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VERY HIGH RESOLUTION INTERPOLATED CLIMATE SURFACES FOR GLOBAL LAND AREAS
, 2005
"... We developed interpolated climate surfaces for global land areas (excluding Antarctica) at a spatial resolution of 30 arc s (often referred to as 1-km spatial resolution). The climate elements considered were monthly precipitation and mean, minimum, and maximum temperature. Input data were gathered ..."
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Cited by 553 (8 self)
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We developed interpolated climate surfaces for global land areas (excluding Antarctica) at a spatial resolution of 30 arc s (often referred to as 1-km spatial resolution). The climate elements considered were monthly precipitation and mean, minimum, and maximum temperature. Input data were gathered from a variety of sources and, where possible, were restricted to records from the 1950–2000 period. We used the thin-plate smoothing spline algorithm implemented in the ANUSPLIN package for interpolation, using latitude, longitude, and elevation as independent variables. We quantified uncertainty arising from the input data and the interpolation by mapping weather station density, elevation bias in the weather stations, and elevation variation within grid cells and through data partitioning and cross validation. Elevation bias tended to be negative (stations lower than expected) at high latitudes but positive in the tropics. Uncertainty is highest in mountainous and in poorly sampled areas. Data partitioning showed high uncertainty of the surfaces on isolated islands, e.g. in the Pacific. Aggregating the elevation and climate data to 10 arc min resolution showed an enormous variation within grid cells, illustrating the value of high-resolution surfaces. A comparison with an existing data set at 10 arc min resolution showed overall agreement, but with significant variation in some regions. A comparison with two high-resolution data sets for the United States also identified areas with large local differences, particularly in mountainous areas. Compared to previous global climatologies, ours has the following advantages: the data are at a
Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late Nineteenth Century
- J. GEOPHYSICAL RESEARCH
, 2003
"... ... data set, HadISST1, and the nighttime marine air temperature (NMAT) data set, HadMAT1. HadISST1 replaces the global sea ice and sea surface temperature (GISST) data sets and is a unique combination of monthly globally complete fields of SST and sea ice concentration on a 1 ° latitude-longitude g ..."
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Cited by 539 (4 self)
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... data set, HadISST1, and the nighttime marine air temperature (NMAT) data set, HadMAT1. HadISST1 replaces the global sea ice and sea surface temperature (GISST) data sets and is a unique combination of monthly globally complete fields of SST and sea ice concentration on a 1 ° latitude-longitude grid from 1871. The companion HadMAT1 runs monthly from 1856 on a 5 ° latitude-longitude grid and incorporates new corrections for the effect on NMAT of increasing deck (and hence measurement) heights. HadISST1 and HadMAT1 temperatures are reconstructed using a two-stage reducedspace optimal interpolation procedure, followed by superposition of quality-improved gridded observations onto the reconstructions to restore local detail. The sea ice fields are made more homogeneous by compensating satellite microwave-based sea ice concentrations for the impact of surface melt effects on retrievals in the Arctic and for algorithm deficiencies in the Antarctic and by making the historical in situ concentrations consistent with the satellite data. SSTs near sea ice are estimated using statistical relationships between SST and sea ice concentration. HadISST1 compares well with other published analyses, capturing trends in global, hemispheric, and regional SST well,
Surface air temperature and its changes over the past 150 years
- Rev. Geophys
, 1999
"... Abstract. We review the surface air temperature record of the past 150 years, considering the homogene-ity of the basic data and the standard errors of estima-tion of the average hemispheric and global estimates. We present global fields of surface temperature change over the two 20-year periods of ..."
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Cited by 210 (8 self)
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Abstract. We review the surface air temperature record of the past 150 years, considering the homogene-ity of the basic data and the standard errors of estima-tion of the average hemispheric and global estimates. We present global fields of surface temperature change over the two 20-year periods of greatest warming this century, 1925-1944 and 1978-1997. Over these periods, global temperatures rose by 0.37 ø and 0.32øC, respec-tively. The twentieth-century warming has been accom-panied by a decrease in those areas of the world affected by exceptionally cool temperatures and to a lesser extent by increases in areas affected by exceptionally warm temperatures. In recent decades there have been much greater increases in night minimum temperatures than in day maximum temperatures, so that over 1950-1993 the diurnal temperature range has decreased by 0.08øC per decade. We discuss the recent divergence of surface and satellite temperature measurements of the lower troposphere and consider the last 150 years in the con-text of the last millennium. We then provide a globally complete absolute surface air temperature climatology on a 1 ø x 1 ø grid. This is primarily based on data for 1961-1990. Extensive interpolation had to be under-taken over both polar regions and in a few other regions where basic data are scarce, but we believe the climatol-ogy is the most consistent and reliable of absolute sur-face air temperature conditions over the world. The climatology indicates that the annual average surface temperature of the world is 14.0øC (14.6øC in the North-ern Hemisphere (NH) and 13.4øC for the Southern Hemisphere). The annual cycle of global mean temper-atures follows that of the land-dominated NH, with a maximum in July of 15.9øC and a minimum in January of 12.2øC. 1.
