Multiyear predictability of the North Atlantic subpolar gyre
Wouters, B. ; Hazeleger, W. ; Drijfhout, S. ; Oldenborgh, G.J. van; Guemas, V. - \ 2013
Geophysical Research Letters 40 (2013)12. - ISSN 0094-8276 - p. 3080 - 3084.
surface-temperature - variability - circulation - prediction - ensemble - model
 In decadal predictability studies, the subpolar Atlantic stands out as a region of high potential and real predictability. Since local temperature and salinity variations in the region are for a large part controlled by ocean dynamics, skillful predictability of the local ocean dynamics is a prerequisite to obtain multiyear predictability of other variables such as sea surface temperature. In this study, we discuss the predictability of the main ocean current system in the region, the subpolar gyre. From perfect model hindcasts exploiting initial condition information only from realistic ocean observation locations, we find that predictability is increased when Argo subsurface data are included. In our real-world experiments with initialized hindcasts, the observed decline in subpolar gyre strength of the mid-1990s is reproduced well and we find predictability of the subpolar gyre up to 2 years ahead, comparable to the skill of a damped persistence model.
Predicting multiyear North Atlantic Ocean variability
Hazeleger, W. ; Wouters, B. ; Oldenborgh, G.J. van; Corti, S. ; Palmer, T. ; Lloyd Smith, D. ; Dunstone, N. ; Kroger, J. ; Pohlmann, H. ; Storch, J.S. von - \ 2013
Journal of Geophysical Research: Oceans 118 (2013)3. - ISSN 2169-9275 - p. 1087 - 1098.
meridional overturning circulation - coupled climate models - surface-temperature - physical parametrizations - multidecadal variability - decadal variability - data assimilation - labrador sea - ecmwf model - ec-earth
We assess the skill of retrospective multiyear forecasts of North Atlantic ocean characteristics obtained with ocean-atmosphere-sea ice models that are initialized with estimates from the observed ocean state. We show that these multimodel forecasts can skilfully predict surface and subsurface ocean variability with lead times of 2 to 9 years. We focus on assessment of forecasts of major well-observed oceanic phenomena that are thought to be related to the Atlantic meridional overturning circulation (AMOC). Variability in the North Atlantic subpolar gyre, in particular that associated with the Atlantic Multidecadal Oscillation, is skilfully predicted 2-9 years ahead. The fresh water content and heat content in major convection areas such as the Labrador Sea are predictable as well, although individual events are not captured. The skill of these predictions is higher than that of uninitialized coupled model simulations and damped persistence. However, except for heat content in the subpolar gyre, differences between damped persistence and the initialized predictions are not significant. Since atmospheric variability is not predictable on multiyear time scales, initialization of the ocean and oceanic processes likely provide skill. Assessment of relationships of patterns of variability and ocean heat content and fresh water content shows differences among models indicating that model improvement can lead to further improvements of the predictions. The results imply there is scope for skilful predictions of the AMOC.
Real-time multi-model decadal climate predictions
Smith, D.M. ; Scaife, A.A. ; Boer, G.J. ; Caian, M. ; Doblas-Reyes, F.J. ; Guemas, V. ; Hawkins, E. ; Hazeleger, W. ; Hermanson, L. ; Ho, C.K. ; Ishii, M. ; Kharin, V. ; Kimoto, M. ; Kirtman, B. ; Lean, J. ; Matei, D. ; Merryfield, W.J. ; Muller, W.A. ; Pohlmann, H. ; Rosati, A. ; Wouters, B. ; Wyser, K. - \ 2013
Climate Dynamics 41 (2013)11-12. - ISSN 0930-7575 - p. 2875 - 2888.
