Spatio‐temporal variability of summer monsoon surface air temperature over India and its regions using Regional Climate Model

2021 ◽  
Author(s):  
Shruti Verma ◽  
R. Bhatla ◽  
S. Ghosh ◽  
Palash Sinha ◽  
R.K. Mall ◽  
...  
Keyword(s):  
Regional Climate Model ◽  
Air Temperature ◽  
Summer Monsoon ◽  
Temporal Variability ◽  
Climate Model ◽  
Regional Climate ◽  
Surface Air Temperature ◽  
Its Regions ◽  
Spatio Temporal

scholarly journals Panama’s Current Climate Replicability in a Non-Hydrostatic Regional Climate Model Nested in an Atmospheric General Circulation Model

Atmosphere ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1543
Author(s):  
Reinhardt Pinzón ◽  
Noriko N. Ishizaki ◽  
Hidetaka Sasaki ◽  
Tosiyuki Nakaegawa
Keyword(s):  
Regional Climate Model ◽  
Air Temperature ◽  
General Circulation ◽  
Climate Model ◽  
Regional Climate ◽  
Surface Air Temperature ◽  
Circulation Model ◽  
Horizontal Resolution ◽  
Temperature And Precipitation ◽  
Current Climate

To simulate the current climate, a 20-year integration of a non-hydrostatic regional climate model (NHRCM) with grid spacing of 5 and 2 km (NHRCM05 and NHRCM02, respectively) was nested within the AGCM. The three models did a similarly good job of simulating surface air temperature, and the spatial horizontal resolution did not affect these statistics. NHRCM02 did a good job of reproducing seasonal variations in surface air temperature. NHRCM05 overestimated annual mean precipitation in the western part of Panama and eastern part of the Pacific Ocean. NHRCM05 is responsible for this overestimation because it is not seen in MRI-AGCM. NHRCM02 simulated annual mean precipitation better than NHRCM05, probably due to a convection-permitting model without a convection scheme, such as the Kain and Fritsch scheme. Therefore, the finer horizontal resolution of NHRCM02 did a better job of replicating the current climatological mean geographical distributions and seasonal changes of surface air temperature and precipitation.

scholarly journals Regional Climate Model Simulations of U.S. Precipitation and Surface Air Temperature during 1982–2002: Interannual Variation

2007 ◽  
Vol 20 (2) ◽  
pp. 218-232 ◽  
Author(s):  
Jinhong Zhu ◽  
Xin-Zhong Liang
Keyword(s):  
Regional Climate Model ◽  
Air Temperature ◽  
Interannual Variation ◽  
Climate Model ◽  
Regional Climate ◽  
Phase Relationship ◽  
Surface Air Temperature ◽  
Department Of Energy ◽  
Precipitation Pattern ◽  
Interannual Variations

Abstract The fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5)-based regional climate model (CMM5) capability in simulating the interannual variations of U.S. precipitation and surface air temperature during 1982–2002 is evaluated with a continuous baseline integration driven by the NCEP–Department of Energy (DOE) Second Atmospheric Model Intercomparison Project Reanalysis (R-2). It is demonstrated that the CMM5 has a pronounced downscaling skill for precipitation and temperature interannual variations. The EOF and correlation analyses illustrate that, for both quantities, the CMM5 captures the spatial pattern, temporal evolution, and circulation teleconnections much better than the R-2. In particular, the CMM5 more realistically simulates the precipitation pattern centered in the Northwest, where the representation of the orographic enhancement by the forced uplifting during winter (rainy season) is greatly improved over the R-2. The downscaling skill, however, is sensitive to the cumulus parameterization. This sensitivity is studied by comparing the baseline with a branch summer integration replacing the Grell with the Kain–Fritsch cumulus scheme in the CMM5. The dominant EOF mode of the U.S. summer precipitation interannual variation, identified with the out-of-phase relationship between the Midwest and Southeast in observations, is reproduced more accurately by the Grell than the Kain–Fritsch scheme, which largely underestimates the variation in the Midwest. This pattern is associated with east–west movement of the Great Plains low-level jet (LLJ): a more western position corresponds to a stronger southerly flow bringing more moisture and heavier rainfall in the Midwest and less in the Southeast. The second EOF pattern, which describes the consistent variation over the southern part of the Midwest and the South in observations, is captured better by the Kain–Fritsch scheme than the Grell, whose pattern systematically shifts southward.

scholarly journals Biogeophysical impacts of peatland forestation on regional climate changes in Finland

2014 ◽  
Vol 11 (24) ◽  
pp. 7251-7267 ◽  
Author(s):  
Y. Gao ◽  
T. Markkanen ◽  
L. Backman ◽  
H. M. Henttonen ◽  
J.-P. Pietikäinen ◽  
...  
Keyword(s):  
Land Cover ◽  
Air Temperature ◽  
Surface Albedo ◽  
Climate Model ◽  
Regional Climate ◽  
Surface Air Temperature ◽  
Forest Growth ◽  
Background Information ◽  
Snow Melting ◽  
Melting Period

