scholarly journals Can significant trends be detected in surface air temperature and precipitation over South America in recent decades?

2016 ◽  
Vol 37 (3) ◽  
pp. 1483-1493 ◽  
Author(s):  
Daniel de Barros Soares ◽  
Huikyo Lee ◽  
Paul C. Loikith ◽  
Armineh Barkhordarian ◽  
Carlos R. Mechoso
Keyword(s):  
South America ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Temperature And Precipitation

scholarly journals Seasonal Surface Air Temperature and Precipitation in the FSU Climate Model Coupled to the CLM2

2005 ◽  
Vol 18 (16) ◽  
pp. 3217-3228 ◽  
Author(s):  
D. W. Shin ◽  
S. Cocke ◽  
T. E. LaRow ◽  
James J. O’Brien
Keyword(s):  
Heat Flux ◽  
Air Temperature ◽  
Climate Model ◽  
Initial Conditions ◽  
Sensible Heat Flux ◽  
Surface Air Temperature ◽  
Community Land Model ◽  
Temperature And Precipitation ◽  
The Impact ◽  
Convective Scheme

Abstract The current Florida State University (FSU) climate model is upgraded by coupling the National Center for Atmospheric Research (NCAR) Community Land Model Version 2 (CLM2) as its land component in order to make a better simulation of surface air temperature and precipitation on the seasonal time scale, which is important for crop model application. Climatological and seasonal simulations with the FSU climate model coupled to the CLM2 (hereafter FSUCLM) are compared to those of the control (the FSU model with the original simple land surface treatment). The current version of the FSU model is known to have a cold bias in the temperature field and a wet bias in precipitation. The implementation of FSUCLM has reduced or eliminated this bias due to reduced latent heat flux and increased sensible heat flux. The role of the land model in seasonal simulations is shown to be more important during summertime than wintertime. An additional experiment that assimilates atmospheric forcings produces improved land-model initial conditions, which in turn reduces the biases further. The impact of various deep convective parameterizations is examined as well to further assess model performance. The land scheme plays a more important role than the convective scheme in simulations of surface air temperature. However, each convective scheme shows its own advantage over different geophysical locations in precipitation simulations.

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 Diagnosis of Multiyear Predictability on Continental Scales

2011 ◽  
Vol 24 (19) ◽  
pp. 5108-5124 ◽  
Author(s):  
Liwei Jia ◽  
Timothy DelSole
Keyword(s):  
Time Scales ◽  
Air Temperature ◽  
Climate Models ◽  
Coupled Model ◽  
Surface Air Temperature ◽  
Optimization Method ◽  
First Year ◽  
Temperature And Precipitation ◽  
Regional Prediction ◽  
Intercomparison Project

A new statistical optimization method is used to identify components of surface air temperature and precipitation on six continents that are predictable in multiple climate models on multiyear time scales. The components are identified from unforced “control runs” of the Coupled Model Intercomparison Project phase 3 dataset. The leading predictable components can be calculated in independent control runs with statistically significant skill for 3–6 yr for surface air temperature and 1–3 yr for precipitation, depending on the continent, using a linear regression model with global sea surface temperature (SST) as a predictor. Typically, lag-correlation maps reveal that the leading predictable components of surface air temperature are related to two types of SST patterns: persistent patterns near the continent itself and an oscillatory ENSO-like pattern. The only exception is Europe, which has no significant ENSO relation. The leading predictable components of precipitation are significantly correlated with an ENSO-like SST pattern. No multiyear predictability of land precipitation could be verified in Europe. The squared multiple correlations of surface air temperature and precipitation for nonzero lags on each continent are less than 0.4 in the first year, implying that less than 40% of variations of the leading predictable component can be predicted from global SST. The predictable components describe the spatial structures that can be predicted on multiyear time scales in the absence of anthropogenic and natural forcing, and thus provide a scientific rationale for regional prediction on multiyear time scales.

scholarly journals Reanalysis of 44 Yr of Climate in the French Alps (1958–2002): Methodology, Model Validation, Climatology, and Trends for Air Temperature and Precipitation

