Influence of Eurasian spring snowmelt on surface air temperature in late spring and early summer

2021 ◽  
pp. 1-45
Author(s):  
Juan Zhou ◽  
Zhiyan Zuo ◽  
Qiong He
Keyword(s):  
Soil Moisture ◽  
Air Temperature ◽  
Cloud Cover ◽  
Climate Models ◽  
Surface Air Temperature ◽  
Early Summer ◽  
Late Spring ◽  
Shortwave Radiation ◽  
Sensible Heat ◽  
Spring Snowmelt

AbstractThe effect of Eurasian spring snowmelt on surface air temperature (SAT) in late spring (April–May) and early summer (June–July) and the relevant physical mechanisms during 1981–2016 are investigated. Results show that the first mode of the inter-annual Eurasian spring snowmelt represents an east–west dipole anomaly pattern, with an intense center over Siberia and another moderate center around eastern Europe. The European spring snowmelt shows an insignificant relation to the local SAT, whereas the Siberian spring snowmelt has a significant impact on the SAT in late spring and early summer. More Siberian spring snowmelt contributes to higher SAT in late spring and lower SAT in early summer via different mechanisms. In late spring, increased Siberian spring snowmelt corresponds to less local surface albedo and cloud cover, leading to the surface absorbing more shortwave radiation and thereby higher SAT. The sub-surface and deep soil moisture anomalies generated from Siberian spring snowmelt can persist into early summer. Excessive Siberian spring snowmelt corresponds to positive soil moisture anomalies, contributing to decreased sensible heat and increased cloud cover in early summer. Increased cloud cover leads to the surface receiving less shortwave radiation. Thus, lower SAT appears over Siberia in early summer due to reduced sensible heat and shortwave radiation. However, the simulation of Eurasian spring snowmelt variability and its influences on SAT via the snow hydrological effect is still a challenge for the climate models that participated in the Coupled Model Intercomparison Project phase 6.

scholarly journals Numerical Simulations of Effects of Soil Moisture and Modification by Mountains over New Zealand in Summer

2011 ◽  
Vol 139 (2) ◽  
pp. 494-510 ◽  
Author(s):  
Yang Yang ◽  
Michael Uddstrom ◽  
Mike Revell ◽  
Phil Andrews ◽  
Hilary Oliver ◽  
...  
Keyword(s):  
Soil Moisture ◽  
New Zealand ◽  
Moisture Content ◽  
Air Temperature ◽  
Land Surface ◽  
Soil Moisture Content ◽  
Surface Air Temperature ◽  
Shortwave Radiation ◽  
Lower Sensitivity ◽  
The South

Abstract Historically most soil moisture–land surface impact studies have focused on continents because of the important forecasting and climate implications involved. For a relatively small isolated mountainous landmass in the ocean such as New Zealand, these impacts have received less attention. This paper addresses some of these issues for New Zealand through numerical experiments with a regional configuration of the Met Office Unified Model atmospheric model. Two pairs of idealized simulations with only contrasting dry or wet initial soil moisture over a 6-day period in January 2004 were conducted, with one pair using realistic terrain and the other pair flat terrain. For the mean of the 6 days, the differences in the simulated surface air temperature between the dry and moist cases were 3–5 K on the leeside slopes and 1–2 K on the windward slopes and the central leeside coastal region of the South Island in the afternoon. This quite nonuniform response in surface air temperature to a uniformly distributed soil moisture content and soil type is mainly attributed to modification of the effects of soil moisture by mountains through two different processes: 1) spatial variation in cloud coverage across the mountains ranges leading to more shortwave radiation at ground surface on the leeside slope than the windward slope, and 2) the presence of a dynamically and thermally induced onshore flow on the leeside coast bringing in air with a lower sensitivity to soil moisture. The response of local winds to soil moisture content is through direct or indirect effects. The direct effect is due to the thermal contrast between land and sea/land shown for the leeside solenoidal circulations, and the indirect effect is through the weakening of the upstream blocking of the South Island for dryer soils shown by the weakening and onshore shift of the upstream deceleration and forced ascent of incoming airflow.

scholarly journals Modulation of summer monsoon sub-seasonal surface air temperature over India by soil moisture-temperature coupling

