The Second Phase of the Global Land–Atmosphere Coupling Experiment: Soil Moisture Contributions to Subseasonal Forecast Skill
Goddard Space Flight Center1, University of Maryland, Baltimore County2, Science Applications International Corporation3, Hokkaido University4, European Centre for Medium-Range Weather Forecasts5, University of Guelph6, Florida State University7, Catalan Institution for Research and Advanced Studies8, National Oceanic and Atmospheric Administration9, University of Gothenburg10, Environment Canada11, Michigan State University12, Princeton University13, ETH Zurich14, Royal Netherlands Meteorological Institute15
01 Oct 2011-Journal of Hydrometeorology (American Meteorological Society)-Vol. 12, Iss: 5, pp 805-822
TL;DR: The second phase of the Global Land-Atmosphere Coupling Experiment (GLACE-2) is a multi-institutional numerical modeling experiment focused on quantifying, for boreal summer, the subseasonal forecast skill for precipitation and air temperature that can be derived from the realistic initialization of land surface states, notably soil moisture as mentioned in this paper.
Abstract: The second phase of the Global Land–Atmosphere Coupling Experiment (GLACE-2) is a multi-institutional numerical modeling experiment focused on quantifying, for boreal summer, the subseasonal (out to two months) forecast skill for precipitation and air temperature that can be derived from the realistic initialization of land surface states, notably soil moisture. An overview of the experiment and model behavior at the global scale is described here, along with a determination and characterization of multimodel “consensus” skill. The models show modest but significant skill in predicting air temperatures, especially where the rain gauge network is dense. Given that precipitation is the chief driver of soil moisture, and thereby assuming that rain gauge density is a reasonable proxy for the adequacy of the observational network contributing to soil moisture initialization, this result indeed highlights the potential contribution of enhanced observations to prediction. Land-derived precipitation forec...
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Vienna University of Technology1, Centre national de la recherche scientifique2, European Centre for Medium-Range Weather Forecasts3, National Research Council4, ETH Zurich5, Finnish Meteorological Institute6, Nanjing University of Information Science and Technology7, Ghent University8, VU University Amsterdam9, University College Cork10, Starlab11
TL;DR: The European Space Agency (ESA) released the first multi-decadal, global satellite-observed soil moisture (SM) dataset as part of its Climate Change Initiative (CCI) program.
756 citations
TL;DR: The ERA-Interim/Land dataset as discussed by the authors provides a global integrated and coherent estimate of soil moisture and snow water equivalent, which can also be used for the initialization of numerical weather prediction and climate models.
Abstract: ERA-Interim/Land is a global land surface reanalysis data set covering the period 1979–2010. It describes the evolution of soil moisture, soil temperature and snowpack. ERA-Interim/Land is the result of a single 32-year simulation with the latest ECMWF (European Centre for Medium-Range Weather Forecasts) land surface model driven by meteorological forcing from the ERA-Interim atmospheric reanalysis and precipitation adjustments based on monthly GPCP v2.1 (Global Precipitation Climatology Project). The horizontal resolution is about 80 km and the time frequency is 3-hourly. ERA-Interim/Land includes a number of parameterization improvements in the land surface scheme with respect to the original ERA-Interim data set, which makes it more suitable for climate studies involving land water resources. The quality of ERA-Interim/Land is assessed by comparing with ground-based and remote sensing observations. In particular, estimates of soil moisture, snow depth, surface albedo, turbulent latent and sensible fluxes, and river discharges are verified against a large number of site measurements. ERA-Interim/Land provides a global integrated and coherent estimate of soil moisture and snow water equivalent, which can also be used for the initialization of numerical weather prediction and climate models.
455 citations
Cites background from "The Second Phase of the Global Land..."
...Multimodel land surface simulations, such as those performed within the Global Soil Wetness Project (Dirmeyer, 2011; Dirmeyer et al., 2002, 2006), combined with seasonal forecasting systems have been crucial in triggering advances in land-related predictability as documented in the Global Land–Atmosphere Coupling Experiments (Koster et al., 2006, 2009, 2011)....
