The Plumbing of Land Surface Models Best, M. J.; Abramowitz, G.; Johnson, H. R. ...
Journal of hydrometeorology,
06/2015, Letnik:
16, Številka:
3
Journal Article
Recenzirano
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The Protocol for the Analysis of Land Surface Models (PALS) Land Surface Model Benchmarking Evaluation Project (PLUMBER) was designed to be a land surface model (LSM) benchmarking intercomparison. ...Unlike the traditional methods of LSM evaluation or comparison, benchmarking uses a fundamentally different approach in that it sets expectations of performance in a range of metrics a priori—before model simulations are performed. This can lead to very different conclusions about LSM performance. For this study, both simple physically basedmodels and empirical relationships were used as the benchmarks. Simulations were performed with 13 LSMs using atmospheric forcing for 20 sites, and then model performance relative to these benchmarks was examined. Results show that even for commonly used statistical metrics, the LSMs’ performance varies considerably when compared to the different benchmarks. All models outperform the simple physically based benchmarks, but for sensible heat flux the LSMs are themselves outperformed by an out-of-sample linear regression against downward shortwave radiation. While moisture information is clearly central to latent heat flux prediction, the LSMs are still outperformed by a three-variable nonlinear regression that uses instantaneous atmospheric humidity and temperature in addition to downward shortwave radiation. These results highlight the limitations of the prevailing paradigm of LSM evaluation that simply compares an LSM to observations and to other LSMs without a mechanism to objectively quantify the expectations of performance. The authors conclude that their results challenge the conceptual view of energy partitioning at the land surface.
Land-atmosphere (L-A) interactions are important for understanding convective processes, climate feedbacks, the development and perpetuation of droughts, heatwaves, pluvials, and other land-centred ...climate anomalies. Local L-A coupling (LoCo) metrics capture relevant L-A processes, highlighting the impact of soil and vegetation states on surface flux partitioning, and the impact of surface fluxes on boundary layer (BL) growth, development, and entrainment of air above the BL. A primary goal of the Climate Process Team on Coupling Land and Atmospheric Subgrid Parameterizations (CLASP) is parameterizing and characterizing the impact of subgrid heterogeneity in global and regional earth system models (ESMs) to improve the connection between land and atmospheric states and processes. A critical step in achieving that aim is the incorporation of L-A metrics, especially LoCo metrics, into climate model diagnostic process streams. However, because land-atmosphere interactions span time scales of minutes (e.g., turbulent fluxes), hours (e.g., BL growth and decay), days (e.g., soil moisture memory), and seasons (e.g., variability of behavioural regimes between soil moisture and latent heat flux), with multiple processes of interest happening in different geographic regions at different times of year, there is not a single metric that captures all the modes, means, and methods of interaction between the land and the atmosphere. And while monthly means of most of the LoCo-relevant variables are routinely saved from ESM simulations, data storage constraints typically preclude routine archival of the hourly data that would enable the calculation of all LoCo metrics.
Here we outline a reasonable data request that would allow for adequate characterization of sub-daily coupling processes between the land and the atmosphere, preserving enough sub-daily output to describe, analyse, and better understand L-A coupling in modern climate models. A secondary request involves embedding calculations within the models to determine mean properties in and above the BL to further improve characterization of model behaviour. Higher-frequency model output will (i) allow for more direct comparison with observational field campaigns on process-relevant time scales, (ii) enable demonstration of inter-model spread in L-A coupling processes, and (iii) aid in targeted identification of sources of deficiencies and opportunities for improvement of the models.
The coupling between soil, vegetation and atmosphere is thought to be crucial
in the development and intensification of weather extremes, especially
meteorological droughts, heat waves and severe ...storms. Therefore, understanding
the evolution of the atmospheric boundary layer (ABL) and the role of
land–atmosphere feedbacks is necessary for earlier warnings,
better climate projection and timely societal adaptation. However, this
understanding is hampered by the difficulties of attributing cause–effect
relationships from complex coupled models and the irregular space–time
distribution of in situ observations of the land–atmosphere system.
