scholarly journals Understanding Land-Atmosphere-Climate Coupling from the Canadian Prairie Dataset

2018 ◽  
Author(s):  
Alan K Betts ◽  
Raymond L Desjardins
Keyword(s):  
Snow Cover ◽  
Diurnal Cycle ◽  
Radiative Forcing ◽  
Potential Temperature ◽  
Warm Season ◽  
Growing Season ◽  
Cold Season ◽  
Maximum Temperature ◽  
Canadian Prairie ◽  
Cloud Forcing

Analysis of the hourly Canadian Prairie data for the past 60 years has transformed our quantitative understanding of land-atmosphere-cloud coupling. The key reason is that trained observers made hourly estimates of opaque cloud fraction that obscures the sun, moon or stars, following the same protocol for 60 years at all stations. These 24 daily estimates of opaque cloud data are of sufficient quality that they can be calibrated against Baseline Surface Radiation Network data to give the climatology of the daily short-wave, longwave and total cloud forcing (SWCF, LWCF and CF). This key radiative forcing has not been available previously for climate datasets. Net cloud radiative forcing reverses sign from negative in the warm season to positive in the cold season, when reflective snow reduces the negative SWCF below the positive LWCF. This in turn leads to a large climate discontinuity with snow cover, with a systematic cooling of 10°C or more with snow cover. In addition, snow cover transforms the coupling between cloud cover and the diurnal range of temperature. In the warm season, maximum temperature increases with decreasing cloud, while minimum temperature barely changes; while in the cold season with snow cover, maximum temperature decreases with decreasing cloud and minimum temperature decreases even more. In the warm season, the diurnal ranges of temperature, relative humidity, equivalent potential temperature and the pressure height of the lifting condensation level are all tightly coupled to opaque cloud cover. Given over 600 station-years of hourly data, we are able to extract, perhaps for the first time, the coupling between cloud forcing and the warm season imbalance of the diurnal cycle; which changes monotonically from a warming and drying under clear skies to a cooling and moistening under cloudy skies with precipitation. Because we have the daily cloud radiative forci, which is large, we are able to show that the memory of water storage anomalies, from precipitation and the snowpack, goes back many months. The spring climatology shows the memory of snowfall back through the entire winter, and the memory in summer goes back to the months of snowmelt. Lagged precipitation anomalies modify the thermodynamic coupling of the diurnal cycle to the cloud forcing, and shift the diurnal cycle of mixing ratio which has a double peak. The seasonal extraction of the surface total water storage is a large damping of the interannual variability of precipitation anomalies in the growing season. The large land-use change from summer fallow to intensive cropping, which peaked in the early 1990s, has led to a coupled climate response that has cooled and moistened the growing season, lowering cloud-base, increasing equivalent potential temperature, and increasing precipitation. We show a simplified energy balance of the Prairies during the growing season and its dependence on reflective cloud.

scholarly journals Understanding Land–Atmosphere–Climate Coupling from the Canadian Prairie Dataset

Environments ◽  
2018 ◽  
Vol 5 (12) ◽  
pp. 129 ◽  
Author(s):  
Alan Betts ◽  
Raymond Desjardins
Keyword(s):  
Snow Cover ◽  
Diurnal Cycle ◽  
Radiative Forcing ◽  
Potential Temperature ◽  
Warm Season ◽  
Growing Season ◽  
Cold Season ◽  
Maximum Temperature ◽  
Canadian Prairie ◽  
Cloud Forcing

