Spatial aspects of the design and targeting of agricultural development strategies:

Two increasingly shared perspectives within the international development community are that (a) geography matters, and (b) many government interventions would be more successful if they were better targeted. This paper unites these two notions by exploring the opportunities for, and benefits of, bringing an explicitly spatial dimension to the tasks of formulating and evaluating agricultural development strategies. We first review the lingua franca of land fragility and find it lacking in its capacity to describe the dynamic interface between the biophysical and socioeconomic factors that help shape rural development options. Subsequently, we propose a two-phased approach. First, development strategy options are characterized to identify the desirable ranges of conditions that would most favor successful strategy implementation. Second, those conditions exhibiting important spatial dependency – such as agricultural potential, population density, and access to infrastructure and markets – are matched against a similarly characterized, spatially-referenced (GIS) database. This process generates both spatial (map) and tabular representations of strategy-specific development domains. An important benefit of a spatial (GIS) framework is that it provides a powerful means of organizing and integrating a very diverse range of disciplinary and data inputs. At a more conceptual level we propose that it is the characterization of location, not the narrowly-focused characterization of land, that is more properly the focus of attention from a development perspective. The paper includes appropriate examples of spatial analysis using data from East Africa and Burkina Faso, and concludes with an appendix describing and interpreting regional climate and soil data for Sub-Saharan Africa that was directly relevant to our original goal.Spatial analysis (Statistics), Agricultural development., Burkina Faso., Africa, Sub-Saharan.,

Revisiting the parameterization of potential evaporation as a driver of long-term water balance trends

We examine the effects of two different parameterizations of potential evaporation on long-term trends in soil moisture, evaporative flux and runoff simulated by the water balance model underlying the Palmer Drought Severity Index. The first, traditiona

Validation of GPS-derived long-term trend in the atmospheric water vapor using homogenized radiosonde data

Atmospheric water vapor is important for the Earth’s energy balance due to its ability of absorbing and trapping long wave radiation emitted from the Earth’s surface. Therefore, measurements of the atmospheric water vapor content are of very interest for meteorology and climatology. Based on the path delay, which radio signals undergo when propagating through the neutral atmosphere, the Global Positioning System (GPS) measurements can be used to derive the atmospheric integrated water vapor (IWV). With a relatively high temporal resolution, continuously improved spatial density, and less expensive receivers, ground-based GPS measurement has been identified as a useful technique to monitor long-term variations in the IWV. This study will focus on investigating uncertainties of long-term IWV trend obtained from the NCAR global, 2-hourly ground-based GPS IWV dataset. The IWV trends were estimated for approximate 70 GPS sites covering the time period from 1997 to 2011. The GPS-IWV trends will be validated against that from the co-located and homogenized NCAR radiosonde data. The estimated GPS IWV trend consists of two types of uncertainties. The first type is larger in magnitude and is caused by short-term IWV variations (natural variability of the weather), which is not described by the model used for the trend estimation. This type will be investigated by using a statistical model and comparing the GPS IWV trends to the “true” IWV trends estimated from the radiosonde data during 1973-2011. The second type has smaller amplitude and is mainly caused by systematic errors in the GPS data, such as elevation-angle-dependent errors and changes of the GPS antenna and mask. A comparison with the homogenized radiosonde data will help us understand and quantify this type of uncertainty

Changes in Continental Freshwater Discharge from 1948 to 2004

A new dataset of historical monthly streamflow at the farthest downstream stations for the world’s 925 largest ocean-reaching rivers has been created for community use. Available new gauge records are added to a network of gauges that covers ∼80 × 106 km2 or ∼80% of global ocean-draining land areas and accounts for about 73% of global total runoff. For most of the large rivers, the record for 1948–2004 is fairly complete. Data gaps in the records are filled through linear regression using streamflow simulated by a land surface model [Community Land Model, version 3 (CLM3)] forced with observed precipitation and other atmospheric forcings that are significantly (and often strongly) correlated with the observed streamflow for most rivers. Compared with previous studies, the new dataset has improved homogeneity and enables more reliable assessments of decadal and long-term changes in continental freshwater discharge into the oceans. The model-simulated runoff ratio over drainage areas with and without gauge records is used to estimate the contribution from the areas not monitored by the gauges in deriving the total discharge into the global oceans. Results reveal large variations in yearly streamflow for most of the world’s large rivers and for continental discharge, but only about one-third of the top 200 rivers (including the Congo, Mississippi, Yenisey, Paraná, Ganges, Columbia, Uruguay, and Niger) show statistically significant trends during 1948–2004, with the rivers having downward trends (45) outnumbering those with upward trends (19). The interannual variations are correlated with the El Niño–Southern Oscillation (ENSO) events for discharge into the Atlantic, Pacific, Indian, and global ocean as a whole. For ocean basins other than the Arctic, and for the global ocean as a whole, the discharge data show small or downward trends, which are statistically significant for the Pacific (−9.4 km3 yr−1). Precipitation is a major driver for the discharge trends and large interannual-to-decadal variations. Comparisons with the CLM3 simulation suggest that direct human influence on annual streamflow is likely small compared with climatic forcing during 1948–2004 for most of the world’s major rivers. For the Arctic drainage areas, upward trends in streamflow are not accompanied by increasing precipitation, especially over Siberia, based on available data, although recent surface warming and associated downward trends in snow cover and soil ice content over the northern high latitudes contribute to increased runoff in these regions. The results are qualitatively consistent with climate model projections but contradict an earlier report of increasing continental runoff during the recent decades based on limited records