As such, there is a need for simple deterministic appraisals that
systematically discriminate land–atmosphere interactions from observed weather
phenomena over large domains and climatological time spans. Here, we present a
new interactive data platform to study the behavior of the ABL and
land–atmosphere interactions based on worldwide weather balloon soundings and an ABL model. This
software tool – referred to as CLASS4GL (http://class4gl.eu, last access: 27 May 2018) – is developed with the objectives of (a) mining appropriate global observational data from ∼15 million weather balloon
soundings since 1981 and combining them with satellite and reanalysis data and (b) constraining and initializing a numerical model of the daytime
evolution of the ABL that serves as a tool to interpret these observations
mechanistically and deterministically.
As a result, it fully automizes extensive global
model experiments to assess the effects of land and
atmospheric conditions on the ABL evolution as observed in different
climate regions around the world.
The suitability of the set of
observations, model formulations and global parameters employed by
CLASS4GL is extensively validated. In most cases, the framework is able to
realistically reproduce the observed daytime response of the mixed-layer height,
potential temperature and specific humidity from the balloon soundings. In this
extensive global validation exercise, a bias of 10.1 m h−1, −0.036 K h−1 and 0.06 g kg−1 h−1 is found for the
morning-to-afternoon evolution of the mixed-layer height, potential temperature
and specific humidity. The virtual tool is in continuous development and
aims to foster a better process understanding of the drivers of the
ABL evolution and their global distribution, particularly during
the onset and amplification of weather extremes. Finally, it can also be
used to scrutinize the representation of land–atmosphere feedbacks and
ABL dynamics in Earth system models, numerical weather prediction
models, atmospheric reanalysis and satellite retrievals, with the
ultimate goal of improving local climate projections, providing earlier
warning of extreme weather and fostering a more effective development of
climate adaptation strategies. The tool can be easily downloaded via
http://class4gl.eu (last access: 27 May 2018) and is open source.
Cyclone Kelvin made landfall in northwest Australia as a category 1 storm on 18 February 2018. After landfall, tropical cyclones typically weaken due to the exhaustion of a moisture supply. Cyclone ...Kelvin continued to intensify with winds gusting to 100 knots and significant flooding well inland. A distinct eye feature also formed well after landfall. An analysis of meteorological satellite, MERRA2reanalysis, and Global Data Assimilation System (GDAS) data was employedin a case study of Cyclone Kelvin. Using a cyclone phase diagram, it is confirmed that a warm core structure was maintained as Cyclone Kelvin continued to move inland, even through a period of brief inland intensification.
Background The Safety Planning, Evaluation and Reporting Team (SPERT) was formed in 2006 by the Pharmaceutical Research and Manufacturers of America.
Purpose SPERT’s goal was to propose a ...pharmaceutical industry standard for safety planning, data collection, evaluation, and reporting, beginning with planning first-in-human studies and continuing through the planning of the post-product-approval period.
Methods SPERT’s recommendations are based on our review of relevant literature and on consensus reached in our discussions.
Results An important recommendation is that sponsors create a Program Safety Analysis Plan early in development. We also give recommendations for the planning of repeated, cumulative meta-analyses of the safety data obtained from the studies conducted within the development program. These include clear definitions of adverse events of special interest and standardization of many aspects of data collection and study design. We describe a 3-tier system for signal detection and analysis of adverse events and highlight proposals for reducing "false positive" safety findings. We recommend that sponsors review the aggregated safety data on a regular and ongoing basis throughout the development program, rather than waiting until the time of submission.
Limitations We recognize that there may be other valid approaches.
Conclusions The proactive approach we advocate has the potential to benefit patients and health care providers by providing more comprehensive safety information at the time of new product marketing and beyond. Clinical Trials 2009; 6: 430—440. http://ctj.sagepub.com
The Plumbing of Land Surface Models Haughton, Ned; Abramowitz, Gab; Pitman, Andy J. ...