Analysis of the hourly Canadian Prairie data for the past 60 years has transformed our quantitative understanding of land–atmosphere–cloud coupling. The key reason is that trained observers made hourly estimates of the opaque cloud fraction that obscures the sun, moon, or stars, following the same protocol for 60 years at all stations. These 24 daily estimates of opaque cloud data are of sufficient quality such that they can be calibrated against Baseline Surface Radiation Network data to yield the climatology of the daily short-wave, long-wave, and total cloud forcing (SWCF, LWCF and CF, respectively). This key radiative forcing has not been available previously for climate datasets. Net cloud radiative forcing changes sign from negative in the warm season, to positive in the cold season, when reflective snow reduces the negative SWCF below the positive LWCF. This in turn leads to a large climate discontinuity with snow cover, with a systematic cooling of 10 °C or more with snow cover. In addition, snow cover transforms the coupling between cloud cover and the diurnal range of temperature. In the warm season, maximum temperature increases with decreasing cloud, while minimum temperature barely changes; while in the cold season with snow cover, maximum temperature decreases with decreasing cloud, and minimum temperature decreases even more. In the warm season, the diurnal ranges of temperature, relative humidity, equivalent potential temperature, and the pressure height of the lifting condensation level are all tightly coupled to the opaque cloud cover. Given over 600 station-years of hourly data, we are able to extract, perhaps for the first time, the coupling between the cloud forcing and the warm season imbalance of the diurnal cycle, which changes monotonically from a warming and drying under clear skies to a cooling and moistening under cloudy skies with precipitation. Because we have the daily cloud radiative forcing, which is large, we are able to show that the memory of water storage anomalies, from precipitation and the snowpack, goes back many months. The spring climatology shows the memory of snowfall back through the entire winter, and the memory in summer, goes back to the months of snowmelt. Lagged precipitation anomalies modify the thermodynamic coupling of the diurnal cycle to the cloud forcing, and shift the diurnal cycle of the mixing ratio, which has a double peak. The seasonal extraction of the surface total water storage is a large damping of the interannual variability of precipitation anomalies in the growing season. The large land-use change from summer fallow to intensive cropping, which peaked in the early 1990s, has led to a coupled climate response that has cooled and moistened the growing season, lowering cloud-base, increasing equivalent potential temperature, and increasing precipitation. We show a simplified energy balance of the Prairies during the growing season, and its dependence on reflective cloud.

scholarly journals Diurnal Cycle of Convective Instability around the Central Mountains in Japan during the Warm Season

2005 ◽  
Vol 62 (5) ◽  
pp. 1626-1636 ◽  
Author(s):  
Tomonori Sato ◽  
Fujio Kimura
Keyword(s):  
Water Vapor ◽  
Diurnal Cycle ◽  
Convective Instability ◽  
Potential Temperature ◽  
Warm Season ◽  
Precipitable Water ◽  
Specific Humidity ◽  
High Temporal Resolution ◽  
Mountainous Areas ◽  
Diurnal Cycles

Abstract Convective rainfall often shows a clear diurnal cycle. The nighttime peak of convective activity prevails in various regions near the world's mountains. The influence of the water vapor and convective instability upon nocturnal precipitation is investigated using a numerical model and observed data. Recent developments in GPS meteorology allow the estimation of precipitable water vapor (PWV) with a high temporal resolution. A dense network has been established in Japan. The GPS analysis in August 2000 provides the following results: In the early evening, a high-GPS-PWV region forms over mountainous areas because of the convergence of low-level moisture, which gradually propagates toward the adjacent plain before midnight. A region of convection propagates simultaneously eastward into the plain. The precipitating frequency correlates fairly well with the GPS-PWV and attains a maximum value at night over the plain. The model also provides similar characteristics in the diurnal cycles of rainfall and high PWV. Abundant moisture accumulates over the mountainous areas in the afternoon and then advects continuously toward the plain by the ambient wind. The specific humidity greatly increases at about the 800-hPa level over the plain at night, and the PWV reaches its nocturnal maximum. The increase in the specific humidity causes an increase of equivalent potential temperature at about the 800-hPa level; as a result, the convective instability index becomes more unstable over the plain at night. These findings are consistent with the diurnal cycle of the observed precipitating frequency.

scholarly journals Teleconnections between Snow Cover Change over Siberia and Crop Growth in Northeast China

