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Global Precipitation with Climate Change

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A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Climatology".

Deadline for manuscript submissions: closed (31 December 2017) | Viewed by 74548

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Prof. Dr. Nicole Mölders

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Guest Editor

Department of Atmospheric Sciences, University of Alaska, Fairbanks, AK 99775, USA
Interests: human and natural impacts on weather, air quality and climate; land-cover/use impacts on cloud and precipitation formation; pollution in remote locations, wind energy; evaluation of air-quality model results
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Special Issue Information

Dear Colleagues,

Precipitation is one of the hardest to predict and measure quantities. However, the amount, duration and time of precipitation is of great importance for agricultural, water management, generation of hydropower, flood protection, shipping, and many more sectors. Water demands have increased tremendously over the last 70 years due to nearly quadrupling of the world population. This Special Issue aims at advancing our current knowledge on precipitation. Articles addressing measurement and modeling issues, as well as parameterization of precipitation, are welcome. Additionally, investigations on precipitation changes over timeframes longer than 30 years, and improved gridded datasets with high resolution of precipitation are encouraged too. Furthermore, papers addressing the impact of air pollution, land-use and land-cover changes, as well as wind farms on precipitation, are sought.

Prof. Nicole Mölders
Guest Editor

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Keywords

precipitation measurements by gauges and remote sensing methods
precipitation catch deficits
gridded precipitation data products
impact of land-cover changes on precipitation
impact of air pollution on precipitation
long-term precipitation changes including changes in precipitation extreme events
acid precipitation
extreme precipitation events
solid precipitation and snow-water equivalent determination
spatial and temporal heterogeneity of precipitation

Published Papers (10 papers)

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Research

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18 pages, 7065 KiB

Open AccessArticle

Variability of Rainfall Erosivity and Erosivity Density in the Ganjiang River Catchment, China: Characteristics and Influences of Climate Change

by Xianghu Li and Xuchun Ye

Atmosphere 2018, 9(2), 48; https://doi.org/10.3390/atmos9020048 - 03 Feb 2018

Cited by 31 | Viewed by 4631

Abstract

Soil erosion is one of the most critical environmental hazards in the world. Understanding the changes in rainfall erosivity (RE) and erosivity density (ED), as well as their affecting factors, at local and catchment scales in the context of climate warming is an important prerequisite of soil erosion prevention and soil loss risk assessment. The present study identified the variability and trends of RE and ED in terms of both time and space in the Ganjiang River catchment over the period of 1960–2012, and also analyzed and discussed the impact of climate change. The results show that RE and ED in the catchment had great monthly variations and high year-to-year variability. Both presented long-term increasing trends over the entire study period. The highest RE and ED were observed in June and in the eastern and northeast parts of the catchment, which indicated that June was the most susceptible month for soil erosion in this area and the lower reaches of the Ganjiang River was the riskiest area for soil erosion. Finally, the East Asian summer monsoon and climate change were highly correlated with changes in RE and ED. Full article

(This article belongs to the Special Issue Global Precipitation with Climate Change)

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1750 KiB

Open AccessArticle

Observed and Projected Precipitation Changes over the Nine US Climate Regions

by Petr Chylek, Manvendra K. Dubey, Nicholas Hengartner and James D. Klett

Atmosphere 2017, 8(11), 207; https://doi.org/10.3390/atmos8110207 - 25 Oct 2017

Cited by 7 | Viewed by 5789

Abstract

We analyze the past (1900–2015) temperature and precipitation changes in nine separate US climate regions. We find that the temperature increased in a statistically significant (95% confidence level equivalent to alpha level of 0.05) manner in all of these regions. However, the variability in the observed precipitation was much more complex. In the eastern US (east of Rocky Mountains), the precipitation increased in all five climate regions and the increase was statistically significant in three of them. In contract, in the western US, the precipitation increased in two regions and decreased in two with no statistical significance in any region. The CMIP5 climate models (an ensemble mean) were not able to capture properly either the large precipitation differences between the eastern and the western US, or the changes of precipitation between 1900 and 2015 in eastern US. The statistical regression model explains the differences between the eastern and western US precipitation as results of different significant predictors. The anthropogenic greenhouse gases and aerosol (GHGA) are the major forcing of the precipitation in the eastern part of US, while the Pacific Decadal Oscillation (PDO) has the major influence on precipitation in the western part of the US. Our analysis suggests that the precipitation over the eastern US increased at an approximate rate of 6.7%/K, in agreement with the Clausius-Clapeyron equation, while the precipitation of the western US was approximately constant, independent of the temperature. Future precipitation over the western part of the US will depend on the behavior of the PDO, and how it (PDO) may be affected by future warming. Low hydrological sensitivity (percent increase of precipitation per one K of warming) projected by the CMIP5 models for the eastern US suggests either an underestimate of future precipitation or an overestimate of future warming. Full article