Journal of hydrometeorology,
06/2016, Letnik:
17, Številka:
6
Journal Article
Recenzirano
Odprti dostop
The Protocol for the Analysis of Land Surface Models (PALS) Land Surface Model Benchmarking Evaluation Project (PLUMBER) illustrated the value of prescribing a priori performance targets in model ...intercomparisons. It showed that the performance of turbulent energy flux predictions from different land surface models, at a broad range of flux tower sites using common evaluation metrics, was on average worse than relatively simple empirical models. For sensible heat fluxes, all land surface models were outperformed by a linear regression against downward shortwave radiation. For latent heat flux, all land surface models were outperformed by a regression against downward shortwave radiation, surface air temperature, and relative humidity. These results are explored here in greater detail and possible causes are investigated. It is examined whether particular metrics or sites unduly influence the collated results, whether results change according to time-scale aggregation, and whether a lack of energy conservation in flux tower data gives the empirical models an unfair advantage in the intercomparison. It is demonstrated that energy conservation in the observational data is not responsible for these results. It is also shown that the partitioning between sensible and latent heat fluxes in LSMs, rather than the calculation of available energy, is the cause of the original findings. Finally, evidence is presented that suggests that the nature of this partitioning problem is likely shared among all contributing LSMs. While a single candidate explanation for why land surface models perform poorly relative to empirical benchmarks in PLUMBER could not be found, multiple possible explanations are excluded and guidance is provided on where future research should focus.
Near-surface soil moisture is a critical component of land surface energy and water balance studies encompassing a wide range of disciplines. However, the processes of infiltration, runoff, and ...evapotranspiration in the vadose zone of the soil are not easy to quantify or predict because of the difficulty in accurately representing soil texture and hydraulic properties in land surface models. This study approaches the problem of parameterizing soil properties from a unique perspective based on components originally developed for operational estimation of soil moisture for mobility assessments. Estimates of near-surface soil moisture derived from passive (L-band) microwave remote sensing were acquired on six dates during the Monsoon '90 experiment in southeastern Arizona, and used to calibrate hydraulic properties in an offline land surface model and infer information on the soil conditions of the region. Specifically, a robust parameter estimation tool (PEST) was used to calibrate the Noah land surface model and run at very high spatial resolution across the Walnut Gulch Experimental Watershed. Errors in simulated versus observed soil moisture were minimized by adjusting the soil texture, which in turn controls the hydraulic properties through the use of pedotransfer functions. By estimating within a continuous range of widely applicable soil properties such as sand, silt, and clay percentages rather than applying rigid soil texture classes, lookup tables, or large parameter sets as in previous studies, the physical accuracy and consistency of the resulting soils could then be assessed.
In addition, the sensitivity of this calibration method to the number and timing of microwave retrievals is determined in relation to the temporal patterns in precipitation and soil drying. The resultant soil properties were applied to an extended time period demonstrating the improvement in simulated soil moisture over that using default or county-level soil parameters. The methodology is also applied to an independent case at Walnut Gulch using a new soil moisture product from active (C-band) radar imagery with much lower spatial and temporal resolution. Overall, results demonstrate the potential to gain physically meaningful soil information using simple parameter estimation with few but appropriately timed remote sensing retrievals.
Global observations of near-surface air temperature and specific humidity over land are needed for a variety of applications, including to constrain global estimates of evapotranspiration (ET). ...Spaceborne hyperspectral observations, such as those from NASA's Atmospheric Infrared Sounder (AIRS) mission, show promise for meeting this need, yet there are surprisingly few validation studies of AIRS near-surface atmospheric state retrievals. In this study, we use triple collocation to validate AIRS Level 3 retrievals of near-surface atmospheric state over land using twelve years of gridded station observations and two reanalyses. Deseasonalized AIRS retrievals correlate well with deseasonalized ground observations outside the tropics, but correlate less well in the tropics. Lower temporal sensitivity near the surface in the tropics contributes to the lower correlation for near-surface air temperature and is consistent with known physics of the tropical atmosphere, in which temperatures outside the boundary layer (which dominate the AIRS retrieval signal) are poorly correlated with those near the surface. Retrievals in the tropics may also be more susceptible to errors in cloud-clearing algorithms, and to uncertainty in surface emissivity. Since ET is greatest in the tropics, and tropical measurement networks are particularly sparse, this work motivates new approaches for measuring ET in the tropics.
•AIRS retrievals of near-surface air temperature and specific humidity are compared to observations and reanalyses.•Retrievals are reasonably accurate at mid- and high-latitudes, but not in the tropics.•Lower accuracy in the tropics is consistent with known physics of the tropical atmosphere.
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