MAUSAM ◽  
2021 ◽  
Vol 67 (1) ◽  
pp. 53-66
Author(s):  
M. V. S. RAMARAO ◽  
J. SANJAY ◽  
R. KRISHNAN
Keyword(s):  
Soil Moisture ◽  
Air Temperature ◽  
Summer Monsoon ◽  
Climate Models ◽  
Monsoon Season ◽  
Surface Air Temperature ◽  
Monsoon Precipitation ◽  
Summer Monsoon Season ◽  
Weather And Climate ◽  
Dry Soil

The influence of soil moisture on the sub-seasonal warmer surface air temperature anomalies during drier soil conditions associated with break spells in the Indian summer monsoon precipitation is explored using observations.  The multi-model analysis of land surface states and fluxes available from the Second Global Soil Wetness Project (GSWP-2) are found useful in understanding the mechanism for this soil moisture-temperature coupling on sub-seasonal timescales. The analysis uses a soil moisture-temperature coupling diagnostic computed based on linear correlations of daily fields. It is shown that the summer surface air temperature variations are linked to intraseasonal variations of the Indian monsoon precipitation, which control the land-climate coupling by modulating the soil moisture variations. Strong coupling mainly occurs during dry soil states within the summer monsoon season over the transition zones between wet and dry climates of central to north-west India. In contrast, the coupling is weak for constantly wet and energy-limited evaporative regimes over eastern India during the entire summer monsoon season. This observational based analysis provided a better understanding of the linkages between the sub-seasonal dry soil states and warm conditions during the Indian summer monsoon season. A proper representation of these aspects of land-atmosphere interactions in weather and climate models used for sub-seasonal and seasonal monsoon forecasting could be critical for several applications, in particular agriculture. The soil moisture-temperature coupling diagnostic used in this study will be a useful metric for evaluating the performance of weather and climate models.

Modeled Climate Responses to Realistic Extremes of Northern Hemisphere Spring and Summer Snow Anomalies

2020 ◽  
Vol 33 (22) ◽  
pp. 9905-9927
Author(s):  
Shizuo Liu ◽  
Qigang Wu ◽  
Lin Wang ◽  
Steven R. Schroeder ◽  
Yang Zhang ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Snow Cover ◽  
Northern Hemisphere ◽  
Climate Models ◽  
Snow Water Equivalent ◽  
Surface Air Temperature ◽  
Early Summer ◽  
The Arctic ◽  
Snow Cover Extent ◽  
Climate Responses

AbstractNorthern Hemisphere (NH) snow cover extent (SCE) has diminished in spring and early summer since the 1960s. Historical simulations from phase 5 of the Coupled Model Intercomparison Project (CMIP5) estimated about half as much NH SCE reduction as observed, and thus underestimated the associated climate responses. This study investigates atmospheric responses to realistic decreasing snow anomalies using multiple ensemble transient integrations of climate models forced by observed light and heavy NH snow cover years, specifically satellite-based observations of NH SCE and snow water equivalent from March to August in 1990 (light snow) and 1985 (heavy snow), as a proxy for the trend. The primary atmospheric responses to March–August NH snow reduction are decreased soil moisture, increased surface air temperature, general tropospheric warming in the extratropics and the Arctic, increased geopotential heights, and weakening of the midlatitude jet stream and eddy kinetic energy. The localized response is maintained by persistent increased diabatic heating due to reduced snow anomalies and resulting soil moisture drying, and the remote atmospheric response results partly from horizontal propagation of stationary Rossby wave energy and also from a transient eddy feedback mechanism. In summer, atmospheric responses are significant in both the Arctic and the tropics and are mostly induced by contemporaneous snow forcing, but also by the summer soil moisture dry anomaly associated with early snow melting.

scholarly journals Evaluation and Comparison of Noah and Pleim–Xiu Land Surface Models in MM5 Using GÖTE2001 Data: Spatial and Temporal Variations in Near-Surface Air Temperature

2007 ◽  
Vol 46 (10) ◽  
pp. 1587-1605 ◽  
Author(s):  
J-F. Miao ◽  
D. Chen ◽  
K. Borne
Keyword(s):  
Soil Moisture ◽  
Air Temperature ◽  
Land Surface ◽  
Model Performance ◽  
Surface Air Temperature ◽  
Near Surface ◽  
Surface Models ◽  
Urban Heat ◽  
Soil Moisture Initialization ◽  
Evident Difference