2020 ◽  
Vol 12 (18) ◽  
pp. 7632
Author(s):  
Cong Guan ◽  
Lingxue Yu ◽  
Fengqin Yan ◽  
Shuwen Zhang
Keyword(s):  
Snow Cover ◽  
Northeast China ◽  
Vegetation Index ◽  
Regional Climate ◽  
Growing Season ◽  
Crop Growth ◽  
Maximum Temperature ◽  
Satellite Measurement ◽  
Agricultural Ecosystem ◽  
Snow Cover Area

Snow cover is a sensitive indicator of climate change, and the variations in snow cover can influence the global climate system and terrestrial water cycling. However, the teleconnections between snow cover changes of the northern hemisphere and the crop growth of Northeast China (NEC) are less documented. In this study, we estimated the correlations between spring snow cover area over Siberia (SSCA) and the regional climate, as well as the crop growth in NEC based on both satellite measurement and observational climate records from 1982 to 2015. The local temperature, including minimum temperature (Tmin) in May–June, maximum temperature (Tmax), and Tmin in July–August, showed significant negative correlations with SSCA. SSCA is found to be negatively correlated to rainfall during the beginning of the growing season, while positively correlated to rainfall during the peak growing season for the agricultural ecosystem of NEC. The remote responses of the normalized difference vegetation index (NDVI) to SSCA varied across different climate zones and different growing periods. The NDVI variations over cold and dry cultivated regions exhibit negative correlations with SSCA in May–June, which is opposite for the wetter areas. The negative correlation between NDVI over the agricultural ecosystem and SSCA during the peak growing season was also detected, implying the variations in SSCA might be an essential driving factor in affecting the crop growth through modifying the regional climate of NEC. In the future, more in situ observations and model simulations should be conducted to verify our results described here, which would have significant implications for maintaining regional food security and sustainable development in Northeast China under the changing climate background.

scholarly journals Characterizing Recent Trends in U.S. Heavy Precipitation

2016 ◽  
Vol 29 (7) ◽  
pp. 2313-2332 ◽  
Author(s):  
Martin Hoerling ◽  
Jon Eischeid ◽  
Judith Perlwitz ◽  
Xiao-Wei Quan ◽  
Klaus Wolter ◽  
...  
Keyword(s):  
United States ◽  
Radiative Forcing ◽  
Daily Precipitation ◽  
Warm Season ◽  
Heavy Precipitation ◽  
Cold Season ◽  
Tropical Eastern Pacific ◽  
Climate Simulations ◽  
Daily Events ◽  
Northern United States

Abstract Time series of U.S. daily heavy precipitation (95th percentile) are analyzed to determine factors responsible for regionality and seasonality in their 1979–2013 trends. For annual conditions, contiguous U.S. trends have been characterized by increases in precipitation associated with heavy daily events across the northern United States and decreases across the southern United States. Diagnosis of climate simulations (CCSM4 and CAM4) reveals that the evolution of observed sea surface temperatures (SSTs) was a more important factor influencing these trends than boundary condition changes linked to external radiative forcing alone. Since 1979, the latter induces widespread, but mostly weak, increases in precipitation associated with heavy daily events. The former induces a meridional pattern of northern U.S. increases and southern U.S. decreases as observed, the magnitude of which closely aligns with observed changes, especially over the south and far west. Analysis of model ensemble spread reveals that appreciable 35-yr trends in heavy daily precipitation can occur in the absence of forcing, thereby limiting detection of the weak anthropogenic influence at regional scales. Analysis of the seasonality in heavy daily precipitation trends supports physical arguments that their changes during 1979–2013 have been intimately linked to internal decadal ocean variability and less so to human-induced climate change. Most of the southern U.S. decrease has occurred during the cold season that has been dynamically driven by an atmospheric circulation reminiscent of teleconnections linked to cold tropical eastern Pacific SSTs. Most of the northeastern U.S. increase has been a warm season phenomenon, the immediate cause for which remains unresolved.

scholarly journals Characteristics of extratropical cyclones and precursors to windstorms in Northern Europe