(This article belongs to the Special Issue Global Precipitation with Climate Change)

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6094 KiB

Open AccessArticle

Decadal Spatial-Temporal Variations in the Spatial Pattern of Anomalies of Extreme Precipitation Thresholds (Case Study: Northwest Iran)

by Iman Rousta, Mohammad Hossain Nasserzadeh, Masoud Jalali, Esmaeil Haghighi, Haraldur Ólafsson, Saeide Ashrafi, Mehdi Doostkamian and Ali Ghasemi

Atmosphere 2017, 8(8), 135; https://doi.org/10.3390/atmos8080135 - 03 Aug 2017

Cited by 17 | Viewed by 4270

Abstract

This study focused on decadalvariations of extreme precipitation thresholds within a 50-year period (1961–2010) for 250 stations of Iran’s northwest. The 99th percentile was used as the threshold of extreme precipitation. In order to analyze threshold cycles and spatial autocorrelation pattern dominating extreme precipitation thresholds, spectral analysis and Gi (known as HOTSPOT) were used respectively. The results revealed that the highest threshold of extreme precipitation occurred along the Ghoosheh Dagh mountain range. Additionally, in all the five studied decades, the highest positive anomalies were observed in the same region (i.e., the Ghoosheh Dagh). The findings also showed that the intensity of positive spatial autocorrelation pattern of extreme precipitation thresholds experienced a declining trend in recent decades. At the same time, extreme precipitation weighted mean center indicated that they followed an ordered pattern during the studied period. The results of harmonic analysis demonstrated that, in all decades, short-term (2–4 years) and mid-term (4–8 years) cycles of extreme precipitation thresholds were dominated. However, especially the southwest of the studied area, the return period of extreme precipitation thresholds was as long as the studied period, a phenomenon that indicates the existence of a trend in extreme precipitation thresholds of these regions. Full article

(This article belongs to the Special Issue Global Precipitation with Climate Change)

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8599 KiB

Open AccessArticle

The Impacts of Atmospheric Moisture Transportation on Warm Sector Torrential Rains over South China

by Shuixin Zhong and Zitong Chen

Atmosphere 2017, 8(7), 116; https://doi.org/10.3390/atmos8070116 - 30 Jun 2017

Cited by 12 | Viewed by 4335

Abstract

Warm Sector Torrential Rains (WSTRs) occurring during the outbreak of the monsoon in May of 2015 in South China were studied using surface automatic weather observational data, sounding, European Centre for Medium-Range Weather Forecasts Reanalysis interim Data (ERA-interim), satellite and radar data, and a four-level nested grid simulation with the finest grid spacing of 1 km using the Weather Research and Forecasting model (WRF). The results show that the extreme precipitation event, which had maximum rainfall amounts of 406.3 mm in 10 h and 542.2 mm in 24 h on 20 May 2015, and was characterized by its rapid development and its highly concentrated and long duration of heavy rainfall, occurred over the trumpet-shaped topography of Haifeng. The simulation results indicated that the South China Sea (SCS) atmospheric moisture transportation (AMT) was crucial in triggering the precipitation of the WSTR over South China. The simulation of the WSTR was conducted by using the total energy-mass flux scheme (TEMF), which provided a reasonable simulation of the circulation and the vertical profile in the Planetary Boundary Layer (PBL) as well as the estimation of the precipitation. The AMT, which extends from the Beibu Gulf and the South China Sea to the coastal areas and provides Shanwei with a considerable amount of moisture in the boundary layer, and the effects within the PBL, which include orographic effects, an extra low-level jet, and a high-energy tongue characterized by a high-potential pseudo-equivalent temperature tongue with a warm and moist southwesterly wind, were the important large-scale factors causing the WSTR. Full article

(This article belongs to the Special Issue Global Precipitation with Climate Change)

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5461 KiB

Open AccessArticle

Future Changes in Global Precipitation Projected by the Atmospheric Model MRI-AGCM3.2H with a 60-km Size

by Shoji Kusunoki

Atmosphere 2017, 8(5), 93; https://doi.org/10.3390/atmos8050093 - 21 May 2017

Cited by 13 | Viewed by 5278

Abstract

We conducted global warming projections using the Meteorological Research Institute-Atmospheric General Circulation Model Version 3.2 with a 60-km grid size (MRI-AGCM3.2H). For the present-day climate of 21 years from 1983 through 2003, the model was forced with observed historical sea surface temperature (SST). For the future climate of 21 years from 2079–2099, the model was forced with future SST projected by conventional couple models. Twelve-member ensemble simulations for three different cumulus convection schemes and four different SST distributions were conducted to evaluate the uncertainty of projection. Annual average precipitation will increase over the equatorial regions and decrease over the subtropical regions. The future precipitation changes are generally sensitive to the cumulus convection scheme, but changes are influenced by the SST over the some regions of the Pacific Ocean. The precipitation efficiency defined as precipitation change per 1° surface air temperature warming is evaluated. The global average of precipitation efficiency for annual average precipitation was less than the maximum value expected by thermodynamical theory, indicating that dynamical atmospheric circulation is acting to reduce the conversion efficiency from water vapor to precipitation. The precipitation efficiency by heavy precipitation is larger than that by moderate and weak precipitation. Full article

