scholarly journals A New Technique for Estimation of Surface Latent Heat Fluxes Using Satellite-Based Observations

2005 ◽  
Vol 133 (9) ◽  
pp. 2692-2710 ◽  
Author(s):  
Randhir Singh ◽  
P. C. Joshi ◽  
C. M. Kishtawal

Abstract Monthly mean surface latent heat fluxes (LHFs) over the global oceans are estimated using bulk formula. LHFs are computed using wind speed (U) from the Special Sensor Microwave Imager (SSM/I), sea surface temperature (SST) from the Advanced Very High Resolution Radiometer (AVHRR), and near-surface specific humidity. Near-surface specific humidity (Qa) is estimated from SSM/I-observed precipitable water (W) and AVHRR-observed SST using a genetic algorithm (GA) approach. The GA-retrieved monthly mean Qa has an accuracy of 0.80 ± 0.32 g kg−1 as compared with surface marine observations based on the Comprehensive Ocean–Atmosphere Data Set (COADS). The GA approach improves upon the surface specific humidity retrieval based on regression, the EOF approach, and is comparable to the artificial neural network technique. The satellite-derived LHFs are compared with globally distributed surface marine observations to monthly averages of 1° × 1° latitude–longitude bins, during 1988–93. When GA-retrieved Qa is used in the computation of satellite-derived latent heat fluxes (LHFGA) the global mean rmse, bias, and correlation are 22 ± 8 W m−2, 5 W m−2, and 0.85, respectively, for monthly mean latent heat fluxes. The rmses in LHF are larger when Qa is retrieved using regression and EOF approaches.

2017 ◽  
Author(s):  
Julian Kinzel ◽  
Marc Schröder ◽  
Karsten Fennig ◽  
Axel Andersson ◽  
Rainer Hollmann

Abstract. Latent heat fluxes (LHF) are one of the main contributors to the global energy budget. As the density of LHF measurements over the global oceans is generally poor, the potential of remotely sensed LHF for meteorological applications is enormous. However, to date none of the available satellite products include estimates of systematic, random retrieval, and sampling uncertainties, all of which are essential for assessing their quality. Here, this challenge is taken on by applying regionally independent multi-dimensional bias analyses to LHF-related parameters (wind speed U, near-surface specific humidity qa, and sea surface saturation specific humidity qs) of the Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite (HOAPS) climatology. In connection with multiple triple collocation analyses, it is demonstrated how both instantaneous (gridded) uncertainty measures may be assigned to each pixel (grid box). A high-quality in situ data archive including buoys and selected ships serves as the ground reference. Results show that systematic LHF uncertainties range between 15–50 W m-2 with a global mean of 25 W m-2. Local maxima are mainly found over the subtropical ocean basins as well as along the western boundary currents. Investigations indicate that contributions by qa (U) to the overall LHF uncertainty are in the order of 60 % (25 %). From an instantaneous point of view, random retrieval uncertainties are specifically large over the subtropics with a global average of 37 W m-2. In a climatological sense, their magnitudes become negligible, as do respective sampling uncertainties. Time series analyses show footprints of climate events, such as the strong El Niño during 1997/98. Regional and seasonal analyses suggest that largest total (i.e., systematic + instantaneous random) LHF uncertainties are seen over the Gulf Stream and the Indian monsoon region during boreal winter. In light of the uncertainty measures, the observed continuous global mean LHF increase up to 2009 needs to be treated with caution. First intercomparisons to other LHF climatologies (in situ, satellite) reveal overall resemblance with few, yet distinct exceptions.


2016 ◽  
Vol 33 (7) ◽  
pp. 1455-1471 ◽  
Author(s):  
Julian Kinzel ◽  
Karsten Fennig ◽  
Marc Schröder ◽  
Axel Andersson ◽  
Karl Bumke ◽  
...  

AbstractLatent heat fluxes (LHF) play an essential role in the global energy budget and are thus important for understanding the climate system. Satellite-based remote sensing permits a large-scale determination of LHF, which, among others, are based on near-surface specific humidity . However, the random retrieval error () remains unknown. Here, a novel approach is presented to quantify the error contributions to pixel-level of the Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data, version 3.2 (HOAPS, version 3.2), dataset. The methodology makes use of multiple triple collocation (MTC) analysis between 1995 and 2008 over the global ice-free oceans. Apart from satellite records, these datasets include selected ship records extracted from the Seewetteramt Hamburg (SWA) archive and the International Comprehensive Ocean–Atmosphere Data Set (ICOADS), serving as the in situ ground reference. The MTC approach permits the derivation of as the sum of model uncertainty and sensor noise , while random uncertainties due to in situ measurement errors () and collocation () are isolated concurrently. Results show an average of 1.1 ± 0.3 g kg−1, whereas the mean () is in the order of 0.5 ± 0.1 g kg−1 (0.5 ± 0.3 g kg−1). Regional analyses indicate a maximum of exceeding 1.5 g kg−1 within humidity regimes of 12–17 g kg−1, associated with the single-parameter, multilinear retrieval applied in HOAPS. Multidimensional bias analysis reveals that global maxima are located off the Arabian Peninsula.


