Land-atmosphere interactions

Saharan dust is shown to enter the Central Amazon Basin (CAB) in bursts which accompany major wet season rain systems. Low-level horizontal convergence feeding these rain systems draws dust from plumes which have crossed the tropical Atlantic under the large-scale circulation fields. Mass exchange of air between the surface and 4km over the eastern Amazon basin is calculated using rawinsonde data collected during storm events. Mean concentrations of dust observed by aircraft over the western tropical Atlantic are used to calculate the amount of dust injected into the Basin. Individual storm events inject some 480,000 tons of dust into the north-eastern Amazon Basin. Storm and dust climatology suggest that the annual importation of dust is in the order of 13 Mtons. In the north-eastern basin, this may amount to as much as 190kg ha<img src="/entityImage/script/2212.gif" alt="-" border="0" style="font-weight: bold"></img>1 yr<img src="/entityImage/script/2212.gif" alt="-" border="0" style="font-weight: bold"></img>1. Deposition of trace species, such as phosphate, associated with this dust ranges from 1-4kg ha<img src="/entityImage/script/2212.gif" alt="-" border="0" style="font-weight: bold"></img>1 yr<img src="/entityImage/script/2212.gif" alt="-" border="0" style="font-weight: bold"></img>1. Uncertainties in these estimates are not believed to be greater than ± 50% and may be as low as±20%. The deposition fluxes from Saharan dust are essentially identical to the CAB wet deposition fluxes from precipitation in the wet season; a result that implies that the major ionic composition of rain water in the CAB wet season may be strongly influenced by inputs of material originating on the African continent nearly 5000km away. The total amount of Saharan dust calculated to enter the Amazon basin is 1/2 to 1/3 of that estimated to cross 60°W longitude between 10° and 25°N latitude. We conclude that part of the productivity of the Amazon rain forest is dependent upon critical trace elements contained in the soil dust originating in the Sahara/Sahel. This dependence should be reflected by expansions and contractions of the Amazon rain forest in direct relationship to expansions and contractions of the Sahara/Sahel. Turnover rates for nutrient species deposited with Saharan dust in the Amazon Basin suggest a time scale of 500 to 20,000years. We believe the dependence of one large ecosystem upon another separated by an ocean and coupled by the atmosphere to be fundamentally important to any view of how the global system functions. Any strategy designed to preserve the Amazonian rain forest or any part thereof should equally concern itself with the inter-relationship between the rain forest, global climate and arid zones well removed from Amazonia.

As a unique geological and geographical unit, the Tibetan Plateau dramatically impacts the world's environment and especially controls climatic and environmental changes in China, Asia and even in the Northern Hemisphere. Tibetan Plateau, therefore, provides a field laboratory for studying global change. With support from various agencies in the People's Republic of China, a Tibetan Observation and Research Platform (TORP) is now implementing. Firstly the background of the establishment of the TORP, the establishing and monitoring plan of long-term scale (5-10 years) of the TORP has been introduced. Then the preliminary observational analysis results, such as the characteristics of land surface heat fluxes and CO 2 flux partitioning (diurnal variation and inter-monthly variation etc.), the characteristics of atmospheric and soil variables, the structure of the Atmospheric Boundary Layer (ABL) and the turbulent characteristics have also been shown in this paper.

Large-scale cultivation of perennial bioenergy crops (e.g., miscanthus and switchgrass) offers unique opportunities to mitigate climate change through avoided fossil fuel use and associated greenhouse gas reduction. Although conversion of existing agriculturally intensive lands (e.g., maize and soy) to perennial bioenergy cropping systems has been shown to reduce near-surface temperatures, unintended consequences on natural water resources via depletion of soil moisture may offset these benefits. The hydroclimatic impacts associated with perennial bioenergy crop expansion over the contiguous United States are quantified using the Weather Research and Forecasting Model dynamically coupled to a land surface model (LSM). A suite of continuous (2000–09) medium-range resolution (20-km grid spacing) ensemble-based simulations is conducted using seasonally evolving biophysical representation of perennial bioenergy cropping systems within the LSM based on observational data. Deployment is carried out only over suitable abandoned and degraded farmlands to avoid competition with existing food cropping systems. Results show that near-surface cooling (locally, up to 58C) is greatest during the growing season over portions of the central United States. For some regions, principal impacts are restricted to a reduction in near-surface temperature (e.g., eastern portions of the United States), whereas for other regions deployment leads to soil moisture reduction in excess of 0.15–0.2 m 3 m 23 during the simulated 10-yr period (e.g., western Great Plains). This reduction (;25%–30% of available soil moisture) manifests as a progressively decreasing trend over time. The large-scale focus of this research demonstrates the long-term hydroclimatic sustainability of large-scale deployment of perennial bioenergy crops across the continental United States, revealing potential hot spots of suitable deployment and regions to avoid.

We couple a single column model (SCM) to a cutting-edge single-layer urban canopy model (SLUCM) with realistic representation of urban hydrological processes. The land-surface transport of energy and moisture parametrized by the SLUCM provides lower boundary conditions to the overlying atmosphere. The coupled SLUCM–SCM model is tested against field measurements of sensible and latent heat fluxes in the surface layer, as well as vertical profiles of temperature and humidity in the mixed layer under convective conditions. The model is then used to simulate urban land–atmosphere interactions by changing urban geometry, surface albedo, vegetation fraction and aerodynamic roughness. Results show that changes of landscape characteristics have a significant impact on the growth of the boundary layer as well as on the distributions of temperature and humidity in the mixed layer. Overall, the proposed numerical framework provides a useful stand-alone modelling tool, with which the impact of urban land-surface conditions on the local hydrometeorology can be assessed via land–atmosphere interactions.