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...…the Global Soil Wetness Project (Dirmeyer, 2011; Dirmeyer et al., 2002, 2006), combined with seasonal forecasting systems have been crucial in triggering advances in land-related predictability as documented in the Global Land–Atmosphere Coupling Experiments (Koster et al., 2006, 2009, 2011)....
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TL;DR: In this paper, the authors found that wide areas of the world display a strong relationship between the number of hot days in the regions' hottest month and preceding precipitation deficits, and that effects of soil moisture-temperature coupling are geographically more widespread than commonly assumed.
Abstract: Global warming increases the occurrence probability of hot extremes, and improving the predictability of such events is thus becoming of critical importance. Hot extremes have been shown to be induced by surface moisture deficits in some regions. In this study, we assess whether such a relationship holds at the global scale. We find that wide areas of the world display a strong relationship between the number of hot days in the regions’ hottest month and preceding precipitation deficits. The occurrence probability of an above-average number of hot days is over 70% after precipitation deficits in most parts of South America as well as the Iberian Peninsula and Eastern Australia, and over 60% in most of North America and Eastern Europe, while it is below 30–40% after wet conditions in these regions. Using quantile regression analyses, we show that the impact of precipitation deficits on the number of hot days is asymmetric, i.e. extreme high numbers of hot days are most strongly influenced. This relationship also applies to the 2011 extreme event in Texas. These findings suggest that effects of soil moisture-temperature coupling are geographically more widespread than commonly assumed.
431 citations
01 Apr 2013
TL;DR: It is found that wide areas of the world display a strong relationship between the number of hot days in the regions’ hottest month and preceding precipitation deficits, and effects of soil moisture-temperature coupling are geographically more widespread than commonly assumed.
Abstract: Global warming increases the occurrence probability of hot extremes, and improving the predictability of such events is thus becoming of critical importance. Hot extremes have been shown to be induced by surface moisture deficits in some regions. In this study, we assess whether such a relationship holds at the global scale. We find that wide areas of the world display a strong relationship between the number of hot days in the regions’ hottest month and preceding precipitation deficits. The occurrence probability of an above-average number of hot days is over 70% after precipitation deficits in most parts of South America as well as the Iberian Peninsula and Eastern Australia, and over 60% in most of North America and Eastern Europe, while it is below 30–40% after wet conditions in these regions. Using quantile regression analyses, we show that the impact of precipitation deficits on the number of hot days is asymmetric, i.e. extreme high numbers of hot days are most strongly influenced. This relationship also applies to the 2011 extreme event in Texas. These findings suggest that effects of soil moisture-temperature coupling are geographically more widespread than commonly assumed.
416 citations
Cites background from "The Second Phase of the Global Land..."
...The more recent GLACE-2 experiment (28) has similar limitations, except that it has been computed over a longer time period (1986–1995)....
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...However, there are also some common features, mostly the strong coupling found in the Great Plains of North America, and the strong potential predictability found in Europe in the second phase of the GLACE experiment (GLACE-2) (28)....
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TL;DR: In this paper, the authors present a review of the current representation of hydrologic processes in Earth System Models and identify the key opportunities for improvement, and suggest that the development of ESMs has not kept pace with modeling advances in hydrology.
Abstract: Many of the scientific and societal challenges in understanding and preparing for global environmental change rest upon our ability to understand and predict the water cycle change at large river basin, continent, and global scales. However, current large-scale models, such as the land components of Earth System Models (ESMs), do not yet represent the terrestrial water cycle in a fully integrated manner or resolve the finer-scale processes that can dominate large-scale water budgets. This paper reviews the current representation of hydrologic processes in ESMs and identifies the key opportunities for improvement. This review suggests that (1) the development of ESMs has not kept pace with modeling advances in hydrology, both through neglecting key processes (e.g., groundwater) and neglecting key aspects of spatial variability and hydrologic connectivity; and (2) many modeling advances in hydrology can readily be incorporated into ESMs and substantially improve predictions of the water cycle. Accelerating modeling advances in ESMs requires comprehensive hydrologic benchmarking activities, in order to systematically evaluate competing modeling alternatives, understand model weaknesses, and prioritize model development needs. This demands stronger collaboration, both through greater engagement of hydrologists in ESM development and through more detailed evaluation of ESM processes in research watersheds. Advances in themore » representation of hydrologic process in ESMs can substantially improve energy, carbon and nutrient cycle prediction capabilities through the fundamental role the water cycle plays in regulating these cycles.« less
371 citations
Cites background from "The Second Phase of the Global Land..."