2020 ◽  
Vol 33 (19) ◽  
pp. 8415-8437
Author(s):  
Franklin R. Robertson ◽  
Jason B. Roberts ◽  
Michael G. Bosilovich ◽  
Abderrahim Bentamy ◽  
Carol Anne Clayson ◽  
...  

AbstractFour state-of-the-art satellite-based estimates of ocean surface latent heat fluxes (LHFs) extending over three decades are analyzed, focusing on the interannual variability and trends of near-global averages and regional patterns. Detailed intercomparisons are made with other datasets including 1) reduced observation reanalyses (RedObs) whose exclusion of satellite data renders them an important independent diagnostic tool; 2) a moisture budget residual LHF estimate using reanalysis moisture transport, atmospheric storage, and satellite precipitation; 3) the ECMWF Reanalysis 5 (ERA5); 4) Remote Sensing Systems (RSS) single-sensor passive microwave and scatterometer wind speed retrievals; and 5) several sea surface temperature (SST) datasets. Large disparities remain in near-global satellite LHF trends and their regional expression over the 1990–2010 period, during which time the interdecadal Pacific oscillation changed sign. The budget residual diagnostics support the smaller RedObs LHF trends. The satellites, ERA5, and RedObs are reasonably consistent in identifying contributions by the 10-m wind speed variations to the LHF trend patterns. However, contributions by the near-surface vertical humidity gradient from satellites and ERA5 trend upward in time with respect to the RedObs ensemble and show less agreement in trend patterns. Problems with wind speed retrievals from Special Sensor Microwave Imager/Sounder satellite sensors, excessive upward trends in trends in Optimal Interpolation Sea Surface Temperature (OISST AVHRR-Only) data used in most satellite LHF estimates, and uncertainties associated with poor satellite coverage before the mid-1990s are noted. Possibly erroneous trends are also identified in ERA5 LHF associated with the onset of scatterometer wind data assimilation in the early 1990s.


Agromet ◽  
2011 ◽  
Vol 25 (1) ◽  
pp. 24
Author(s):  
Satyanto Krido Saptomo

<em>Artificial neural network (ANN) approach was used to model energy dissipation process into sensible heat and latent heat (evapotranspiration) fluxes. The ANN model has 5 inputs which are leaf temperature T<sub>l</sub>, air temperature T<sub>a</sub>, net radiation R<sub>n</sub>, wind speed u<sub>c</sub> and actual vapor pressure e<sub>a</sub>. Adjustment of ANN was conducted using back propagation technique, employing measurement data of input and output parameters of the ANN. The estimation results using the adjusted ANN shows its capability in resembling the heat dissipation process by giving outputs of sensible and latent heat fluxes closed to its respective measurement values as the measured input values are given.  The ANN structure presented in this paper suits for modeling similar process over vegetated surfaces, but the adjusted parameters are unique. Therefore observation data set for each different vegetation and adjustment of ANN are required.</em>


2018 ◽  
Vol 10 (10) ◽  
pp. 1640 ◽  
Author(s):  
Ralph Ferraro ◽  
Brian Nelson ◽  
Tom Smith ◽  
Olivier Prat

Passive microwave measurements have been available on satellites back to the 1970s, first flown on research satellites developed by the National Aeronautics and Space Administration (NASA). Since then, several other sensors have been flown to retrieve hydrological products for both operational weather applications (e.g., the Special Sensor Microwave/Imager—SSM/I; the Advanced Microwave Sounding Unit—AMSU) and climate applications (e.g., the Advanced Microwave Scanning Radiometer—AMSR; the Tropical Rainfall Measurement Mission Microwave Imager—TMI; the Global Precipitation Mission Microwave Imager—GMI). Here, the focus is on measurements from the AMSU-A, AMSU-B, and Microwave Humidity Sounder (MHS). These sensors have been in operation since 1998, with the launch of NOAA-15, and are also on board NOAA-16, -17, -18, -19, and the MetOp-A and -B satellites. A data set called the “Hydrological Bundle” is a climate data record (CDR) that utilizes brightness temperatures from fundamental CDRs (FCDRs) to generate thematic CDRs (TCDRs). The TCDRs include total precipitable water (TPW), cloud liquid water (CLW), sea-ice concentration (SIC), land surface temperature (LST), land surface emissivity (LSE) for 23, 31, 50 GHz, rain rate (RR), snow cover (SC), ice water path (IWP), and snow water equivalent (SWE). The TCDRs are shown to be in general good agreement with similar products from other sources, such as the Global Precipitation Climatology Project (GPCP) and the Modern-Era Retrospective Analysis for Research and Applications (MERRA-2). Due to the careful intercalibration of the FCDRs, little bias is found among the different TCDRs produced from individual NOAA and MetOp satellites, except for normal diurnal cycle differences.


