Development of a daily gridded precipitation data set for the Middle East

Abstract. We show an algorithm to construct a rain-gauge-based analysis of daily precipitation for the Middle East. One of the key points of our algorithm is to construct an accurate distribution of climatology. One possible advantage of this product is to validate high-resolution climate models and/or to diagnose the impact of climate changes on local hydrological resources. Many users are familiar with a monthly precipitation dataset (New et al., 1999) and a satellite-based daily precipitation dataset (Huffman et al., 2001), yet our data set, unlike theirs, clearly shows the effect of orography on daily precipitation and other extreme events, especially over the Fertile Crescent region. Currently the Middle-East precipitation analysis product is consisting of a 25-year data set for 1979–2003 based on more than 1300 stations.

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Evaluation of Future Climate and Potential Impact on Streamflow in the Upper Nan River Basin of Northern Thailand

Advances in Meteorology ◽

10.1155/2020/8881118 ◽

2020 ◽

Vol 2020 ◽

pp. 1-15

Author(s):

Miyuru B. Gunathilake ◽

Yasasna V. Amaratunga ◽

Anushka Perera ◽

Imiya M. Chathuranika ◽

Anura S. Gunathilake ◽

...

Keyword(s):

River Basin ◽

Minimum Temperature ◽

Climate Models ◽

Hydrological Modeling ◽

Winter Season ◽

Future Climate ◽

Maximum Temperature ◽

Monthly Precipitation ◽

Northern Thailand ◽

The Impact

Water resources in Northern Thailand have been less explored with regard to the impact on hydrology that the future climate would have. For this study, three regional climate models (RCMs) from the Coordinated Regional Downscaling Experiment (CORDEX) of Coupled Model Intercomparison Project 5 (CMIP5) were used to project future climate of the upper Nan River basin. Future climate data of ACCESS_CCAM, MPI_ESM_CCAM, and CNRM_CCAM under Representation Concentration Pathways RCP4.5 and RCP8.5 were bias-corrected by the linear scaling method and subsequently drove the Hydrological Engineering Center-Hydrological Modeling System (HEC-HMS) to simulate future streamflow. This study compared baseline (1988–2005) climate and streamflow values with future time scales during 2020–2039 (2030s), 2040–2069 (2050s), and 2070–2099 (2080s). The upper Nan River basin will become warmer in future with highest increases in the maximum temperature of 3.8°C/year for MPI_ESM and minimum temperature of 3.6°C/year for ACCESS_CCAM under RCP8.5 during 2080s. The magnitude of changes and directions in mean monthly precipitation varies, with the highest increase of 109 mm for ACESSS_CCAM under RCP 4.5 in September and highest decrease of 77 mm in July for CNRM, during 2080s. Average of RCM combinations shows that decreases will be in ranges of −5.5 to −48.9% for annual flows, −31 to −47% for rainy season flows, and −47 to −67% for winter season flows. Increases in summer seasonal flows will be between 14 and 58%. Projection of future temperature levels indicates that higher increases will be during the latter part of the 20th century, and in general, the increases in the minimum temperature will be higher than those in the maximum temperature. The results of this study will be useful for river basin planners and government agencies to develop sustainable water management strategies and adaptation options to offset negative impacts of future changes in climate. In addition, the results will also be valuable for agriculturists and hydropower planners.

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Global gridded precipitation over land: a description of the new GPCC First Guess Daily product

Earth System Science Data ◽

10.5194/essd-6-49-2014 ◽

2014 ◽

Vol 6 (1) ◽

pp. 49-60 ◽

Cited By ~ 77

Author(s):

K. Schamm ◽

M. Ziese ◽

A. Becker ◽

P. Finger ◽

A. Meyer-Christoffer ◽

...

Keyword(s):

