Initiation of a Stable Convective Hydroclimatic Regime in Central America Circa 9000 Years BP

Many Holocene hydroclimate records show rainfall changes that vary with local orbital insolation. However, some tropical regions display rainfall evolution that differs from gradual precessional pacing, suggesting that direct rainfall forcing effects were predominantly driven by sea-surface temperature thresholds or inter-ocean temperature gradients. Here we present a 12,000 yr continuous U/Th-dated precipitation record from a Guatemalan speleothem showing that Central American rainfall increased within a 2000 yr period from a persistently dry state to an active convective regime at 9000 yr BP and has remained strong thereafter. Our data suggest that the Holocene evolution of Central American rainfall was driven by exceeding a temperature threshold in the nearby tropical oceans. The sensitivity of this region to slow changes in radiative forcing is thus strongly mediated by internal dynamics acting on much faster time scales

Dynamics of a salinity-prone agricultural catchment driven by markets, farmers' attitude and climate change

An agent-based simulation model has been developed with CORMAS combining simplified bio-physical processes of land cover, dry-land salinity changes, rainfall, farm profitability and farmer decisions on land uses in a dry-land agricultural catchment (no irrigation). Simulated farmers formulate individual decisions dealing with land use changes based on the combined performance of their past land cover productivity and market returns. The willingness to adapt to market drivers and the ability to maximize returns varies across farmers. In addition, farmers in the model can demonstrate various attitudes towards salinity mitigation as a consequence of experiencing and perceiving salinity on their farm, in the neighborhood or in the entire region. Consequently, farmers can adopt land cover strategies aiming at reducing salinity impact. The simulation results using historical rainfall records reproduces similar trends of crop-pasture ratios, salinity change and farm decline as observed in the last 20 years in the Katanning catchment (Western Australia). Using the model as an explorative tool for future scenarios, the simulation results highlighted the importance of rainfall changes and wide-spread willingness of farmers to combat dry-land salinity. Rainfall changes as a consequence of climate change can lead to prolonged sequences of dry and wet seasons. Adaptation to these sequences by farmers seems to be critical for farm survival in this catchment. (Résumé d'auteur

Climatic and oceanic associations with daily rainfall extremes over southern Africa

Changes in climate variability and, in particular, changes in extreme climate events are likely to be of far more significance for environmentally vulnerable regions than changes in the mean state. It is generally accepted that sea-surface temperatures (SSTs) play an important role in modulating rainfall variability. Consequently, SSTs can be prescribed in global and regional climate modelling in order to study the physical mechanisms behind rainfall and its extremes. Using a satellite-based daily rainfall historical data set, this paper describes the main patterns of rainfall variability over southern Africa, identifies the dates when extreme rainfall occurs within these patterns, and shows the effect of resolution in trying to identify the location and intensity of SST anomalies associated with these extremes in the Atlantic and southwest Indian Ocean. Derived from a Principal Component Analysis (PCA), the results also suggest that, for the spatial pattern accounting for the highest amount of variability, extremes extracted at a higher spatial resolution do give a clearer indication regarding the location and intensity of anomalous SST regions. As the amount of variability explained by each spatial pattern defined by the PCA decreases, it would appear that extremes extracted at a lower resolution give a clearer indication of anomalous SST regions

Changes in land cover, rainfall and stream flow in Upper Gilgel Abbay catchment, Blue Nile basin – Ethiopia

In this study we evaluated changes in land cover and rainfall in the Upper Gilgel Abbay catchment in the Upper Blue Nile basin and how changes affected stream flow in terms of annual flow, high flows and low flows. Land cover change assessment was through classification analysis of remote sensing based land cover data while assessments on rainfall and stream flow data are by statistical analysis. Results of the supervised land cover classification analysis indicated that 50.9 % and 16.7 % of the catchment area was covered by forest in 1973 and 2001, respectively. This significant decrease in forest cover is mainly due to expansion of agricultural land. \ud \ud By use of a change detection procedure, three periods were identified for which changes in rainfall and stream flow were analyzed. Rainfall was analyzed at monthly base by use of the Mann-Kendall test statistic and results indicated a statistically significant, decreasing trend for most months of the year. However, for the wet season months of June, July and August rainfall has increased. In the period 1973–2005, the annual flow of the catchment decreased by 12.1 %. Low flow and high flow at daily base were analyzed by a low flow and a high flow index that is based on a 95 % and 5 % exceedance probability. Results of the low flow index indicated decreases of 18.1 % and 66.6 % for the periods 1982–2000 and 2001–2005 respectively. Results of high flows indicated an increase of 7.6 % and 46.6 % for the same periods. In this study it is concluded that over the period 1973–2005 stream flow has changed in the Gilgel Abbay catchment by changes in land cover and changes in rainfall

