Role of land surface parameter change in dust emission and impacts of dust on climate in Southwest Asia

2021 ◽  
Author(s):  
Ali Darvishi Boloorani ◽  
Mohammad Saeed Najafi ◽  
Saham Mirzaie
Keyword(s):  
Land Surface ◽  
Dust Emission ◽  
Southwest Asia ◽  
Parameter Change ◽  
Surface Parameter ◽  
Land Surface Parameter

Land surface parameter monitoring with ERS scatterometer data over the Sahel: A comparison between agro-pastoral and pastoral areas

2005 ◽  
Vol 96 (3-4) ◽  
pp. 438-452 ◽  
Author(s):  
S ZINE ◽  
L JARLAN ◽  
P FRISON ◽  
E MOUGIN ◽  
P HIERNAUX ◽  
...  
Keyword(s):  
Land Surface ◽  
Surface Parameter ◽  
Land Surface Parameter ◽  
Parameter Monitoring

The Impact of Land-Surface Parameter Properties and Resolution on the Simulated Cloud-Topped Atmospheric Boundary Layer

2017 ◽  
Vol 165 (3) ◽  
pp. 475-496 ◽  
Author(s):  
Leonhard Gantner ◽  
Vera Maurer ◽  
Norbert Kalthoff ◽  
Olga Kiseleva
Keyword(s):  
Boundary Layer ◽  
Atmospheric Boundary Layer ◽  
Land Surface ◽  
Surface Parameter ◽  
Land Surface Parameter ◽  
The Impact

scholarly journals Modeling the Summertime Climate of Southwest Asia: The Role of Land Surface Processes in Shaping the Climate of Semiarid Regions

2012 ◽  
Vol 25 (2) ◽  
pp. 704-719 ◽  
Author(s):  
Marc P. Marcella ◽  
Elfatih A. B. Eltahir
Keyword(s):  
Vapor Pressure ◽  
Land Surface ◽  
Surface Albedo ◽  
Incident Radiation ◽  
Radiation Budget ◽  
Surface Processes ◽  
Southwest Asia ◽  
Land Surface Processes ◽  
Semiarid Regions

Abstract Presented is a study on the role of land surface processes in determining the summertime climate over the semiarid region of southwest Asia. In this region, a warm surface air temperature bias of 3.5°C is simulated in the summer by using the standard configuration of Regional Climate Model version 3 (RegCM3). Biases are also simulated in surface albedo (underestimation), shortwave incident radiation (overestimation), and vapor pressure (underestimation). Based on satellite measurements documented in NASA’s surface radiation budget (SRB) dataset, a correction in surface albedo by 4% is introduced in RegCM3 to match the observed SRB data. Increasing albedo values results in a nearly 1°C cooling over the region. In addition, by incorporating RegCM3’s dust module and including subgrid variability for surface wind, shortwave incident radiation bias originally of about 45 W m−2 is reduced by 30 W m−2. As a result, the reduction of shortwave incident radiation cools the surface by 0.6°C. Finally, including a representation for the irrigation and marshlands of Mesopotamia produces surface relative humidity values closer to observations, thus eliminating a nearly 5-mb vapor pressure dry bias over some of the region. Consequently, the representation of irrigation and marshlands results in cooling of nearly 1°C in areas downwind of the actual land-cover change. Along with identified biases in observational datasets, these combined processes explain the 3.5°C warm bias in RegCM3 simulations. Therefore, it is found that accurate representations of surface albedo, dust emissions, and irrigation are important in correctly modeling summertime climates of semiarid regions.

scholarly journals Optimally Merging Precipitation to Minimize Land Surface Modeling Errors

2010 ◽  
Vol 49 (3) ◽  
pp. 415-423 ◽  
Author(s):  
M. Tugrul Yilmaz ◽  
Paul Houser ◽  
Roshan Shrestha ◽  
Valentine G. Anantharaj
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Land Surface Model ◽  
Surface Modeling ◽  
Surface Model ◽  
Surface Parameter ◽  
Land Surface Modeling ◽  
Precipitation Product ◽  
Land Surface Parameter ◽  
Modeling Errors

Abstract This paper introduces a new method to improve land surface model skill by merging different available precipitation datasets, given that an accurate land surface parameter ground truth is available. Precipitation datasets are merged with the objective of improving terrestrial water and energy cycle simulation skill, unlike most common methods in which the merging skills are evaluated by comparing the results with gauge data or selected reference data. The optimal merging method developed in this study minimizes the simulated land surface parameter (soil moisture, temperature, etc.) errors using the Noah land surface model with the Nelder–Mead (downhill simplex) method. In addition to improving the simulation skills, this method also impedes the adverse impacts of single-source precipitation data errors. Analysis has indicated that the results from the optimally merged precipitation product have fewer errors in other land surface states and fluxes such as evapotranspiration (ET), discharge R, and skin temperature T than do simulation results obtained by forcing the model using the precipitation products individually. It is also found that, using this method, the true knowledge of soil moisture information minimized land surface modeling errors better than the knowledge of other land surface parameters (ET, R, and T). Results have also shown that, although it does not have the true precipitation information, the method has associated heavier weights with the precipitation product that has intensity, amount, and frequency that are similar to those of the true precipitation.

scholarly journals European plant phenology and climate as seen in a 20-year AVHRR land-surface parameter dataset

2004 ◽  
Vol 25 (17) ◽  
pp. 3303-3330 ◽  
Author(s):  
R. Stöckli ◽  
P. L. Vidale
Keyword(s):  
Land Surface ◽  
Plant Phenology ◽  
Surface Parameter ◽  
Land Surface Parameter

Regularized kernel-based BRDF model inversion method for ill-posed land surface parameter retrieval

2007 ◽  
Vol 111 (1) ◽  
pp. 36-50 ◽  
Author(s):  
Yanfei Wang ◽  
Xiaowen Li ◽  
Zuhair Nashed ◽  
Feng Zhao ◽  
Hua Yang ◽  
...  
Keyword(s):  
Land Surface ◽  
Inversion Method ◽  
Surface Parameter ◽  
Model Inversion ◽  
Land Surface Parameter ◽  
Ill Posed ◽  
Parameter Retrieval

The impact of the SSM/I antenna gain function on land surface parameter retrieval

1999 ◽  
Vol 26 (23) ◽  
pp. 3481-3484 ◽  
Author(s):  
Matthias Drusch ◽  
Eric F. Wood ◽  
Ralf Lindau
Keyword(s):  
Land Surface ◽  
Antenna Gain ◽  
Gain Function ◽  
Surface Parameter ◽  
Land Surface Parameter ◽  
The Impact ◽  
Parameter Retrieval

scholarly journals Quantifying uncertainties in projections of extremes—a perturbed land surface parameter experiment

2010 ◽  
Vol 37 (7-8) ◽  
pp. 1381-1398 ◽  
Author(s):  
Erich M. Fischer ◽  
David M. Lawrence ◽  
Benjamin M. Sanderson
Keyword(s):  
Land Surface ◽  
Surface Parameter ◽  
Land Surface Parameter ◽  
Parameter Experiment
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