HadISD: a quality-controlled global synoptic report database for selected variables at long-term stations from 1973--2011

[Abridged] This paper describes the creation of HadISD: an automatically quality-controlled synoptic resolution dataset of temperature, dewpoint temperature, sea-level pressure, wind speed, wind direction and cloud cover from global weather stations for 1973--2011. The full dataset consists of over 6000 stations, with 3427 long-term stations deemed to have sufficient sampling and quality for climate applications requiring sub-daily resolution. As with other surface datasets, coverage is heavily skewed towards Northern Hemisphere mid-latitudes. The dataset is constructed from a large pre-existing ASCII flatfile data bank that represents over a decade of substantial effort at data retrieval, reformatting and provision. These raw data have had varying levels of quality control applied to them by individual data providers. The work proceeded in several steps: merging stations with multiple reporting identifiers; reformatting to netCDF; quality control; and then filtering to form a final dataset. Particular attention has been paid to maintaining true extreme values where possible within an automated, objective process. Detailed validation has been performed on a subset of global stations and also on UK data using known extreme events to help finalise the QC tests. Further validation was performed on a selection of extreme events world-wide (Hurricane Katrina in 2005, the cold snap in Alaska in 1989 and heat waves in SE Australia in 2009). Although the filtering has removed the poorest station records, no attempt has been made to homogenise the data thus far. Hence non-climatic, time-varying errors may still exist in many of the individual station records and care is needed in inferring long-term trends from these data. A version-control system has been constructed for this dataset to allow for the clear documentation of any updates and corrections in the future.Comment: Published in Climate of the Past, www.clim-past.net/8/1649/2012/. 31 pages, 23 figures, 9 pages. For data see http://www.metoffice.gov.uk/hadobs/hadis

Challenges in quantifying changes in the global water cycle

Human influences have likely already impacted the large-scale water cycle but natural variability and observational uncertainty are substantial. It is essential to maintain and improve observational capabilities to better characterize changes. Understanding observed changes to the global water cycle is key to predicting future climate changes and their impacts. While many datasets document crucial variables such as precipitation, ocean salinity, runoff, and humidity, most are uncertain for determining long-term changes. In situ networks provide long time-series over land but are sparse in many regions, particularly the tropics. Satellite and reanalysis datasets provide global coverage, but their long-term stability is lacking. However, comparisons of changes among related variables can give insights into the robustness of observed changes. For example, ocean salinity, interpreted with an understanding of ocean processes, can help cross-validate precipitation. Observational evidence for human influences on the water cycle is emerging, but uncertainties resulting from internal variability and observational errors are too large to determine whether the observed and simulated changes are consistent. Improvements to the in situ and satellite observing networks that monitor the changing water cycle are required, yet continued data coverage is threatened by funding reductions. Uncertainty both in the role of anthropogenic aerosols, and due to large climate variability presently limits confidence in attribution of observed changes

Two-Dimensional Lattice Boltzmann Model For Compressible Flows With High Mach Number

In this paper we present an improved lattice Boltzmann model for compressible Navier-Stokes system with high Mach number. The model is composed of three components: (i) the discrete-velocity-model by Watari and Tsutahara [Phys Rev E \textbf{67},036306(2003)], (ii) a modified Lax-Wendroff finite difference scheme where reasonable dissipation and dispersion are naturally included, (iii) artificial viscosity. The improved model is convenient to compromise the high accuracy and stability. The included dispersion term can effectively reduce the numerical oscillation at discontinuity. The added artificial viscosity helps the scheme to satisfy the von Neumann stability condition. Shock tubes and shock reflections are used to validate the new scheme. In our numerical tests the Mach numbers are successfully increased up to 20 or higher. The flexibility of the new model makes it suitable for tracking shock waves with high accuracy and for investigating nonlinear nonequilibrium complex systems