2021 ◽  
Author(s):  
Terhi K. Laurila ◽  
Hilppa Gregow ◽  
Joona Cornér ◽  
Victoria A. Sinclair
Keyword(s):  
Potential Temperature ◽  
Storm Track ◽  
Warm Season ◽  
Cold Season ◽  
Northern Europe ◽  
Annual Number ◽  
Extratropical Cyclones ◽  
Maximum Wind ◽  
The North ◽  
Wind Gusts

Abstract. Extratropical cyclones play a major role in the atmospheric circulation, weather variability and can cause damage to society. Extratropical cyclones in Northern Europe, which is located at the end of the North Atlantic storm track, have been less studied than extratropical cyclones elsewhere. Our study investigates extratropical cyclones and windstorms in Northern Europe (which in this study covers Norway, Sweden, Finland, Estonia and parts of the Baltic, Norwegian and Barents Seas) by analysing their characteristics, spatial and temporal evolution and precursors. We examine cold and warm seasons separately to determine seasonal differences. We track all extratropical cyclones in Northern Europe, create cyclone composites and use an ensemble sensitivity method to analyse the precursors. The ensemble sensitivity analysis is a novel method in cyclone studies where linear regression is used to statistically identify what variables possibly influence the subsequent evolution of extratropical cyclones. We investigate windstorm precursors for both the minimum mean sea level pressure (MSLP) and for the maximum 10-m wind gusts. The annual number of extratropical cyclones and windstorms have a large inter-annual variability and no significant linear trends during 1980–2019. Windstorms originate and occur over the Barents and Norwegian Seas whereas weaker extratropical cyclones originate and occur over land areas in Northern Europe. During the windstorm evolution, the maximum wind gusts move from the warm sector to behind the cold front following the strongest pressure gradient. Windstorms in both seasons are located on the poleward side of the jet stream. The maximum wind gusts occur nearly at the same time than the minimum MSLP occurs. The cold season windstorms have higher sensitivities and thus are potentially better predictable than warm season windstorms, and the minimum MSLP has higher sensitivities than the maximum wind gusts. Of the four examined precursors, both the minimum MSLP and the maximum wind gusts are the most sensitive to the 850-hPa potential temperature anomaly i.e. the temperature gradient. Hence, this parameter is likely important when predicting windstorms in Northern Europe.

scholarly journals Characteristics of extratropical cyclones and precursors to windstorms in northern Europe

2021 ◽  
Vol 2 (4) ◽  
pp. 1111-1130
Author(s):  
Terhi K. Laurila ◽  
Hilppa Gregow ◽  
Joona Cornér ◽  
Victoria A. Sinclair
Keyword(s):  
Potential Temperature ◽  
Storm Track ◽  
Warm Season ◽  
Cold Season ◽  
Northern Europe ◽  
Annual Number ◽  
Extratropical Cyclones ◽  
Maximum Wind ◽  
The North ◽  
Wind Gusts

Abstract. Extratropical cyclones play a major role in the atmospheric circulation and weather variability and can cause widespread damage and destruction. Extratropical cyclones in northern Europe, which is located at the end of the North Atlantic storm track, have been less studied than extratropical cyclones elsewhere. Our study investigates extratropical cyclones and windstorms in northern Europe (which in this study covers Norway; Sweden; Finland; Estonia; and parts of the Baltic, Norwegian, and Barents seas) by analysing their characteristics, spatial and temporal evolution, and precursors. We examine cold and warm seasons separately to determine seasonal differences. We track all extratropical cyclones in northern Europe, create cyclone composites, and use an ensemble sensitivity method to analyse the precursors. The ensemble sensitivity analysis is a novel method in cyclone studies where linear regression is used to statistically identify what variables possibly influence the subsequent evolution of extratropical cyclones. We investigate windstorm precursors for both the minimum mean sea level pressure (MSLP) and for the maximum 10 m wind gusts. The annual number of extratropical cyclones and windstorms has a large inter-annual variability and no significant linear trends during 1980–2019. Windstorms originate and occur over the Barents and Norwegian seas, whereas weaker extratropical cyclones originate and occur over land areas in northern Europe. During the windstorm evolution, the maximum wind gusts move from the warm sector to behind the cold front following the strongest pressure gradient. Windstorms in both seasons are located on the poleward side of the jet stream. The maximum wind gusts occur nearly at the same time as the minimum MSLP occurs. The cold-season windstorms have higher sensitivities and thus are potentially better predictable than warm-season windstorms, and the minimum MSLP has higher sensitivities than the maximum wind gusts. Of the four examined precursors, both the minimum MSLP and the maximum wind gusts are the most sensitive to the 850 hPa potential temperature anomaly, i.e. the temperature gradient. Hence, this parameter is likely important when predicting windstorms in northern Europe.

