The different impacts of the daytime and nighttime land surface temperatures on the alpine grassland phenology

Abstract. General circulation models (GCMs) are routinely run under Atmospheric Modelling Intercomparison Project (AMIP) conditions with prescribed sea surface temperatures (SSTs) and sea ice concentrations (SICs) from observations. These AMIP simulations are often used to evaluate the role of the land and/or atmosphere in causing the development of systematic errors in such GCMs. Extensions to the original AMIP experiment have also been developed to evaluate the response of the global climate to increased SSTs (prescribed) and carbon-dioxide (CO2) as part of the Cloud Feedback Model Intercomparison Project (CFMIP). None of these international modelling initiatives has undertaken a set of experiments where the land conditions are also prescribed, which is the focus of the work presented in this paper. Experiments are performed initially with freely varying land conditions (surface temperature and, soil temperature and mositure) under five different configurations (AMIP, AMIP with uniform 4 K added to SSTs, AMIP SST with quadrupled CO2, AMIP SST and quadrupled CO2 without the plant stomata response, and increasing the solar constant by 3.3 %). Then, the land surface temperatures from the free-land experiments are used to perform a set of “AMIP-prescribed land” (PL) simulations, which are evaluated against their free-land counterparts. The PL simulations agree well with the free-land experiments, which indicates that the land surface is prescribed in a way that is consistent with the original free-land configuration. Further experiments are also performed with different combinations of SSTs, CO2 concentrations, solar constant and land conditions. For example, SST and land conditions are used from the AMIP simulation with quadrupled CO2 in order to simulate the atmospheric response to increased CO2 concentrations without the surface temperature changing. The results of all these experiments have been made publicly available for further analysis. The main aims of this paper are to provide a description of the method used and an initial validation of these AMIP-prescribed land experiments.

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Quantifying the Congruence between Air and Land Surface Temperatures for Various Climatic and Elevation Zones of Western Himalaya

Remote Sensing ◽

10.3390/rs11242889 ◽

2019 ◽

Vol 11 (24) ◽

pp. 2889 ◽

Cited By ~ 3

Author(s):

Shaktiman Singh ◽

Anshuman Bhardwaj ◽

Atar Singh ◽

Lydia Sam ◽

Mayank Shekhar ◽

...

Keyword(s):

Air Temperature ◽

Land Surface ◽

Extreme Environments ◽

Western Himalaya ◽

In Situ Monitoring ◽

Lapse Rate ◽

Similar Data ◽

Surface Temperatures ◽

Land Surface Temperatures

The surface and near-surface air temperature observations are primary data for glacio-hydro-climatological studies. The in situ air temperature (Ta) observations require intense logistic and financial investments, making it sparse and fragmented particularly in remote and extreme environments. The temperatures in Himalaya are controlled by a complex system driven by topography, seasons, and cryosphere which further makes it difficult to record or predict its spatial heterogeneity. In this regard, finding a way to fill the observational spatiotemporal gaps in data becomes more crucial. Here, we show the comparison of Ta recorded at 11 high altitude stations in Western Himalaya with their respective land surface temperatures (Ts) recorded by Moderate Resolution Imagining Spectroradiometer (MODIS) Aqua and Terra satellites in cloud-free conditions. We found remarkable seasonal and spatial trends in the Ta vs. Ts relationship: (i) Ts are strongly correlated with Ta (R2 = 0.77, root mean square difference (RMSD) = 5.9 °C, n = 11,101 at daily scale and R2 = 0.80, RMSD = 5.7 °C, n = 3552 at 8-day scale); (ii) in general, the RMSD is lower for the winter months in comparison to summer months for all the stations, (iii) the RMSD is directly proportional to the elevations; (iv) the RMSD is inversely proportional to the annual precipitation. Our results demonstrate the statistically strong and previously unreported Ta vs. Ts relationship and spatial and seasonal variations in its intensity at daily resolution for the Western Himalaya. We anticipate that our results will provide the scientists in Himalaya or similar data-deficient extreme environments with an option to use freely available remotely observed Ts products in their models to fill-up the spatiotemporal data gaps related to in situ monitoring at daily resolution. Substituting Ta by Ts as input in various geophysical models can even improve the model accuracy as using spatially continuous satellite derived Ts in place of discrete in situ Ta extrapolated to different elevations using a constant lapse rate can provide more realistic estimates.

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