surface-temperature - data assimilation - atlantic hurricanes - north-american - ensemble - model - design
We present the first climate prediction of the coming decade made with multiple models, initialized with prior observations. This prediction accrues from an international activity to exchange decadal predictions in near real-time, in order to assess differences and similarities, provide a consensus view to prevent over-confidence in forecasts from any single model, and establish current collective capability. We stress that the forecast is experimental, since the skill of the multi-model system is as yet unknown. Nevertheless, the forecast systems used here are based on models that have undergone rigorous evaluation and individually have been evaluated for forecast skill. Moreover, it is important to publish forecasts to enable open evaluation, and to provide a focus on climate change in the coming decade. Initialized forecasts of the year 2011 agree well with observations, with a pattern correlation of 0.62 compared to 0.31 for uninitialized projections. In particular, the forecast correctly predicted La Nia in the Pacific, and warm conditions in the north Atlantic and USA. A similar pattern is predicted for 2012 but with a weaker La Nia. Indices of Atlantic multi-decadal variability and Pacific decadal variability show no signal beyond climatology after 2015, while temperature in the Nio3 region is predicted to warm slightly by about 0.5 A degrees C over the coming decade. However, uncertainties are large for individual years and initialization has little impact beyond the first 4 years in most regions. Relative to uninitialized forecasts, initialized forecasts are significantly warmer in the north Atlantic sub-polar gyre and cooler in the north Pacific throughout the decade. They are also significantly cooler in the global average and over most land and ocean regions out to several years ahead. However, in the absence of volcanic eruptions, global temperature is predicted to continue to rise, with each year from 2013 onwards having a 50 % chance of exceeding the current observed record. Verification of these forecasts will provide an important opportunity to test the performance of models and our understanding and knowledge of the drivers of climate change.
Diagnosing evaporative fraction over land from boundary-layer clouds
Gentine, P. ; Ferguson, C.R. ; Holtslag, A.A.M. - \ 2013
Journal of Geophysical Research: Atmospheres 118 (2013)15. - ISSN 2169-897X - p. 8185 - 8196.
large-aperture scintillometer - large-eddy simulation - relative-humidity - mixed-layer - cumulus convection - diurnal behavior - soil-moisture - atmosphere interaction - surface-temperature - spatial variability
The potential use of continental fair-weather shallow cumuli as a way to retrieve the daily surface evaporative fraction over land is evaluated in convective conditions. The proposed method utilizes the fact that both the timing of cloud occurrence and the cloud base height at the time of occurrence provide strong constraints on the surface energy balance and evaporative fraction. The retrieval is especially reliable in the presence of relatively stable and humid free troposphere profiles. The advantage of the method is that it provides a more direct estimate of the surface evaporative fraction than indirect estimation based on inversion of a highly parameterized land surface model. In addition, the evaporative fraction is obtained at a scale of a few kilometers, which is more pertinent for weather and climate studies. The retrieval strategy is tested and validated for three contrasting climates: the U.S. southern Great Plains, West Africa, and the Netherlands. We suggest that the use of satellite observations of shallow cumuli can help constrain the retrieval of the surface evaporative fraction within a data assimilation scheme/reanalysis
Decadal prediction skill in a multi-model ensemble
Oldenborgh, G.J. van; Doblas-Reyes, F.J. ; Wouters, B. ; Hazeleger, W. - \ 2012
Climate Dynamics 38 (2012)7-8. - ISSN 0930-7575 - p. 1263 - 1280.
coupled climate models - surface-temperature - precipitation trends - north-atlantic - time-scales - el-nino - ocean - variability - pacific - predictability
Decadal climate predictions may have skill due to predictable components in boundary conditions (mainly greenhouse gas concentrations but also tropospheric and stratospheric aerosol distributions) and initial conditions (mainly the ocean state). We investigate the skill of temperature and precipitation hindcasts from a multi-model ensemble of four climate forecast systems based on coupled ocean-atmosphere models. Regional variations in skill with and without trend are compared with similarly analysed uninitialised experiments to separate the trend due to monotonically increasing forcings from fluctuations around the trend due to the ocean initial state and aerosol forcings. In temperature most of the skill in both multi-model ensembles comes from the externally forced trends. The rise of the global mean temperature is represented well in the initialised hindcasts, but variations around the trend show little skill beyond the first year due to the absence of volcanic aerosols in the hindcasts and the unpredictability of ENSO. The models have non-trivial skill in hindcasts of North Atlantic sea surface temperature beyond the trend. This skill is highest in the northern North Atlantic in initialised experiments and in the subtropical North Atlantic in uninitialised simulations. A similar result is found in the Pacific Ocean, although the signal is less clear. The uninitialised simulations have good skill beyond the trend in the western North Pacific. The initialised experiments show some skill in the decadal ENSO region in the eastern Pacific, in agreement with previous studies. However, the results in this study are not statistically significant (p ˜ 0.1) by themselves. The initialised models also show some skill in forecasting 4-year mean Sahel rainfall at lead times of 1 and 5 years, in agreement with the observed teleconnection from the Atlantic Ocean. Again, the skill is not statistically significant (p ˜ 0.2). Furthermore, uninitialised simulations that include volcanic aerosols have similar skill. It is therefore still an open question whether initialisation improves predictions of Sahel rainfall. We conclude that the main source of skill in forecasting temperature is the trend forced by rising greenhouse gas concentrations. The ocean initial state contributes to skill in some regions, but variations in boundary forcings such as aerosols are as important in decadal forecasting.