Abstract In this study, the performance of two advanced land surface models (LSMs; Noah LSM and Pleim–Xiu LSM) coupled with the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5), version 3.7.2, in simulating the near-surface air temperature in the greater Göteborg area in Sweden is evaluated and compared using the GÖTE2001 field campaign data. Further, the effects of different planetary boundary layer schemes [Eta and Medium-Range Forecast (MRF) PBLs] for Noah LSM and soil moisture initialization approaches for Pleim–Xiu LSM are investigated. The investigation focuses on the evaluation and comparison of diurnal cycle intensity and maximum and minimum temperatures, as well as the urban heat island during the daytime and nighttime under the clear-sky and cloudy/rainy weather conditions for different experimental schemes. The results indicate that 1) there is an evident difference between Noah LSM and Pleim–Xiu LSM in simulating the near-surface air temperature, especially in the modeled urban heat island; 2) there is no evident difference in the model performance between the Eta PBL and MRF PBL coupled with the Noah LSM; and 3) soil moisture initialization is of crucial importance for model performance in the Pleim–Xiu LSM. In addition, owing to the recent release of MM5, version 3.7.3, some experiments done with version 3.7.2 were repeated to reveal the effects of the modifications in the Noah LSM and Pleim–Xiu LSM. The modification to longwave radiation parameterizations in Noah LSM significantly improves model performance while the adjustment of emissivity, one of the vegetation properties, affects Pleim–Xiu LSM performance to a larger extent. The study suggests that improvements both in Noah LSM physics and in Pleim–Xiu LSM initialization of soil moisture and parameterization of vegetation properties are important.

Evaluating temperature extremes in CMIP6 simulations using statistically proper evaluation methods

2021 ◽  
Author(s):  
Thordis Thorarinsdottir ◽  
Jana Sillmann ◽  
Marion Haugen ◽  
Nadine Gissibl ◽  
Marit Sandstad
Keyword(s):  
Air Temperature ◽  
Model Evaluation ◽  
Climate Models ◽  
Climate Model ◽  
Mean Squared Error ◽  
Surface Air Temperature ◽  
Cmip5 Models ◽  
Model Output ◽  
Intergovernmental Panel ◽  
Near Surface

<p>Reliable projections of extremes in near-surface air temperature (SAT) by climate models become more and more important as global warming is leading to significant increases in the hottest days and decreases in coldest nights around the world with considerable impacts on various sectors, such as agriculture, health and tourism.</p><p>Climate model evaluation has traditionally been performed by comparing summary statistics that are derived from simulated model output and corresponding observed quantities using, for instance, the root mean squared error (RMSE) or mean bias as also used in the model evaluation chapter of the fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5). Both RMSE and mean bias compare averages over time and/or space, ignoring the variability, or the uncertainty, in the underlying values. Particularly when interested in the evaluation of climate extremes, climate models should be evaluated by comparing the probability distribution of model output to the corresponding distribution of observed data.</p><p>To address this shortcoming, we use the integrated quadratic distance (IQD) to compare distributions of simulated indices to the corresponding distributions from a data product. The IQD is the proper divergence associated with the proper continuous ranked probability score (CRPS) as it fulfills essential decision-theoretic properties for ranking competing models and testing equality in performance, while also assessing the full distribution.</p><p>The IQD is applied to evaluate CMIP5 and CMIP6 simulations of monthly maximum (TXx) and minimum near-surface air temperature (TNn) over the data-dense regions Europe and North America against both observational and reanalysis datasets. There is not a notable difference between the model generations CMIP5 and CMIP6 when the model simulations are compared against the observational dataset HadEX2. However, the CMIP6 models show a better agreement with the reanalysis ERA5 than CMIP5 models, with a few exceptions. Overall, the climate models show higher skill when compared against ERA5 than when compared against HadEX2. While the model rankings vary with region, season and index, the model evaluation is robust against changes in the grid resolution considered in the analysis.</p>

scholarly journals A Study of the Surface Air Temperature Variations in Nigeria

2017 ◽  
Vol 11 (1) ◽  
pp. 54-70 ◽  
Author(s):  
Najib Yusuf ◽  
Daniel Okoh ◽  
Ibrahim Musa ◽  
Samson Adedoja ◽  
Rabia Said
Keyword(s):  
Air Temperature ◽  
Cloud Cover ◽  
Coastal Region ◽  
Surface Air Temperature ◽  
The South ◽  
Climate Type ◽  
Temperature Variations ◽  
North Central ◽  
North East ◽  
The North

