Parameterization of subsurface heating for soil and concrete using net radiation data

The variability of surface sensible heat flux depends strongly on the heating rate of the material beneath the surface. This variability is expected to be large in urban areas where the surfaces are layered with a variety of man-made materials. Parameterization of the ground heat storage as a function of surface materials is presented based on analyses of data obtained during the U.S. Environmental Protection Agency's Regional Air Pollution Study conducted in St. Louis, Missouri. Ground heat flux data are derived from observations of surface and subsurface temperatures for a soil layer and for concrete slabs resting on soil. The data show that the presence of the concrete slabs increases the ground storage term relative to that for soil alone. The ground storage and sensible heat flux terms for a blackened concrete slab are larger than for an unpainted concrete slab. For the concrete surfaces, the ratio of ground storage to net radiation is >1 at night and <1 during the day. This ratio is discontinuous at sunrise and sunset transition periods. For soil, the ratio shows similar temporal behavior except that on average, there is a smoother transition at sunrise. Simple mathematical expressions giving the ratio of ground heat storage to net radiation as a function of time are presented.Now with Enviroplan, Incorporated, West Orange, NJ 07052, U.S.A.On assignment from the National Oceanic and Atmospheric Administration, U.S. Department of Commerce.     

European climate of the past 500 years: new challenges for historical climatology

Temperature reconstructions from Europe for the past 500 years based on documentary and instrumental data are analysed. First, the basic documentary data sources, including information about climate and weather-related extremes, are described. Then, the standard palaeoclimatological reconstruction method adopted here is discussed with a particular application to temperature reconstructions from documentary-based proxy data. The focus is on two new reconstructions; January–April mean temperatures for Stockholm (1502–2008), based on a combination of data for the sailing season in the Stockholm harbour and instrumental temperature measurements, and monthly Central European temperature (CEuT) series (1500–2007) based on documentary-derived temperature indices of the Czech Republic, Germany and Switzerland combined with instrumental records from the same countries. The two series, both of which are individually discussed in greater detail in subsequent papers in this special edition, are here compared and analysed using running correlations and wavelet analysis. While the Stockholm series shows a pronounced low-frequency component, the CEuT series indicates much weaker low-frequency variations. Both series are analysed with respect to three different long-period reconstructions of the North Atlantic Oscillation (NAO) and are compared with other European temperature reconstructions based on tree-rings, wine-harvest data and various climate multiproxies. Correlation coefficients between individual proxy-based series show weaker correlations compared to the instrumental data. There are also indications of temporally varying temperature cross-correlations between different areas of Europe. The two temperature reconstructions have also been compared to geographically corresponding temperature output from simulations with global and regional climate models for the past few centuries. The findings are twofold: on the one hand, the analysis reinforces the hypothesis that the index-data based CEuT reconstruction may not appropriately reflect the centennial scale variations. On the other hand, it is possible that climate models may underestimate regional decadal variability. By way of a conclusion, the results are discussed from a broader point of view and attention is drawn to some new challenges for future investigations in the historical climatology in Europe.     

Modeling Images and Spectra of a Solar Flare Observed by RHESSI on 20 February 2002

We have analyzed a C7.5 limb flare observed by RHESSI on 20 February 2002. The RHESSI images appear to show two footpoints and a loop-top source. Our goal was to determine if the data are consistent with a simple steady-state model in which high-energy electrons are continuously injected at the top of a semicircular flare loop. A comparison of the RHESSI images with simulated images from the model has made it possible for us to identify spurious sources and fluxes in the RHESSI images. We find that the RHESSI results are in many aspects consistent with the model if a thermal source is included between the loop footpoints, but there is a problem with the spectral index of the loop-top source. The thermal source between the footpoints is likely to be a low-lying loop interacting with the northern footpoint of a higher loop containing the loop-top source.     

Fast ensemble smoothing

Smoothing is essential to many oceanographic, meteorological, and hydrological applications. There are two predominant classes of smoothing problems. The first is fixed-interval smoothing, where the objective is to estimate model states within a time interval using all available observations in the interval. The second is fixed-lag smoothing, where the objective is to sequentially estimate model states over a fixed or indefinitely growing interval by restricting the influence of observations within a fixed window of time ahead of the evolving estimation time. In this paper, we use an ensemble-based approach to fixed-interval and fixed-lag smoothing, and synthesize two algorithms. The first algorithm is a fixed-interval smoother whose computation time is linear in the interval. The second algorithm is a fixed-lag smoother whose computation time is independent of the lag length. The complexity of these algorithms is presented, shown to improve upon existing implementations and verified with identical-twin experiments conducted with the Lorenz-95 system. Results suggest that ensemble methods yield efficient fixed-interval and fixed-lag smoothing solutions in the sense that the additional increment for smoothing is a small fraction of either filtering or model propagation costs in a practical ensemble application. We also show that fixed-interval smoothing can perform as fast as fixed-lag smoothing, and it may not be necessary to use a fixed-lag approximation for computational savings alone.     