Response and sensitivity of the nocturnal boundary layer over land to added longwave radiative forcing
McNider, R.T. ; Steeneveld, G.J. ; Holtslag, A.A.M. ; Pielke sr., R.A. ; Mackaro, S. ; Pour Biazar, A. ; Walters, J. ; Nair, U. ; Christy, J. - \ 2012
Journal of Geophysical Research: Atmospheres 117 (2012). - ISSN 2169-897X
diurnal temperature-range - global climate model - surface-temperature - minimum temperature - atmospheric models - heat-flux - intermittent turbulence - vertical resolution - contrasting nights - soil-moisture
One of the most significant signals in the thermometer-observed temperature record since 1900 is the decrease in the diurnal temperature range over land, largely due to rising of the minimum temperatures. Generally, climate models have not well replicated this change in diurnal temperature range. Thus, the cause for night-time warming in the observed temperatures has been attributed to a variety of external causes. We take an alternative approach to examine the role that the internal dynamics of the stable nocturnal boundary layer (SNBL) may play in affecting the response and sensitivity of minimum temperatures to added downward longwave forcing. As indicated by previous nonlinear analyses of a truncated two-layer equation system, the SNBL can be very sensitive to changes in greenhouse gas forcing, surface roughness, heat capacity, and wind speed. A new single-column model growing out of these nonlinear studies is used to examine the SNBL. Specifically, budget analyses of the model are provided that evaluate the response of the boundary layer to forcing and sensitivity to mixing formulations. Based on these model analyses, it is likely that part of the observed long-term increase in minimum temperature is reflecting a redistribution of heat by changes in turbulence and not by an accumulation of heat in the boundary layer. Because of the sensitivity of the shelter level temperature to parameters and forcing, especially to uncertain turbulence parameterization in the SNBL, there should be caution about the use of minimum temperatures as a diagnostic global warming metric in either observations or models.
Retrieval of canopy component temperatures through Bayesian inversion of directional thermal measurements
Timmermans, J. ; Verhoef, W. ; Tol, C. van der; Su, Z. - \ 2009
Hydrology and Earth System Sciences 13 (2009)7. - ISSN 1027-5606 - p. 1249 - 1260.
reflection radiometer aster - balance system sebs - surface-temperature - land - algorithm - radiation - model - emission - fluxes - images
Evapotranspiration is usually estimated in remote sensing from single temperature value representing both soil and vegetation. This surface temperature is an aggregate over multiple canopy components. The temperature of the individual components can differ significantly, introducing errors in the evapotranspiration estimations. The temperature aggregate has a high level of directionality. An inversion method is presented in this paper to retrieve four canopy component temperatures from directional brightness temperatures. The Bayesian method uses both a priori information and sensor characteristics to solve the ill-posed inversion problem. The method is tested using two case studies: 1) a sensitivity analysis, using a large forward simulated dataset, and 2) in a reality study, using two datasets of two field campaigns. The results of the sensitivity analysis show that the Bayesian approach is able to retrieve the four component temperatures from directional brightness temperatures with good success rates using multi-directional sensors (Srspectra˜0.3, Srgonio˜0.3, and SrAATSR˜0.5), and no improvement using mono-angular sensors (Sr˜1). The results of the experimental study show that the approach gives good results for high LAI values (RMSEgrass=0.50 K, RMSEwheat=0.29 K, RMSEsugar beet=0.75 K, RMSEbarley=0.67 K); but for low LAI values the results were unsatisfactory (RMSEyoung maize=2.85 K). This discrepancy was found to originate from the presence of the metallic construction of the setup. As these disturbances, were only present for two crops and were not present in the sensitivity analysis, which had a low LAI, it is concluded that using masked thermal images will eliminate this discrepancy
A new remote optical wetness sensor and its applications
Heusinkveld, B.G. ; Berkowicz, S.M. ; Jacobs, A.F.G. ; Hillen, W.C.A.M. ; Holtslag, A.A.M. - \ 2008
Agricultural and Forest Meteorology 148 (2008)4. - ISSN 0168-1923 - p. 580 - 591.