Background: Simultaneous measurements of air temperature were carried out using automatic weather stations at 14 tropical locations in Nigeria. Diurnal variations were derived from the 5-minute update cycle initial data for the years ranging between 2007 and 2013. The temperature trends in Nigeria revealed a continuous variability that is seasonally dependent within any particular year considered. Method: The analysis was carried out using available data from the network and the results are presented with a focus to characterize the temperature variations at different locations in the country using the mean, maximum and minimum temperatures from the north which is arid in nature to the south, which is a tropical monsoon climate type and a coastal region. Result: In overall, temperature variations in Nigeria were observed to have higher values in the far north, attributed to the influence of Sahara Desert, which has less cloud cover and therefore is more transparent to solar irradiance and lowers values in the south, where there are more cloud cover and abundant vegetation. Conclusion: Measured maximum and minimum temperatures in Nigeria are respectively 43.1°C at Yola (north-east part of Nigeria) and 10.2°C for Jos (north-central part of Nigeria). The least temperature variations were recorded for stations in the southern part of the country, while the largest variations were recorded in the north-central region of the country.

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 Compost and soil moisture effects on seasonal carbon and nitrogen dynamics, greenhouse gas fluxes and global warming potential of semi-arid soils

2019 ◽  
Vol 8 (S1) ◽  
pp. 367-376 ◽  
Author(s):  
Mavis Badu Brempong ◽  
Urszula Norton ◽  
Jay B. Norton
Keyword(s):  
Global Warming ◽  
Soil Moisture ◽  
Global Warming Potential ◽  
Carbon Dioxide Emissions ◽  
Inorganic Nitrogen ◽  
Early Summer ◽  
Late Spring ◽  
Late Winter ◽  
Normal Soil ◽  
Soil Inorganic

Abstract Purpose An 8-week incubation study was conducted to monitor soil inorganic nitrogen (N), dissolved organic carbon (DOC), greenhouse gases (GHG) [CO2, N2O and CH4] and cumulative global warming potential (GWP) in dryland soil. Methods Soil was amended with variable rates of compost (zero, 15, 30 and 45 dry Mg ha−1) and soil moistures [5% (dry), 7% (normal) and 14% (wet) water filled pore space (WFPS)] and experienced biweekly temperature transitions from 5 °C (late winter) to 10 °C (early spring) to 15 °C (late spring) to 25 °C (early summer). Results The addition of 30 and 45 Mg ha−1 compost enhanced N mineralization with 13% more soil inorganic N (7.49 and 7.72 µg Ng−1 day−1, respectively) during early summer compared with lower compost rates. Normal and wet soils had 35% more DOC in the late spring (an average of 34 µg g−1 day−1) compared to the dry WFPS, but transitioning from late spring to early summer, DOC at all soil WFPS levels increased. Highest rates of compost were not significant sources of GHG with normal soil WFPS, compared with lower compost rates. Carbon dioxide emissions increased by 59 and 15%, respectively, as soil WFPS increased from dry to normal and normal to wet. Soils with normal WFPS were the most effective CH4 sink. Conclusion One-time application of high compost rates to dryland soils leads to enhanced N and C mineralization under normal soil moisture and warmer temperature of the summer but will not pose significant global warming dangers to the environment through GHG emissions since soils are rarely wet.

scholarly journals Spatiotemporal Characteristics of the Dominant Modes of Surface Air Temperature Interannual Variations over South China during the Spring-to-Summer Transition

Atmosphere ◽  
2019 ◽  
Vol 10 (2) ◽  
pp. 65
Author(s):  
Fen Wang ◽  
Yaokun Li ◽  
Jianping Li
Keyword(s):  
Heat Flux ◽  
Air Temperature ◽  
South China ◽  
Surface Heat Flux ◽  
Surface Air Temperature ◽  
Surface Heat ◽  
Shortwave Radiation ◽  
Northerly Wind ◽  
The North ◽  
Land Surfaces