The local impacts of climate change in the Ferlo, Western Sahel

Recent increases in the accuracy of climate models have enhanced the possibilities for analyzing the impacts of climate change on society. This paper explores how the local, economic impacts of climate change can be modeled for a specific eco-region, the Western Sahel. The people in the Sahel are highly dependent on their natural resource base, and these resources are highly vulnerable to climate change, in particular to changes in rainfall. Climate models project substantial changes in rainfall in the Sahel in the coming 50 years, with most models predicting a reduction in rainfall. To connect climate change to changes in ecosystem productivity and local income, we construct an ecological¿economic model that incorporates rangeland dynamics, grazing and livestock prices. The model shows that decreased rainfall in the Sahel will considerably reduce local incomes, in particular if combined with increases in rainfall variability. Adaptation to these climate change projections is possible if reductions in rainfall are followed by destocking to reach efficient grazing levels. However, while such a strategy is optimal from the perspective of society, the stocking rate is determined by individual pastoralists that face few incentives to destoc

Persistent Decadal-Scale Rainfall Variability in the Tropical South Pacific Convergence Zone Through the Past Six Centuries

Modern Pacific decadal variability (PDV) has global impacts; hence records of PDV from the pre-instrumental period are needed to better inform models that are used to project future climate variability. We focus here on reconstructing rainfall in the western tropical Pacific (Solomon Islands; similar to 9.5 degrees S, similar to 160 degrees E), a region directly influenced by PDV, using cave deposits (stalagmite). A relationship is developed between delta O-18 variations in the stalagmite and local rainfall amount to produce a 600 yr record of rainfall variability from the South Pacific Convergence Zone (SPCZ). We present evidence for large (similar to 1.5 m), abrupt, and periodic changes in total annual rainfall amount on decadal to multidecadal timescales since 1423 +/- 5 CE (Common Era) in the Solomon Islands. The timing of the decadal changes in rainfall inferred from the 20th-century portion of the stalagmite delta O-18 record coincides with previously identified decadal shifts in PDV-related Pacific ocean-atmosphere behavior (Clement et al., 2011; Deser et al., 2004). The Solomons record of PDV is not associated with variations in external forcings, but rather results from internal climate variability. The 600 yr Solomon Islands stalagmite delta O-18 record indicates that decadal oscillations in rainfall are a persistent characteristic of SPCZ-related climate variability.Taiwan ROC NSCNTU 101-2116-M-002-009, 102-2116-M-002-016, 101R7625Geological Science

The O and H stable isotope composition of freshwaters in the British Isles. 1, rainfall

An understanding of the hydrological cycle in stable isotopic terms requires the characterisation of rainfall. This paper reviews existing and new data for the British Isles. Rainfall at the Wallingford (Oxfordshire) collection station was collected daily from November 1979 to October 1980. Large variations in isotopic content were noted, sometimes from day to day. Winter rainfall was similar to summer in amount, and only slightly depleted isotopically. Amount and temperature correlations with δ18O were generally low, only the autumn and winter temperature relationships being significant. A 20-year monthly dataset from 1982 to 2001 for Wallingford gives the following regression: δ2H = 7.0δ18O + 1.2, a slope somewhat below the world meteoric line but consistent with the those from other long-term stations in NW Europe. The data showed uncorrelated maxima and minima for each year, but rather more consistent amount-weighted averages. Although there is only a small difference in gradient between summer and winter rainfall values, when plotted against the month of the year there are clear changes in the values of both isotopes, and the δ2H-δ18O relationship as demonstrated by the d-excess parameter. The isotope-amount correlation is low but significant, with summer months appearing to be well-correlated when considered in terms of month of the year. On this same seasonal basis temperature has a strong correlation throughout the year, giving a positive δ18O-temperature relationship of 0.25 ‰ per °C change. The Wallingford monthly record is compared with data from Keyworth (Nottinghamshire) and the Valentia station of the GNIP (IAEA-WMO Global Network for Isotopes in Precipitation) in SW Ireland. While not large, differences between the stations are broadly attributable to the balance between maritime and continental influences. Over the period September 1981 to August 1982 the maximum number of monthly collection stations was operating across the British Isles. While a comparison of the sites serves mostly to illustrate the variability of British weather in space and time, there is clear isotopic evidence for the predominance of frontal rainfall in winter and convective rainfall in summer. The effect of altitude on isotopic content was measured within a high-relief stream catchment in Scotland. The best correlations occurred during winter, when an average relationship of approximately –0.30 ‰ δ18O per 100 m increase in altitude was observed. It is well established that rainfall isotopic composition changes in response to alterations in climate. However these changes are difficult to detect isotopically in the short term, even when the changes are indexed, e.g. in the form of the NAO (North Atlantic Oscillation). The brief duration of rainfall isotope records is a further hindrance; for the British Isles proxies such as tree-ring cellulose may have some value in extending the record back