2019 ◽  
Vol 7 (2) ◽  
pp. 28 ◽  
Author(s):  
Si Gao ◽  
Shengbin Jia ◽  
Yanyu Wan ◽  
Tim Li ◽  
Shunan Zhai ◽  
...  

The possible role of air–sea latent heat flux (LHF) in tropical cyclone (TC) genesis over the western North Pacific (WNP) is investigated using state-of-the-art satellite and analysis datasets. The authors conducted composite analyses of several meteorological variables after identifying developing and non-developing tropical disturbances from June to October of the period 2000 to 2009. Compared to the non-developing disturbances, increased LHF underlying the developing disturbances enhances boundary–layer specific humidity. The secondary circulation then transports more boundary–layer moisture inward and upward and, thus, induces a stronger moist core in the middle troposphere. Accordingly, the air in the core region ascends following a warmer moist adiabat than that in the environment and results in a stronger upper-level warm core, which is associated with a stronger near-surface tangential wind based on the thermal wind balance. This enlarges the magnitude and negative radial gradient of LHF and, thereby, further increases boundary–layer specific humidity. A tropical depression forms when the near-surface tangential wind increases to a certain extent as a result of the continuing positive feedback between near-surface wind and LHF. The results suggest an important role of wind-driven LHF in TC genesis over the WNP.


2019 ◽  
Vol 58 (6) ◽  
pp. 1399-1415 ◽  
Author(s):  
Miao Yu ◽  
Jorge González ◽  
Shiguang Miao ◽  
Prathap Ramamurthy

AbstractA cooling tower scheme that quantifies the sensible and latent anthropogenic heat fluxes released from buildings was coupled to an operational forecasting system [Rapid Refresh Multiscale Analysis and Prediction of the Beijing Urban Meteorological Institute (RMAPS-Urban)] and was evaluated in the context of the megacity of Beijing, China, during summer months. The objective of this scheme is to correct for underestimations of surface latent heat fluxes in regional climate modeling and weather forecasts in urban areas. The performance for surface heat fluxes by the modified RMAPS-Urban is greatly improved when compared with a suite of observations in Beijing. The cooling tower scheme increases the anthropogenic latent heat partition by 90% of the total anthropogenic heat flux release. Averaged surface latent heat flux in urban areas increases to about 64.3 W m−2 with a peak of 150 W m−2 on dry summer days and 40.35 W m−2 with a peak of 150 W m−2 on wet summer days. The model performance of near-surface temperature and humidity is also improved. Average 2-m temperature errors are reduced by 1°C, and maximum and minimum temperature errors are improved by 2°–3°C; absolute humidity is increased by 5%.


2015 ◽  
Vol 8 (3) ◽  
pp. 1407-1424 ◽  
Author(s):  
H. C. Ward ◽  
J. G. Evans ◽  
C. S. B. Grimmond

Abstract. A millimetre-wave scintillometer was paired with an infrared scintillometer, enabling estimation of large-area evapotranspiration across northern Swindon, a suburban area in the UK. Both sensible and latent heat fluxes can be obtained using this "two-wavelength" technique, as it is able to provide both temperature and humidity structure parameters, offering a major advantage over conventional single-wavelength scintillometry. The first paper of this two-part series presented the measurement theory and structure parameters. In this second paper, heat fluxes are obtained and analysed. These fluxes, estimated using two-wavelength scintillometry over an urban area, are the first of their kind. Source area modelling suggests the scintillometric fluxes are representative of 5–10 km2. For comparison, local-scale (0.05–0.5 km2) fluxes were measured by an eddy covariance station. Similar responses to seasonal changes are evident at the different scales but the energy partitioning varies between source areas. The response to moisture availability is explored using data from 2 consecutive years with contrasting rainfall patterns (2011–2012). This extensive data set offers insight into urban surface-atmosphere interactions and demonstrates the potential for two-wavelength scintillometry to deliver fluxes over mixed land cover, typically representative of an area 1–2 orders of magnitude greater than for eddy covariance measurements. Fluxes at this scale are extremely valuable for hydro-meteorological model evaluation and assessment of satellite data products.


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