The surface air temperature (SAT) interannual variability during the spring-to-summer transition over South China (SC) has been decomposed into two dominant modes by applying empirical orthogonal function (EOF) analysis. The first EOF mode (EOF1) is characterized by homogenous SAT anomalies over SC, whereas the second EOF mode (EOF2) features a dipole SAT anomaly pattern with opposite anomalies south and north of the Yangtze River. A regression analysis of surface heat flux and advection anomalies on the normalized principle component time series corresponding to EOF1 suggests that surface heat flux anomalies can explain SAT anomalies mainly by modulating cloud-shortwave radiation. Negative cloud anomalies result in positive downward shortwave radiation anomalies through the positive shortwave cloud radiation effect, which favor warm SAT anomalies over most of SC. For EOF2, the distribution of advection anomalies resembles the north–south dipole pattern of SAT anomalies. This suggests that wind-induced advection plays an important role in the SAT anomalies of EOF2. Negative SAT anomalies are favored by cold advection from northerly wind anomalies over land surfaces in high-latitude regions. Positive SAT anomalies are induced by warm advection from southerly wind anomalies over the ocean in low-latitude regions.

scholarly journals Analysis of the decrease in the tropical mean outgoing shortwave radiation at the top of atmosphere for the period 1984-2000

2005 ◽  
Vol 5 (6) ◽  
pp. 1721-1730 ◽  
Author(s):  
A. Fotiadi ◽  
N. Hatzianastassiou ◽  
C. Matsoukas ◽  
K. G. Pavlakis ◽  
E. Drakakis ◽  
...  
Keyword(s):  
Cloud Cover ◽  
Climate Models ◽  
Climate Model ◽  
Shortwave Radiation ◽  
Radiative Energy ◽  
Radiative Transfer Model ◽  
Physical Parameters ◽  
Transfer Model ◽  
Monthly Basis ◽  
Decadal Scale

Abstract. A decadal-scale trend in the tropical radiative energy budget has been observed recently by satellites, which however is not reproduced by climate models. In the present study, we have computed the outgoing shortwave radiation (OSR) at the top of atmosphere (TOA) at 2.5° longitude-latitude resolution and on a mean monthly basis for the 17-year period 1984-2000, by using a deterministic solar radiative transfer model and cloud climatological data from the International Satellite Cloud Climatology Project (ISCCP) D2 database. Anomaly time series for the mean monthly pixel-level OSR fluxes, as well as for the key physical parameters, were constructed. A significant decreasing trend in OSR anomalies, starting mainly from the late 1980s, was found in tropical and subtropical regions (30° S-30° N), indicating a decadal increase in solar planetary heating equal to 1.9±0.3Wm-2/decade, reproducing well the features recorded by satellite observations, in contrast to climate model results. This increase in solar planetary heating, however, is accompanied by a similar increase in planetary cooling, due to increased outgoing longwave radiation, so that there is no change in net radiation. The model computed OSR trend is in good agreement with the corresponding linear decadal decrease of 2.5±0.4Wm-2/decade in tropical mean OSR anomalies derived from ERBE S-10N non-scanner data (edition 2). An attempt was made to identify the physical processes responsible for the decreasing trend in tropical mean OSR. A detailed correlation analysis using pixel-level anomalies of model computed OSR flux and ISCCP cloud cover over the entire tropical and subtropical region (30° S-30° N), gave a correlation coefficient of 0.79, indicating that decreasing cloud cover is the main reason for the tropical OSR trend. According to the ISCCP-D2 data derived from the combined visible/infrared (VIS/IR) analysis, the tropical cloud cover has decreased by 6.6±0.2% per decade, in relative terms. A detailed analysis of the inter-annual and long-term variability of the various parameters determining the OSR at TOA, has shown that the most important contribution to the observed OSR trend comes from a decrease in low-level cloud cover over the period 1984-2000, followed by decreases in middle and high-level cloud cover. Note, however, that there still remain some uncertainties associated with the existence and magnitude of trends in ISCCP-D2 cloud amounts. Opposite but small trends are introduced by increases in cloud scattering optical depth of low and middle clouds.

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