...…latent heat flux (evaporative fraction), which consequently affects surface temperature, boundary layer properties, cloud formation, and in some cases the initiation of convection leading to precipitation [Douville, 2004; Dirmeyer et al., 2006; Koster et al., 2006, 2011; Huang and Margulis, 2013]....
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References
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TL;DR: The Modern-Era Retrospective Analysis for Research and Applications (MERRA) was undertaken by NASA's Global Modeling and Assimilation Office with two primary objectives: to place observations from NASA's Earth Observing System satellites into a climate context and to improve upon the hydrologic cycle represented in earlier generations of reanalyses as mentioned in this paper.
Abstract: The Modern-Era Retrospective Analysis for Research and Applications (MERRA) was undertaken by NASA’s Global Modeling and Assimilation Office with two primary objectives: to place observations from NASA’s Earth Observing System satellites into a climate context and to improve upon the hydrologic cycle represented in earlier generations of reanalyses. Focusing on the satellite era, from 1979 to the present, MERRA has achieved its goals with significant improvements in precipitation and water vapor climatology. Here, a brief overview of the system and some aspects of its performance, including quality assessment diagnostics from innovation and residual statistics, is given.By comparing MERRA with other updated reanalyses [the interim version of the next ECMWF Re-Analysis (ERA-Interim) and the Climate Forecast System Reanalysis (CFSR)], advances made in this new generation of reanalyses, as well as remaining deficiencies, are identified. Although there is little difference between the new reanalyses i...
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TL;DR: The new NOAA operational global sea surface temperature (SST) analysis is described in this paper, which uses 7 days of in situ (ship and buoy) and satellite SST.
Abstract: The new NOAA operational global sea surface temperature (SST) analysis is described. The analyses use 7 days of in situ (ship and buoy) and satellite SST. These analyses are produced weekly and daily using optimum interpolation (OI) on a 1° grid. The OI technique requires the specification of data and analysis error statistics. These statistics are derived and show that the SST rms data errors from ships are almost twice as large as the data errors from buoys or satellites. In addition, the average e-folding spatial error scales have been found to be 850 km in the zonal direction and 615 km in the meridional direction. The analysis also includes a preliminary step that corrects any satellite biases relative to the in situ data using Poisson's equation. The importance of this correction is demonstrated using recent data following the 1991 eruptions of Mt. Pinatubo. The OI analysis has been computed using the in situ and bias-corrected satellite data for the period 1985 to present.
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Goddard Space Flight Center1, National Center for Atmospheric Research2, Meteorological Service of Canada3, Hadley Centre for Climate Prediction and Research4, Geophysical Fluid Dynamics Laboratory5, Commonwealth Scientific and Industrial Research Organisation6, University of Reading7, Science Applications International Corporation8, Princeton University9, Bureau of Meteorology10, University of Tokyo11, Macquarie University12, University of California, Los Angeles13
TL;DR: A multimodel estimation of the regions on Earth where precipitation is affected by soil moisture anomalies during Northern Hemisphere summer indicates potential benefits of this estimation may include improved seasonal rainfall forecasts.
Abstract: Previous estimates of land-atmosphere interaction (the impact of soil moisture on precipitation) have been limited by a lack of observational data and by the model dependence of computational estimates. To counter the second limitation, a dozen climate-modeling groups have recently performed the same highly controlled numerical experiment as part of a coordinated comparison project. This allows a multimodel estimation of the regions on Earth where precipitation is affected by soil moisture anomalies during Northern Hemisphere summer. Potential benefits of this estimation may include improved seasonal rainfall forecasts.
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TL;DR: In this article, the authors present the impact tests that preceded the most recent operational upgrades to the land surface model used in the National Centers for Environmental Prediction (NCEP) mesoscale Eta model, whose operational domain includes North America.
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2,520 citations