(This article belongs to the Special Issue Global Precipitation with Climate Change)

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8486 KiB

Open AccessArticle

Assessment of Temperature and Elevation Controls on Spatial Variability of Rainfall in Iran

by Majid Javari

Atmosphere 2017, 8(3), 45; https://doi.org/10.3390/atmos8030045 - 06 Mar 2017

Cited by 12 | Viewed by 8703

Abstract

With rainfall changes, hydrological process variability increases. This study predicts the potential effects of temperature and topography characteristics on rainfall spatial variability. Temperature and topography were considered as two effective factors that may influence monthly rainfall. This study uses rainfall and temperature data from 174 synoptic and climatic stations and 39,055 rain, elevation and temperature points extracted by ArcGIS10.3 over the 40 years (1975–2014). In this study, in order to predict the relationship between temperature, topography and rainfall, a combination of statistics including spatial statistics and Geographical information System (GIS) methods were employed. It was found that the distribution and rainfall variability in some parts of Iran was regarded to be based on topography and temperature. The spatial patterns showed that the variability based on spatial autocorrelation in rainfall severity gradually increased from west to east and north to south in Iran. Temperature and topography influence rainfall spatial variability; moreover, these factors have direct, indirect and total effects on rainfall variability in temporal and spatial patterns. These research results will be useful for the regionalization of climate and rainfall formation factors, management of water sources, environmental planning and measuring environmental controls on the climate system. Full article

(This article belongs to the Special Issue Global Precipitation with Climate Change)

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3349 KiB

Open AccessFeature PaperArticle

Evaluating the Hydrological Cycle over Land Using the Newly-Corrected Precipitation Climatology from the Global Precipitation Climatology Centre (GPCC)

by Udo Schneider, Peter Finger, Anja Meyer-Christoffer, Elke Rustemeier, Markus Ziese and Andreas Becker

Atmosphere 2017, 8(3), 52; https://doi.org/10.3390/atmos8030052 - 03 Mar 2017

Cited by 224 | Viewed by 17501

Abstract

The 2015 release of the precipitation climatology from the Global Precipitation Climatology Centre (GPCC) for 1951–2000, based on climatological normals of about 75,100 rain gauges, allows for quantification of mean land surface precipitation as part of the global water cycle. In GPCC’s 2011-release, a bulk climatological correction was applied to compensate for gauge undercatch. In this paper we derive an improved correction approach based on the synoptic weather reports for the period 1982–2015. The compared results show that the climatological approach tends to overestimate the correction for Central and Eastern Europe, especially in the northern winter, and in other regions throughout the year. Applying the mean weather-dependent correction to the GPCC’s uncorrected precipitation climatology for 1951–2000 gives a value of 854.7 mm of precipitation per year (excluding Antarctica) or 790 mm for the global land surface. The warming of nearly 1 K relative to pre-industrial temperatures is expected to be accompanied by a 2%–3% increase in global (land and ocean) precipitation. However, a comparison of climatology for 30-year reference periods from 1931–1960 up to 1981–2010 reveals no significant trend for land surface precipitation. This may be caused by the large variability of precipitation, the varying data coverage over time and other issues related to the sampling of rain-gauge networks. The GPCC continues to enlarge and further improve the quality of its database, and will generate precipitation analyses with homogeneous data coverage over time. Another way to reduce the sampling issues is the combination of rain gauge-based analyses with remote sensing (i.e., satellite or radar) datasets. Full article

(This article belongs to the Special Issue Global Precipitation with Climate Change)