Revisiting Hydrometeorology Using Cloud and Climate Observations

2017 ◽  
Vol 18 (4) ◽  
pp. 939-955 ◽  
Author(s):  
Alan K. Betts ◽  
Ahmed B. Tawfik ◽  
Raymond L. Desjardins
Keyword(s):  
Climate Models ◽  
Potential Temperature ◽  
Warm Season ◽  
Monthly Precipitation ◽  
Mixing Ratio ◽  
Climate Data ◽  
Canadian Prairie ◽  
Near Surface ◽  
Mean Temperature ◽  
Precipitation Anomalies

Abstract This paper uses 620 station years of hourly Canadian Prairie climate data to analyze the coupling of monthly near-surface climate with opaque cloud, a surrogate for radiation, and precipitation anomalies. While the cloud–climate coupling is strong, precipitation anomalies impact monthly climate for as long as 5 months. The April climate has memory of precipitation anomalies back to freeze-up in November, mostly stored in the snowpack. The summer climate has memory of precipitation anomalies back to the beginning of snowmelt in March. In the warm season, mean temperature is strongly correlated to opaque cloud anomalies, but only weakly to precipitation anomalies. Mixing ratio anomalies are correlated to precipitation, but only weakly to cloud. The diurnal cycle of mixing ratio shifts upward with increasing precipitation anomalies. Positive precipitation anomalies are coupled to a lower afternoon lifting condensation level and a higher afternoon equivalent potential temperature; both favor increased convection and precipitation. Regression coefficients on precipitation increase from wet to dry conditions. This is consistent with increased uptake of soil water when monthly precipitation is low, until drought conditions are reached, and also consistent with gravity satellite observations. Regression analysis shows monthly opaque cloud cover is tightly correlated to three climate variables that are routinely observed: diurnal temperature range, mean temperature, and mean relative humidity. The set of correlation coefficients, derived from cloud and climate observations, could be used to evaluate the representation of the land–cloud–atmosphere system in both forecast and climate models.

Spatial and temporal characteristics in streamflow-related hydroclimatic variables over western Canada. Part 1: 1950–2010

2016 ◽  
Vol 48 (4) ◽  
pp. 915-931 ◽  
Author(s):  
H. C. L. O'Neil ◽  
T. D. Prowse ◽  
B. R. Bonsal ◽  
Y. B. Dibike
Keyword(s):  
Warm Season ◽  
Cold Season ◽  
Snow Accumulation ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Western Canada ◽  
Spring Freshet ◽  
Hydroclimatic Variables

A large portion of the freshwater in western Canada originates as snowpack from the northern Rocky Mountains. Temperature and precipitation in the region control the amount of snow accumulated and stored throughout the winter, and the intensity and timing of melt during the spring freshet. Therefore, trends in temperature, precipitation, snow accumulation, and snowmelt over western Canada are examined using the Mann-Kendall non-parametric test and an original geographic information system (GIS)-based approach to trend analysis on a newly produced high-resolution gridded climate dataset for the period 1950–2010. Temporal and spatial analyses of these hydroclimatic variables reveal that daily minimum temperature has increased more than daily maximum temperature, particularly during the cold season, and at higher elevations, contributing to earlier spring melt. Precipitation has decreased throughout the cold season and increased in the warm season, particularly in the northern half of the study area. Snow accumulation has decreased through all months of the year while snowmelt results indicate slight increases in mid-winter melt events and an earlier onset of the spring freshet. This study provides a summary of detected trends in key hydroclimatic variables across western Canada regarding the effects these changes can have on the spring freshet and streamflow throughout the region.