Evidence for intensification of the global water cycle: Review and synthesis,
- J. Hydrol.,
, 2006
"... Abstract One of the more important questions in hydrology is: if the climate warms in the future, will there be an intensification of the water cycle and, if so, the nature of that intensification? There is considerable interest in this question because an intensification of the water cycle may lea ..."
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Cited by 112 (1 self)
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Abstract One of the more important questions in hydrology is: if the climate warms in the future, will there be an intensification of the water cycle and, if so, the nature of that intensification? There is considerable interest in this question because an intensification of the water cycle may lead to changes in water-resource availability, an increase in the frequency and intensity of tropical storms, floods, and droughts, and an amplification of warming through the water vapor feedback. Empirical evidence for ongoing intensification of the water cycle would provide additional support for the theoretical framework that links intensification with warming. This paper briefly reviews the current state of science regarding historical trends in hydrologic variables, including precipitation, runoff, tropospheric water vapor, soil moisture, glacier mass balance, evaporation, evapotranspiration, and growing season length. Data are often incomplete in spatial and temporal domains and regional analyses are variable and sometimes contradictory; however, the weight of evidence indicates an ongoing intensification of the water cycle. In contrast to these trends, the empirical evidence to date does not consistently support an increase in the frequency or intensity of tropical storms and floods. q
The worldwide leaf economics spectrum.
- Nature,
, 2004
"... Bringing together leaf trait data spanning 2,548 species and 175 sites we describe, for the first time at global scale, a universal spectrum of leaf economics consisting of key chemical, structural and physiological properties. The spectrum runs from quick to slow return on investments of nutrients ..."
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Cited by 106 (20 self)
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Bringing together leaf trait data spanning 2,548 species and 175 sites we describe, for the first time at global scale, a universal spectrum of leaf economics consisting of key chemical, structural and physiological properties. The spectrum runs from quick to slow return on investments of nutrients and dry mass in leaves, and operates largely independently of growth form, plant functional type or biome. Categories along the spectrum would, in general, describe leaf economic variation at the global scale better than plant functional types, because functional types overlap substantially in their leaf traits. Overall, modulation of leaf traits and trait relationships by climate is surprisingly modest, although some striking and significant patterns can be seen. Reliable quantification of the leaf economics spectrum and its interaction with climate will prove valuable for modelling nutrient fluxes and vegetation boundaries under changing land-use and climate. Green leaves are fundamental for the functioning of terrestrial ecosystems. Their pigments are the predominant signal seen from space. Nitrogen uptake and carbon assimilation by plants and the decomposability of leaves drive biogeochemical cycles. Animals, fungi and other heterotrophs in ecosystems are fuelled by photosynthate, and their habitats are structured by the stems on which leaves are deployed. Plants invest photosynthate and mineral nutrients in the construction of leaves, which in turn return a revenue stream of photosynthate over their lifetimes. The photosynthate is used to acquire mineral nutrients, to support metabolism and to re-invest in leaves, their supporting stems and other plant parts. There are more than 250,000 vascular plant species, all engaging in the same processes of investment and reinvestment of carbon and mineral nutrients, and all making enough surplus to ensure continuity to future generations. These processes of investment and re-investment are inherently economic in nature Data set and parameters We formed a global plant trait network (Glopnet) to quantify leaf economics across the world's plant species. The Glopnet data set spans 2,548 species from 219 families at 175 sites (approximately 1% of the extant vascular plant species). The coverage of traits, species and sites is at least tenfold greater than previous data compilations
A maximum entropy approach to species distribution modeling
- In Proceedings of the Twenty-First International Conference on Machine Learning
, 2004
"... We study the problem of modeling species geographic distributions, a critical problem in conservation biology. We propose the use of maximum-entropy techniques for this problem, specifically, sequential-update algorithms that can handle a very large number of features. We describe experiments compar ..."
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Cited by 104 (7 self)
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We study the problem of modeling species geographic distributions, a critical problem in conservation biology. We propose the use of maximum-entropy techniques for this problem, specifically, sequential-update algorithms that can handle a very large number of features. We describe experiments comparing maxent with a standard distribution-modeling tool, called GARP, on a dataset containing observation data for North American breeding birds. We also study how well maxent performs as a function of the number of training examples and training time, analyze the use of regularization to avoid overfitting when the number of examples is small, and explore the interpretability of models constructed using maxent. 1.
B (2003) A global hydrological model for deriving water availability indicators: model tuning and validation
- Journal of Hydrology
"... Freshwater availability has been recognized as a global issue, and its consistent quantification not only in individual river basins but also at the global scale is required to support the sustainable use of water. The WaterGAP Global Hydrology Model WGHM, which is a submodel of the global water use ..."