Suitability of CLIGEN precipitation estimates based on an updated database and their impacts on urban runoff: a case study of the Great Lakes Region,USA

ABSTRACT

Weather generators rely on historical meteorological records to simulate time series of synthetic weather sequences, the quality of which has direct influence on model applications. The climate generator CLIGEN’s database has recently been updated to comprise consistent historical records from 1974 to 2013 (updated CLIGEN database, UCD) compared to the current database in which records are of different lengths. In this study, CLIGEN’s performance in estimating precipitation using UCD (eight stations) and the subsequent impact on urban runoff simulations (371 stations) were evaluated in the Great Lakes Region, USA. Generally, UCD-based precipitation could replicate observed daily precipitation up to the 99.5th percentile, but maximum precipitation was underestimated. Results from the Long-Term Hydrologic Impact Assessment model using UCD-based precipitation showed about 0.57 billion cubic meters more (14.9%) average annual runoff being simulated compared with simulations based on the current CLIGEN database. Overall, CLIGEN with the updated database was found suitable for providing precipitation estimates and for use with modeling urban runoff or urbanization effects.     

Spatial discretization of large watersheds and its influence on the estimation of hillslope sediment yield

The combined use of water erosion models and geographic information systems has facilitated soil loss estimation at the watershed scale. Tools such as the Geo‐spatial interface for the Water Erosion Prediction Project (GeoWEPP) model provide a convenient spatially distributed soil loss estimate but require discretization to identify hillslopes and channels. In GeoWEPP, the TOpographic PArameteriZation (TOPAZ) model is used as an automated procedure to extract a watershed boundary, hillslopes and channels from a digital elevation model (DEM). Previous studies in small watersheds have shown that the size of the hillslopes and the channel distribution affect the model estimates, but in large watersheds, the effects on the soil loss estimates have yet to be tested. Therefore, the objective of this study was to evaluate the effect of discretization on the hillslope sediment yield estimates using GeoWEPP in two large watersheds (>10 km²). The watersheds were selected and discretized varying the TOPAZ parameters [critical source area (CSA) and minimum source channel length (MSCL)] in a 30‐m resolution digital elevation model. The drainage networks built with TOPAZ were compared with each other using the drainage density index. The results showed that the discretization affected hillslope sediment yield estimates and their spatial distribution more than the total runoff. The drainage density index and the hillslope sediment yield were proportional but inversely related; thus, soil loss estimates were highly affected by the spatial discretization. As a result of this analysis, a method to choose the CSA and MSCL values that generates the greatest fraction of hillslopes having profile lengths less than 200 m was developed. This slope length condition is particularly crucial when using the WEPP and GeoWEPP models, in order for them to produce realistic estimates of sheet and rill erosion. Finally, and as a result of this analysis, a more reliable method was developed for selecting the TOPAZ channel network parameters (CSA and MSCL). Copyright © 2015 John Wiley & Sons, Ltd.     

Changes in landuse/landcover patterns and human population growth in the Lake Chivero catchment,Zimbabwe

The land use and land cover pattern of a region is a consequence of natural and socio-economic factors and their utilization by man in time and space. In this study, we hypothesized that land use and land cover change patterns in the Lake Chivero catchment, Zimbabwe, were related to its human population dynamics. Using nonparametric correlation coefficients (Spearman’s rho, ρ), we found that bareland, cropland and built-up land had positive relations with human population growth of ρ = 0.7, ρ = 0.9 and ρ = 1, respectively. Grassland/shrubland, water and forest, on the other hand, had a negative relationship with human population growth of ρ = ?0.9, ρ = ?0.7 and ρ = ?0.667, respectively. However, these relationships were only significant (p < 0.05) for cropland, grassland/shrubland and built-up land. Human population dynamics in the Lake Chivero catchment could be one of the major drivers of land use and land cover change in the catchment between 1986 and 2014.     

Utilization of Landsat data to quantify land-use and land-cover changes related to oil and gas activities in West-Central Alberta from 2005 to 2013

Land use and land cover (LULC) change detection associated with oil and gas activities plays an important role in effective sustainable management practices, compliance monitoring, and reclamation assessment. In this study, a mapping methodology is presented for quantifying pre- and post-disturbance LULC types with annual Landsat Best-Available-Pixel multispectral data from 2005 to 2013. Annual LULC and land disturbance maps were produced for one of the major conventional oil and gas production areas in West-Central Alberta with an accuracy of 78% and 87%, respectively. The highest rate of vegetation loss (178 km²/year) was observed in coniferous forest compared to broadleaf forest, mixed forest, and native vegetation. Integration of ancillary oil and gas geospatial data with annual land disturbances indicated that less than 20% of the total land disturbances were attributable to oil and gas activities. In 2013, approximately 44% of oil and gas disturbances from 2005 to 2013 showed evidence of vegetation recovery. In the future, geospatial data related to wildfire, logging activities, insect defoliation, and other natural and anthropogenic factors can be integrated to quantify other causes of land disturbances.     

A note on observation decorrelation,variances of residuals,and redundancy numbers

A technique for processing correlated observations suitable for large, sparse, least-squares adjustments is reviewed. Correlated coordinate differences derived from the Global Positioning System are used as illustrative examples. However, the methods examined are suitable for all types of correlated observations. The computation of variances of residuals, redundancy numbers, and marginally detectable errors is considered for sparse systems.