Generally, surface and air temperatures seem closely related but we show that they respond differently to evaporative conditions. We evaluate the temperature increase in response to solar radiation for different evaporative fractions, using observations from the Southern Great Plains. The warming rate of air temperature decreases only by 1.7 × 10 −3 K/(W m −2) from dry to moist conditions compared to a stronger reduction by 14 × 10 −3 K/(W m −2) for surface temperature. The weaker response of air temperature to evaporative fraction is explained by the larger growth of boundary layer on drier days, which suppresses the warming of air. Estimates based on this explanation reproduce the warming rate of air temperature in observations. Our results show that diurnal variations of surface temperatures contain imprints of evapotranspiration while air temperatures do not. These findings appear important to be considered when using, analyzing, or interpreting temperature data in studies dealing with climate change, hydrology, or land-atmosphere interactions. Plain Language Summary Surface and air temperatures are measured just 2 m apart, so it might seem that they carry the same information. Here we show that these temperature measurements respond rather differently to whether the surface evaporates or not. To show this, we use data from a well-equipped measurement site in the Central United States and calculate the rates by which the surface and the air warm in response to solar radiation. We found that the surface temperature responds about 8 times stronger to evaporation than air temperature. We explain this weaker response of air temperature by the stronger growth of the boundary layer without evaporation. This results in a deeper, well-mixed boundary layer that does not warm as strongly. What our results imply is that evaporation may be inferred from surface temperatures, but not from air temperatures.

This paper demonstrates a methodology for modeling the groundwater table fluctuations observed in a shallow unconfined aquifer of Bangladesh. For this purpose, Kushtia district of Bangladesh has been selected as a case study area. A groundwater table monitoring well is selected in each upazilla (sub-district) under the study area. The time series water table observations collected on a weekly basis during the period from 1999 to 2006 from each well is used for experiments. Empirical result demonstrates that observed data of groundwater level exhibits cyclic patterns and shows an annual periodicity. Box and Jenkins univariate stochastic models widely known as ARIMA, are applied to simulate groundwater table fluctuations in all monitoring wells under consideration in the study area. The predicted data using the best models are compared to the observed time series and the resulting accuracy is checked using different error parameters. The simulation revealed that ARIMA models generate reasonably accurate forecasts in terms of numerical accuracy. The results also showed that the predicted data represent the actual data very well for each monitoring well.

Spatial and temporal near-surface air temperature variabilities and trends were analyzed for 30 locations in Illinois based on annual data derived from station records and the North American Regional Reanalysis (NARR) dataset from 1979 to 2006. A high correlation was found between the two datasets for interannual variability at most locations. Temperatures were generally higher at urban stations than non-urban stations, while non-urban NARR data points showed higher temperatures than urban data points. Differences in medians ...

The coastal belt in the southwestern Bangladesh is facing a unique problem compared to other parts of the country because of the direct interaction of the saline surface water (SW) from the coastal rivers and nearby sea with the fresh groundwater (GW) in the underlying aquifers. In this study, an integrated river-aquifer model is developed for the shallow unconfined aquifer in the southwestern Bangladesh to simulate the GW flow characteristics and dynamic flow exchanges between the rivers and aquifer systems. Well-known USGS numerical code for GW flow simulation, MODFLOW and its river simulation package (RIV) are applied in the framework of GW Modeling System (GMS) software, which is satisfactorily calibrated against the observed water levels. Simulation result demonstrates that fluctuations of hydraulic heads are dependent on seasonal variations of recharge from precipitation and riverbed leakage. In addition, the river-aquifer relationships proved to be very responsive to water table fluctuations, which indicate the losing or gaining characteristics of the river reaches. This form of dynamic interactions in an integrated river-aquifer system is important in the field contaminant hydrology, which greatly influence the overall system. The study finally concludes that the developed integrated river-aquifer model opens a window for better understanding of a coupled SW-GW system and thereby finding the potential causes of shallow GW pollution by the contaminated recharge water particularly in the coastal area of southwestern Bangladesh.

The dynamical evolution of the flood response to landscape-climate feedbacks is evaluated in a joint nonlinear statistical-dynamical approach. For that purpose, a spatiotemporal sensitivity analysis is conducted on hydrological data from 1976-2008 over 804 catchments throughout Austria, and a general, data-independent nonlinear dynamical model is built linking floods with climate (via precipitation), landscape (via elevation) and their feedbacks. These involve nonlinear scale interactions, with landform evolution processes taking place at the millennial scale (slow dynamics), and climate adjusting in years to decades (fast dynamics). The results show that floods are more responsive to spatial (regional) than to temporal (decadal) variability. Catchments from dry lowlands and high wetlands exhibit similarity between the spatial and temporal sensitivities (spatiotemporal symmetry) and low landscape-climate codependence, suggesting they are not coevolving significantly. However, intermediate regions show differences between those sensitivities (symmetry breaks) and higher landscapeclimate codependence, suggesting undergoing coevolution. The break of symmetry is an emergent behaviour from nonlinear feedbacks within the system. A new coevolution index is introduced relating spatiotemporal symmetry with relative characteristic celerities, which need to be taken into account in hydrological space-time trading. Coevolution is expressed here by the interplay between slow and fast dynamics, represented respectively by spatial and temporal characteristics. The dynamical model captures emerging features of the flood dynamics and nonlinear landscape-climate feedbacks, supporting the nonlinear statistical assessment of spatiotemporally asymmetric flood change. Moreover, it enables the dynamical estimation of flood changes in space and time from the given knowledge at different spatiotemporal conditions. This study ultimately brings to light emerging signatures of change in floods arising from nonlinear slow-fast feedbacks in the landscape-climate dynamics, and contributes towards a better understanding of spatiotemporal flood changes and underlying nonlinearly interacting drivers.