” results are useful for the comparison]. This study is a very interesting contribution, but we believe it deserves several clarifications.