soil-moisture - negev desert - surface-temperature - western-negev - dew formation - leaf wetness - reflectance - water - simulation - israel
An optical wetness sensor (OWS) was developed for continuous surface wetness measurements. The sensor is an all-weather instrument that does not interfere with the surface wetting and drying process and is unaffected by solar radiation. It is equipped with its own light source with which it can scan a surface and analyse its spectral reflectance. The backscattered radiation is detected around two wave bands: 1.70 ¿m (170 nm waveband) and 1.94 ¿m (80 nm waveband). The optical design is such that the ratio of the two signals is not dependent on the sampling distance, hence making it possible to study leaves under field conditions. Field and lab testing showed that the OWS was also capable of resolving small changes in surface soil water content such as from dew. In addition, the change of leaf water content could be detected (accuracy 5%). The OWS was also capable of measuring small changes in water content in the upper soil layer (
Mixtures of Gaussians for uncertainty description in bivariate latent heat flux proxies
Wójcik, R. ; Troch, P.A.A. ; Stricker, J.N.M. ; Torfs, P.J.J.F. - \ 2006
Journal of Hydrometeorology 7 (2006)3. - ISSN 1525-755X - p. 330 - 345.
surface-temperature - spatial variability - land-surface - model - forecasts - systems
This paper proposes a new probabilistic approach for describing uncertainty in the ensembles of latent heat flux proxies. The proxies are obtained from hourly Bowen ratio and satellite-derived measurements, respectively, at several locations in the southern Great Plains region in the United States. The novelty of the presented approach is that the proxies are not considered separately, but as bivariate samples from an underlying probability density function. To describe the latter, the use of Gaussian mixture density models¿a class of nonparametric, data-adaptive probability density functions¿is proposed. In this way any subjective assumptions (e.g., Gaussianity) on the form of bivariate latent heat flux ensembles are avoided. This makes the estimated mixtures potentially useful in nonlinear interpolation and nonlinear probabilistic data assimilation of noisy latent heat flux measurements. The results in this study show that both of these applications are feasible through regionalization of estimated mixture densities. The regionalization scheme investigated here utilizes land cover and vegetation fraction as discriminatory variables.
An analytical algorithm for the determination of vegetation leaf area index from TRMM/TMI data
Wen, J. ; Su, Z. - \ 2004
International Journal of Remote Sensing 25 (2004)6. - ISSN 0143-1161 - p. 1223 - 1234.
soil-moisture retrieval - surface-temperature - microwave emission - tibetan plateau - polarization - field - ndvi - ghz
In this paper, an analytical algorithm for the determination of land surface vegetation Leaf Area Index (LAI) with the passive microwave remote sensing data is developed. With the developed algorithm and the Tropical Rainfall Measuring Mission/Microwave Imager (TRMM/TMI) remote sensing data collected during the Global Energy and Water Experiment (GEWEX) Asian Monsoon Experiment in Tibet (GAME/Tibet) Intensive Observation Period (IOP'98), the regional and temporal distributions of the land surface vegetation LAI have been evaluated. To validate the developed algorithm and the retrieval results, the maximum-composite Normalized Difference Vegetation Index (NDVI) data over the same study area and period are used in this study; the cloud contaminated NDVI values have been replaced by the cloud-free values reconstructed by the Harmonic ANnalysis of Time Series (HANTS) technique. The results show that the retrieved LAI is in good agreement with the cloud-free NDVI in regional and temporal distributions and in their statistical characteristics; the vegetation characteristics can be clearly assessed from the regional distribution of the retrieved LAI. As lower frequency microwave radiation can penetrate atmosphere and thin cloud layer, with the application of the passive microwave remote sensing data, the developed algorithm can be used to monitor the land surface vegetation condition more effectively.