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Cited by 93 (7 self)
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Freshwater availability has been recognized as a global issue, and its consistent quantification not only in individual river basins but also at the global scale is required to support the sustainable use of water. The WaterGAP Global Hydrology Model WGHM, which is a submodel of the global water use and availability model WaterGAP 2, computes surface runoff, groundwater recharge and river discharge at a spatial resolution of 0.58. WGHM is based on the best global data sets currently available, and simulates the reduction of river discharge by human water consumption. In order to obtain a reliable estimate of water availability, it is tuned against observed discharge at 724 gauging stations, which represent 50 % of the global land area and 70 % of the actively discharging area. For 50 % of these stations, the tuning of one model parameter was sufficient to achieve that simulated and observed long-term average discharges agree within 1%. For the rest, however, additional corrections had to be applied to the simulated runoff and discharge values. WGHM not only computes the long-term average water resources of a country or a drainage basin but also water availability indicators that take into account the interannual and seasonal variability of runoff and discharge. The reliability of the modeling results is assessed by comparing observed and simulated discharges at the tuning stations and at selected other stations. The comparison shows that WGHM is able to calculate reliable and meaningful indicators of water availability at a high spatial resolution. In particular, the 90 % reliable monthly discharge is simulated well. Therefore, WGHM is suited for application in global assessments related to water security, food security and freshwater ecosystems.
A global database of land surface parameters at 1-km resolution in meteorological and climate models
- J. Clim
"... Ecoclimap, a new complete surface parameter global dataset at a 1-km resolution, is presented. It is intended to be used to initialize the soil–vegetation–atmosphere transfer schemes (SVATs) in meteorological and climate models (at all horizontal scales). The database supports the ‘‘tile’ ’ approach ..."
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Cited by 87 (7 self)
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Ecoclimap, a new complete surface parameter global dataset at a 1-km resolution, is presented. It is intended to be used to initialize the soil–vegetation–atmosphere transfer schemes (SVATs) in meteorological and climate models (at all horizontal scales). The database supports the ‘‘tile’ ’ approach, which is utilized by an increasing number of SVATs. Two hundred and fifteen ecosystems representing areas of homogeneous vegetation are derived by combining existing land cover maps and climate maps, in addition to using Advanced Very High Resolution Radiometer (AVHRR) satellite data. Then, all surface parameters are derived for each of these ecosystems using lookup tables with the annual cycle of the leaf area index (LAI) being constrained by the AVHRR information. The resulting LAI is validated against a large amount of in situ ground observations, and it is also compared to LAI derived from the International Satellite Land Surface Climatology Project (ISLSCP-2) database and the Polarization and Directionality of the Earth’s Reflectance (POLDER) satellite. The comparison shows that this new LAI both reproduces values coherent at large scales with other datasets, and includes the high spatial variations owing to the input land cover data at a 1-km resolution. In terms of climate modeling studies, the use of this new database is shown to improve the surface climatology of the ARPEGE climate model. 1.
Performance guarantees for regularized maximum entropy density estimation
- Proceedings of the 17th Annual Conference on Computational Learning Theory
, 2004
"... Abstract. We consider the problem of estimating an unknown probability distribution from samples using the principle of maximum entropy (maxent). To alleviate overfitting with a very large number of features, we propose applying the maxent principle with relaxed constraints on the expectations of th ..."
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Cited by 81 (8 self)
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Abstract. We consider the problem of estimating an unknown probability distribution from samples using the principle of maximum entropy (maxent). To alleviate overfitting with a very large number of features, we propose applying the maxent principle with relaxed constraints on the expectations of the features. By convex duality, this turns out to be equivalent to finding the Gibbs distribution minimizing a regularized version of the empirical log loss. We prove nonasymptotic bounds showing that, with respect to the true underlying distribution, this relaxed version of maxent produces density estimates that are almost as good as the best possible. These bounds are in terms of the deviation of the feature empirical averages relative to their true expectations, a number that can be bounded using standard uniform-convergence techniques. In particular, this leads to bounds that drop quickly with the number of samples, and that depend very moderately on the number or complexity of the features. We also derive and prove convergence for both sequential-update and parallel-update algorithms. Finally, we briefly describe experiments on data relevant to the modeling of species geographical distributions. 1
Explicit representation of subgrid heterogeneity in a GCM land surface scheme
- J. Hydrometeor
, 2003
"... A land surface scheme that may be run with or without a tiled representation of subgrid heterogeneity and includes an implicit atmospheric coupling scheme is described. Simulated average surface air temperatures and diurnal temperature ranges in a GCM using this surface model are compared with clima ..."
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Cited by 70 (7 self)
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A land surface scheme that may be run with or without a tiled representation of subgrid heterogeneity and includes an implicit atmospheric coupling scheme is described. Simulated average surface air temperatures and diurnal temperature ranges in a GCM using this surface model are compared with climatology. Surface tiling is not found to give a clear improvement in the simulated climate but offers more flexibility in the representation of heterogeneous land surface processes. Using the same meteorological forcing in offline simulations using versions of the surface model with and without tiling, the tiled model gives slightly lower winter temperatures at high latitudes and higher summer temperatures at midlatitudes. When the surface model is coupled to a GCM, reduced evaporation in the tiled version leads to changes in cloud cover and radiation at the surface that enhance these differences. 1.