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5994 KiB

Open AccessArticle

Tracing the Source of the Errors in Hourly IMERG Using a Decomposition Evaluation Scheme

by Shiguang Xu, Yan Shen and Zhe Du

Atmosphere 2016, 7(12), 161; https://doi.org/10.3390/atmos7120161 - 13 Dec 2016

Cited by 21 | Viewed by 4324

Abstract

Integrated Multi-satellite Retrievals for Global Precipitation Measurement (IMERG) is an important satellite precipitation product of Global Precipitation Measurement (GPM) mission. Quantitative information about the errors of IMERG has great significance for the data developers and end users. In order to investigate the characteristics and the source of the errors contained in IMERG, a bias-decomposition scheme was employed to evaluate the hourly IMERG over the eastern part of Mainland China during the warm season. First, the total bias of IMERG before and after calibration (termed as precipitationUncal and precipitationCal) was calculated using rain gauge measurements as reference. Then the bias was decomposed into three independent components including false bias, missed bias, and hit bias. Finally, the hit bias was further decomposed according to the rainfall intensity measured by rain gauges. The results indicate that (1) the bias of precipitationUncal over the north part is dominated by hit bias and false bias, leading to the serious overestimation for the precipitation over this area, but it underestimates the precipitation over the south part with the false bias and missed bias acting as major contributors; (2) the precipitationCal overestimates the precipitation over more than 80% of the study areas mainly as a result of a large amplitude of false bias; (3) the calibration algorithm used by IMERG could not reduce the missed bias and enlarges the false bias over some regions, revealing a shortcoming of this algorithm in that it could not effectively alleviate the bias resulting from the rain areas delineation; (4) the hit bias of IMERG is strongly related with the rainfall intensity of rain gauge measurements, which should be beneficial for reducing the errors of IMERG. This study provides a deep insight into the characteristics and sources of the biases inherent in IMERG, which is significant for its utilization and possible correction in future. Full article

(This article belongs to the Special Issue Global Precipitation with Climate Change)

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1427 KiB

Open AccessArticle

Patterns of Dekadal Rainfall Variation Over a Selected Region in Lake Victoria Basin, Uganda

by Isaac Mugume, Michel D. S. Mesquita, Charles Basalirwa, Yazidhi Bamutaze, Joachim Reuder, Alex Nimusiima, Daniel Waiswa, Godfrey Mujuni, Sulin Tao and Triphonia Jacob Ngailo

Atmosphere 2016, 7(11), 150; https://doi.org/10.3390/atmos7110150 - 22 Nov 2016

Cited by 16 | Viewed by 8648

Abstract

Understanding variations in rainfall in tropical regions is important due to its impacts on water resources, health and agriculture. This study assessed the dekadal rainfall patterns and rain days to determine intra-seasonal rainfall variability during the March–May season using the Mann–Kendall ( [...] Read more.

M K

) trend test and simple linear regression (

S L R

) over the period 2000–2015. Results showed an increasing trend of both dekadal rainfall amount and rain days (third and seventh dekads). The light rain days (

S L R

= 0.181;

M K

= 0.350) and wet days (

S L R

= 0.092;

M K

= 0.118) also depict an increasing trend. The rate of increase of light rain days and wet days during the third dekad (light rain days:

S L R

= 0.020;

M K

= 0.279 and wet days:

S L R

= 0.146;

M K

= 0.376) was slightly greater than during the seventh dekad (light rain days:

S L R

= 0.014;

M K

= 0.018 and wet days:

S L R

= 0.061;

M K

= 0.315) dekad. Seventy-four percent accounted for 2–4 consecutive dry days, but no significant trend was detected. The extreme rainfall was increasing over the third (

M K

= 0.363) and seventh (

M K

= 0.429) dekads. The rainfall amount and rain days were highly correlated (r: 0.43–0.72). Full article

(This article belongs to the Special Issue Global Precipitation with Climate Change)

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7351 KiB

Open AccessLetter

On the Precipitation and Precipitation Change in Alaska

by Gerd Wendler, Telayna Gordon and Martin Stuefer

Atmosphere 2017, 8(12), 253; https://doi.org/10.3390/atmos8120253 - 15 Dec 2017

Cited by 30 | Viewed by 9622

Abstract

Alaska observes very large differences in precipitation throughout the state; southeast Alaska experiences consistently wet conditions, while northern Arctic Alaska observes very dry conditions. The maximum mean annual precipitation of 5727 mm is observed in the southeastern panhandle at Little Port Arthur, while the minimum of 92 mm occurs on the North Slope at Kuparuk. Besides explaining these large differences due to geographic and orographic location, we discuss the changes in precipitation with time. Analyzing the 18 first-order National Weather Service stations, we found that the total average precipitation in the state increased by 17% over the last 67 years. The observed changes in precipitation are furthermore discussed as a function of the observed temperature increase of 2.1 °C, the mean temperature change of the 18 stations over the same period. This observed warming of Alaska is about three times the magnitude of the mean global warming and allows the air to hold more water vapor. Furthermore, we discuss the effect of the Pacific Decadal Oscillation (PDO), which has a strong influence on both the temperature and precipitation in Alaska. Full article

(This article belongs to the Special Issue Global Precipitation with Climate Change)

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