A practical algorithm to infer soil and foliage component temperatures from bi-angular ATSR-2 data
Jia, L. ; Li, Z.L. ; Menenti, M. ; Su, Z. ; Verhoef, W. ; Wan, Z. - \ 2003
International Journal of Remote Sensing 24 (2003)23. - ISSN 0143-1161 - p. 4739 - 4760.
surface-temperature - bidirectional reflectance - vegetation temperatures - atmospheric correction - solar spectrum - retrieval
An operational algorithm is proposed to retrieve soil and foliage component temperatures over heterogeneous land surface based on the analysis of bi-angular multi-spectral observations made by ATSR-2. Firstly, on the basis of the radiative transfer theory in a canopy, a model is developed to infer the two component temperatures using six channels of ATSR-2. Four visible, nearinfrared and short wave infrared channels are used to estimate the fractional vegetation cover within a pixel. A split-window method is developed to eliminate the atmospheric effects on the two thermal channels. An advanced method using all four visible, near-infrared and short wave channel measurements at two view angles is developed to perform atmospheric corrections in those channels allowing simultaneous retrieval of aerosol opacity and land surface bi-directional reflectance. Secondly, several case studies are undertaken with ATSR-2 data. The results indicate that both foliage and soil temperatures can be retrieved from bi-angular surface temperatures measurements. Finally, limitations and uncertainties in retrieving component temperatures using the present algorithm are discussed.
SVAT modeling over the Alpilles-ReSeDA experiment: comparing SVAT models over wheat fields
Olioso, A. ; Braud, I. ; Chanzy, A. ; Courault, D. ; Demarty, J. ; Kergoat, L. ; Lewan, E. ; Ottle, C. ; Prevot, L. ; Zhao, W.G.G. ; Calvet, J.C. ; Cayrol, P. ; Jongschaap, R.E.E. ; Moulin, S. ; Noilhan, J. ; Wigneron, J.P. - \ 2002
Agronomie 22 (2002)6. - ISSN 0249-5627 - p. 651 - 668.
soil-water - surface-temperature - land - evaporation - vegetation - parameterization - prediction - moisture - equation - zone
Remote sensing is an interesting tool for monitoring crop production, energy exchanges and mass exchanges between the soil, the biosphere and the atmosphere. The aim of the Alpilles-ReSeDA program was the development of such techniques combining remote sensing data, and soil and vegetation process models. This article focuses on SVAT models (Soil-Vegetation-Atmosphere Transfer models) which may be used for monitoring energy and mass exchanges by using assimilation of remote sensing data procedures. As a first step, we decided to implement a model comparison experiment with the aim of analyzing the relationships between the models' complexity, validity and potential for assimilating remote sensing data. This experiment involved the definition of three comparison scenarios with different objectives: (i) test the models' capacity to accurately describe processes using input parameters as measured in the field; (ii) test the portability of the models by using a priori information on input parameters (such as pedotransfer functions), and (iii) test the robustness of the models by a calibration/validation procedure. These 3 scenarios took advantage of the experimental network that was implemented during the Alpilles experiment and which combined measurements on different fields that may be used for calibration of models and their validations on independent data sets. The results showed that the models' performances were close whatever their complexity. The simpler models were less sensitive to the specification of input parameters. Significant improvements in the models' results were achieved when calibrating the models in comparison with the first scenario
A simple model for potential dewfall in an arid region
Jacobs, A.F.G. ; Heusinkveld, B.G. ; Berkowicz, S.M. - \ 2002
Atmospheric Research 64 (2002)39539. - ISSN 0169-8095 - p. 285 - 295.
negev desert - surface-temperature - dew - moisture - soil - fog - evaporation - ecosystem - canopy - israel
It is not always easy to know, post-facto, whether both dewfall and fog may have occurred over a given evening period. Instrumentation limitations make it difficult to quantify dew deposition since they rely on artificial sensing surfaces that are either visually examined on a daily basis or recorded. In arid to Mediterranean regions, both dew and fog can play significant ecological roles as suppliers of moisture. Long-term observation records of dew and fog in such regions tend to be limited, however, due partly to a lack of interest and limited distribution of well-instrumented meteorological stations. Simple meteorological criteria are suggested here to calculate potential dewfall and to indicate whether fog was likely to have occurred over a given evening. A field campaign was carried out in the NW Negev desert, Israel, in September and October 1997, to collect meteorological data and carry out dewfall measurements