Analysis of 1982-2006 sudano-sahelian vegetation dynamics using NOAA-AVHRR NDVI data and normalized rain-used efficiency

Land cover dynamic has to be taken into account to analyze changes in water resources, especially in vulnerable environment such as the Bani catchment in Mali. To study the land cover changes, we used NDVI AVHRR time series (1982-2006, 8 km spatial resolution), and monthly rainfall data from 65 stations. To interpret the NDVI trends in terms of land cover changes, we had to eliminate the inter-annual rainfall variability. We used the concept of the Rain Use Efficiency (RUE) which is the ratio between NDVI (a proxy of the Net Primary Production) and precipitation. RUE and rainfall were calculated and modeled on a 0.5° x 0.5° grid scale. For each cell we normalized the evolution of the RUE through time (RUE_cor), and calculated its trend over the 25 years period. The results indicate that RUE_cor is stable or in light increase for most of the grid cells. In areas where water is not a limiting factor of NPP, this trend is positively correlated to the fraction of cropped area changes, as determined from a couple of Landsat images acquired during a similar period. However, RUE is a complex concept and further investigations are needed to consolidate our results and conclusions. (Résumé d'auteur

Uncertainty Quantification of Future Design Rainfall Depths in Korea

One of the most common ways to investigate changes in future rainfall extremes is to use future rainfall data simulated by climate models with climate change scenarios. However, the projected future design rainfall intensity varies greatly depending on which climate model is applied. In this study, future rainfall Intensity???Duration???Frequency (IDF) curves are projected using various combinations of climate models. Future Ensemble Average (FEA) is calculated using a total of 16 design rainfall intensity ensembles, and uncertainty of FEA is quantified using the coefficient of variation of ensembles. The FEA and its uncertainty vary widely depending on how the climate model combination is constructed, and the uncertainty of the FEA depends heavily on the inclusion of specific climate model combinations at each site. In other words, we found that unconditionally using many ensemble members did not help to reduce the uncertainty of future IDF curves. Finally, a method for constructing ensemble members that reduces the uncertainty of future IDF curves is proposed, which will contribute to minimizing confusion among policy makers in developing climate change adaptation policies

Improving predictive power of physically based rainfall-induced shallow landslide models: a probabilistic approach

Distributed models to forecast the spatial and temporal occurrence of rainfall-induced shallow landslides are based on deterministic laws. These models extend spatially the static stability models adopted in geotechnical engineering, and adopt an infinite-slope geometry to balance the resisting and the driving forces acting on the sliding mass. An infiltration model is used to determine how rainfall changes pore-water conditions, modulating the local stability/instability conditions. A problem with the operation of the existing models lays in the difficulty in obtaining accurate values for the several variables that describe the material properties of the slopes. The problem is particularly severe when the models are applied over large areas, for which sufficient information on the geotechnical and hydrological conditions of the slopes is not generally available. To help solve the problem, we propose a probabilistic Monte Carlo approach to the distributed modeling of rainfall-induced shallow landslides. For the purpose, we have modified the Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability Analysis (TRIGRS) code. The new code (TRIGRS-P) adopts a probabilistic approach to compute, on a cell-by-cell basis, transient pore-pressure changes and related changes in the factor of safety due to rainfall infiltration. Infiltration is modeled using analytical solutions of partial differential equations describing one-dimensional vertical flow in isotropic, homogeneous materials. Both saturated and unsaturated soil conditions can be considered. TRIGRS-P copes with the natural variability inherent to the mechanical and hydrological properties of the slope materials by allowing values of the TRIGRS model input parameters to be sampled randomly from a given probability distribution. [..]Comment: 25 pages, 14 figures, 9 tables. Revised version; accepted for publication in Geoscientific Model Development on 13 February 201