scholarly journals Terrain Effects on Regional Precipitation in a Warm Season over Qinling-Daba Mountains in Central China

Atmosphere ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1685
Author(s):  
Xiaofei Li ◽  
Ninglian Wang ◽  
Zhanhao Wu
Keyword(s):  
Water Vapor ◽  
Cross Section ◽  
Diurnal Cycle ◽  
Convective Available Potential Energy ◽  
Potential Temperature ◽  
Warm Season ◽  
Central China ◽  
Qinling Mountains ◽  
Terrain Effects ◽  
Time Period

The terrain effects of Qinling–Daba Mountains on reginal precipitation during a warm season were investigated in a two-month day-to-day experiment using the Weather Research and Forecasting (WRF) model. According to the results from the terrain sensitivity experiment with lowered mountains, Qinling–Daba Mountains have been found to have an obvious effect on both the spatial-temporal distribution and diurnal cycle of reginal precipitation from July to August in 2019, where the Qinling Mountains mainly enhanced the precipitation around 34° N, and the Daba Mountains mainly enhanced it around 32° N at the time period of early morning and midnight. Horizontal distribution of water vapor and convective available potential energy (CAPE), as well as cross section of vertical velocity of wind and potential temperature has been studied to examine the key mechanisms for these two mountains’ effect. The existence of Qinling Mountains intercepted transportation of water vapor from South to North in the lower troposphere to across 34° N and caused an obvious enhancement of CAPE in the neighborhood, while the Daba Mountains intercepted the northward water vapor transportation to across 32° N and caused an enhanced CAPE nearby. The time period of the influence is in a good accordance with the diurnal cycle. In the cross-section, the existence of Qinling Mountains and Daba Mountains are found to stimulate the upward motion and unstable environment effectively at around 34° N and 32° N, separately. As a result, the existence of the two mountains lead to a favorable environment in water vapor, thermodynamic, and dynamic conditions for this warm season precipitation.

scholarly journals Temperature and humidity conditions of Macocha Abyss

2012 ◽  
Vol 42 (3) ◽  
pp. 227-242
Author(s):  
Tomáš Litschmann ◽  
Jaroslav Rožnovský ◽  
Tomáš Středa ◽  
Hana Středová ◽  
Jiří Hebelka
Keyword(s):  
Relative Humidity ◽  
Warm Season ◽  
Cold Season ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Cold Air ◽  
Central European ◽  
Temperature And Humidity ◽  
Summer Time

Abstract The paper deals with the evaluation of temperature and humidity measurements in the vertical profile of Macocha Abyss (Moravian Karst, South Moravia, Czech Republic). The measuring profile on a rock wall is made up of seven HOBO-PRO sensors. Two other meteorological stations are installed at the bottom and near the upper edge of the abyss. The evaluation was designed separately for warm season (June 1, 2008 to August 31, 2008) and cold season (November 1, 2008 to February 28, 2009). In the warm season, distribution of inverse temperatures dominated in the abyss. Temperature differences between the bottom of the abyss and its upper edge reached about 10 ◦ C. At the bottom of the abyss, the minimum temperatures proved to be higher than at its upper edge and in its vicinity. Thermal circulation is evident to the depth of about 60 m. The highest temperatures were observed in the deeper layers of the abyss in the warm period at around 10 a.m. of Central European Summer Time. Towards the upper edge of the abyss, the hour of daily maximum temperature shifts to 2 to 4 p.m. In the cold season, the minimum temperature was observed between 6 and 7 a.m. of Central European Time. A decrease in the accumulation of cold air (cold-air pool formation) was not found in the lower floors of the abyss. This phenomenon does not occur even during clear nights. The depth of 60 m from the upper edge of the area maintains a high relative humidity (above 95%) in the warm season. However, humidity decreases from this depth towards the top of the abyss. In the cold season, the whole abyss is filled with air with relative humidity of 90 to 95%.

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