Abstract. Land cover changes can impact the climate by influencing the surface energy and water balance. Naturally treeless or sparsely treed peatlands were extensively drained to stimulate forest growth in Finland over the second half of 20th century. The aim of this study is to investigate the biogeophysical effects of peatland forestation on regional climate in Finland. Two sets of 18-year climate simulations were done with the regional climate model REMO by using land cover data based on pre-drainage (1920s) and post-drainage (2000s) Finnish national forest inventories. In the most intensive peatland forestation area, located in the middle west of Finland, the results show a warming in April of up to 0.43 K in monthly-averaged daily mean 2 m air temperature, whereas a slight cooling from May to October of less than 0.1 K in general is found. Consequently, snow clearance days over that area are advanced up to 5 days in the mean of 15 years. No clear signal is found for precipitation. Through analysing the simulated temperature and energy balance terms, as well as snow depth over five selected subregions, a positive feedback induced by peatland forestation is found between decreased surface albedo and increased surface air temperature in the snow-melting period. Our modelled results show good qualitative agreements with the observational data. In general, decreased surface albedo in the snow-melting period and increased evapotranspiration in the growing period are the most important biogeophysical aspects induced by peatland forestation that cause changes in climate. The results from this study can be further integrally analysed with biogeochemical effects of peatland forestation to provide background information for adapting future forest management to mitigate climate warming effects. Moreover, they provide insights about the impacts of projected forestation of tundra at high latitudes due to climate change.

scholarly journals Assessing the Effects of Spatial Resolution on Regional Climate Model Simulated Summer Temperature and Precipitation in China: A Case Study

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Xin-Min Zeng ◽  
Ming Wang ◽  
Yujian Zhang ◽  
Yang Wang ◽  
Yiqun Zheng
Keyword(s):  
Regional Climate Model ◽  
South China ◽  
Climate Model ◽  
Regional Climate ◽  
Surface Air Temperature ◽  
Northern China ◽  
Horizontal Resolution ◽  
Vertical Resolution ◽  
Humid Climate ◽  
Entire Area

The regional climate model, RegCM3, is used to simulate the 2004 summer surface air temperature (SAT) and precipitation at different horizontal (i.e., 30, 60, and 90 km) and vertical resolutions (i.e., 14, 18, and 23 layers). Results showed that increasing resolution evidently changes simulated SATs with regional characteristics. For example, simulated SATs are apparently better produced when horizontal resolution increases from 60 to 30 km under the 23 layers. Meanwhile, the SATs over the entire area are more sensitive to vertical resolution than horizontal resolution. The subareas present higher sensitivities than the total area, with larger horizontal resolution effects than those of vertical resolution. For precipitation, increasing resolution shows higher impact compared to SAT, with higher sensitivity induced by vertical resolution than by horizontal resolution, especially in rainy South China. The best SAT/precipitation can be produced only when the horizontal and vertical resolutions are reasonably configured. This indicates that different resolutions lead to different atmospheric thermodynamic states. Because of the dry climate and low soil heat capacity in Northern China, resolution changes easily modify surface energy fluxes, hence the SAT; due to the rainy and humid climate in South China, resolution changes likely strongly influence grid-scale structure of clouds and therefore precipitation.

scholarly journals A novel method for assessing climate change impacts in ecotron experiments

2020 ◽  
Vol 64 (10) ◽  
pp. 1709-1727
Author(s):  
Inne Vanderkelen ◽  
Jakob Zscheischler ◽  
Lukas Gudmundsson ◽  
Klaus Keuler ◽  
Francois Rineau ◽  
...  
Keyword(s):  
Climate Change ◽  
Regional Climate Model ◽  
Air Temperature ◽  
Climate Model ◽  
Regional Climate ◽  
Climate Forcing ◽  
Future Climate Change ◽  
Ecosystem Responses ◽  
Model Projection ◽  
Global Mean

Abstract Ecotron facilities allow accurate control of many environmental variables coupled with extensive monitoring of ecosystem processes. They therefore require multivariate perturbation of climate variables, close to what is observed in the field and projections for the future. Here, we present a new method for creating realistic climate forcing for manipulation experiments and apply it to the UHasselt Ecotron experiment. The new methodology uses data derived from the best available regional climate model projection and consists of generating climate forcing along a gradient representative of increasingly high global mean air temperature anomalies. We first identified the best-performing regional climate model simulation for the ecotron site from the Coordinated Regional Downscaling Experiment in the European domain (EURO-CORDEX) ensemble based on two criteria: (i) highest skill compared to observations from a nearby weather station and (ii) representativeness of the multi-model mean in future projections. The time window is subsequently selected from the model projection for each ecotron unit based on the global mean air temperature of the driving global climate model. The ecotron units are forced with 3-hourly output from the projections of the 5-year period in which the global mean air temperature crosses the predefined values. With the new approach, Ecotron facilities become able to assess ecosystem responses on changing climatic conditions, while accounting for the co-variation between climatic variables and their projection in variability, well representing possible compound events. The presented methodology can also be applied to other manipulation experiments, aiming at investigating ecosystem responses to realistic future climate change.

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