2009 ◽  
Vol 48 (3) ◽  
pp. 429-449 ◽  
Author(s):  
Yves Durand ◽  
Martin Laternser ◽  
Gérald Giraud ◽  
Pierre Etchevers ◽  
Bernard Lesaffre ◽  
...  
Keyword(s):  
Air Temperature ◽  
Numerical Models ◽  
Surface Air Temperature ◽  
Positive Trend ◽  
Mountain Areas ◽  
Near Surface ◽  
French Alps ◽  
Mountainous Regions ◽  
Temperature And Precipitation ◽  
Analysis Scheme

Abstract Since the early 1990s, Météo-France has used an automatic system combining three numerical models to simulate meteorological parameters, snow cover stratification, and avalanche risk at various altitudes, aspects, and slopes for a number of mountainous regions in France. Given the lack of sufficient directly observed long-term snow data, this “SAFRAN”–Crocus–“MEPRA” (SCM) model chain, usually applied to operational avalanche forecasting, has been used to carry out and validate retrospective snow and weather climate analyses for the 1958–2002 period. The SAFRAN 2-m air temperature and precipitation climatology shows that the climate of the French Alps is temperate and is mainly determined by atmospheric westerly flow conditions. Vertical profiles of temperature and precipitation averaged over the whole period for altitudes up to 3000 m MSL show a relatively linear variation with altitude for different mountain areas with no constraint of that kind imposed by the analysis scheme itself. Over the observation period 1958–2002, the overall trend corresponds to an increase in the annual near-surface air temperature of about 1°C. However, variations are large at different altitudes and for different seasons and regions. This significantly positive trend is most obvious in the 1500–2000-m MSL altitude range, especially in the northwest regions, and exhibits a significant relationship with the North Atlantic Oscillation index over long periods. Precipitation data are diverse, making it hard to identify clear trends within the high year-to-year variability.

scholarly journals Impact of Atmospheric Blocking on South America in Austral Summer

2017 ◽  
Vol 30 (5) ◽  
pp. 1821-1837 ◽  
Author(s):  
Regina R. Rodrigues ◽  
Tim Woollings
Keyword(s):  
South America ◽  
Wave Train ◽  
Austral Summer ◽  
Surface Air Temperature ◽  
South Atlantic Convergence Zone ◽  
Atmospheric Blocking ◽  
Central Pacific ◽  
Temperature And Precipitation ◽  
The Indian Ocean

Abstract This study investigates atmospheric blocking over eastern South America in austral summer for the period of 1979–2014. The results show that blocking over this area is a consequence of propagating Rossby waves that grow to large amplitudes and eventually break anticyclonically over subtropical South America (SSA). The SSA blocking can prevent the establishment of the South Atlantic convergence zone (SACZ). As such, years with more blocking days coincide with years with fewer SACZ days and reduced precipitation. Convection mainly over the Indian Ocean associated with Madden–Julian oscillation (MJO) phases 1 and 2 can trigger the wave train that leads to SSA blocking whereas convection over the western/central Pacific associated with phases 6 and 7 is more likely to lead to SACZ events. It is found that the MJO is a key source of long-term variability in SSA blocking frequency. The wave packets associated with SSA blocking and SACZ episodes differ not only in their origin but also in their phase and refraction pattern. The tropopause-based methodology used here is proven to reliably identify events that lead to extremes of surface temperature and precipitation over SSA. Up to 80% of warm surface air temperature extremes occur simultaneously with SSA blocking events. The frequency of SSA blocking days is highly anticorrelated with the rainfall over southeast Brazil. The worst droughts in this area, during the summers of 1984, 2001, and 2014, are linked to record high numbers of SSA blocking days. The persistence of these events is also important in generating the extreme impacts.

scholarly journals Observed changes in surface air temperature and precipitation in the Hindu Kush Himalayan region over the last 100-plus years

2017 ◽  
Vol 8 (3) ◽  
pp. 148-156 ◽  
Author(s):  
Yu-Yu Ren ◽  
Guo-Yu Ren ◽  
Xiu-Bao Sun ◽  
Arun Bhakta Shrestha ◽  
Qing-Long You ◽  
...  
Keyword(s):  
Air Temperature ◽  
Surface Air Temperature ◽  
Himalayan Region ◽  
Temperature And Precipitation ◽  
Hindu Kush
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