Quality Control ◽

Real Time ◽

Daily Precipitation ◽

Grid Cell ◽

Rain Gauge ◽

Kriging Interpolation ◽

Telecommunication System ◽

Full Data ◽

Data Set ◽

Global Telecommunication System

Abstract. This paper describes the new First Guess Daily product of the Global Precipitation Climatology Centre (GPCC). The new product gives an estimate of the global daily precipitation gridded at a spatial resolution of 1° latitude by 1° longitude. It is based on rain gauge data reported in near-real time via the Global Telecommunication System (GTS) and available about three to five days after the end of each observation month. In addition to the gridded daily precipitation totals in mm day−1, the standard deviation in mm day−1, the kriging interpolation error in % and the number of measurements per grid cell are also encoded into the monthly netCDF product file and provided for all months since January 2009. Prior to their interpolation, the measured precipitation values undergo a preliminary automatic quality control. For the calculation of the areal mean of the grid, anomalies are interpolated with ordinary block kriging. This approach allows for a near-real-time release. Therefore, the purely GTS-based data processing lacks an intensive quality control as well as a high data density and is denoted as First Guess. The daily data set is referenced under doi:10.5676/DWD_GPCC/FG_D_100. Two further products, the Full Data Daily and a merged satellite-gauge product, are currently under development at Deutscher Wetterdienst (DWD). These additional products will not be available in near-real time, but based on significantly more and strictly quality controlled observations. All GPCC products are provided free of charge via the GPCC webpage: ftp://ftp-anon.dwd.de/pub/data/gpcc/html/download_gate.html.

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High-end climate change impact on European runoff and low flows – exploring the effects of forcing biases

Hydrology and Earth System Sciences ◽

10.5194/hess-20-1785-2016 ◽

2016 ◽

Vol 20 (5) ◽

pp. 1785-1808 ◽

Cited By ~ 29

Author(s):

Lamprini V. Papadimitriou ◽

Aristeidis G. Koutroulis ◽

Manolis G. Grillakis ◽

Ioannis K. Tsanis

Keyword(s):

Global Warming ◽

Bias Correction ◽

Climate Models ◽

Climate Model ◽

Global Climate ◽

Global Climate Model ◽

Data Set ◽

Low Flows ◽

The Impact ◽

Selection Of

Abstract. Climate models project a much more substantial warming than the 2 °C target under the more probable emission scenarios, making higher-end scenarios increasingly plausible. Freshwater availability under such conditions is a key issue of concern. In this study, an ensemble of Euro-CORDEX projections under RCP8.5 is used to assess the mean and low hydrological states under +4 °C of global warming for the European region. Five major European catchments were analysed in terms of future drought climatology and the impact of +2 °C versus +4 °C global warming was investigated. The effect of bias correction of the climate model outputs and the observations used for this adjustment was also quantified. Projections indicate an intensification of the water cycle at higher levels of warming. Even for areas where the average state may not considerably be affected, low flows are expected to reduce, leading to changes in the number of dry days and thus drought climatology. The identified increasing or decreasing runoff trends are substantially intensified when moving from the +2 to the +4° of global warming. Bias correction resulted in an improved representation of the historical hydrology. It is also found that the selection of the observational data set for the application of the bias correction has an impact on the projected signal that could be of the same order of magnitude to the selection of the Global Climate Model (GCM).

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Estimating Probable Maximum Precipitation for Linau River Basin in Sarawak

Journal of Civil Engineering Science and Technology ◽

10.33736/jcest.138.2014 ◽

2014 ◽

Vol 5 (3) ◽

pp. 1-5

Author(s):

M. Hussain ◽

S. Nadya ◽

F.J. Chia

Keyword(s):

Statistical Method ◽

River Basin ◽

Public Safety ◽

Geographical Location ◽

Hydraulic Modeling ◽

Rain Gauge ◽

Data Set ◽

Probable Maximum Precipitation ◽

Maximum Precipitation ◽

The Impact

The probable maximum precipitation (PMP) is the greatest depth of precipitation for a given duration that is physically possible over a given size storm area at a particular geographical location at a certain time of the year. PMP is very important to be considered for the design of river regulating structures i.e Dams and Barrages to overcome any possible chance of overtopping failure as well as for public safety and hazards downstream of any of these structures. Especially if these structures located in the upstream of the of the populated town or city than the failure could damage severely such areas. As such the PMP convention is always a requirement as primary design dam/reservoir criteria when public safety is of concern. The PMP is used to derive Probable Maximum Flood (PMF), which further used in hydraulic modeling to check the impact assessments for such occasions. This paper focuses on estimation of PMP for Linau River Basin in Sarawak using statistical method proposed by World Meteorological Organization (WMO), which is described in its operational manual. Long Lidam and Long Laku are located in Linau River Basin but Long Laku has long discontinuity in the data set thus the rainfall series at Long Lidam is further used for PMP estimation. The missing data was in-filled using Belaga rain gauge station as Long Lidam rainfall has good correlation with Belaga rainfall data. Hershfield statistical method has been adopted to estimate the 24-hour duration PMP. The Probable Maximum Precipitation for 24-hour duration storm is estimated as 691 mm for the Linau River Basin.

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Monitoring aerosol–cloud interactions at the CESAR Observatory in the Netherlands

Atmospheric Measurement Techniques ◽

10.5194/amt-10-1987-2017 ◽

2017 ◽

Vol 10 (5) ◽

pp. 1987-1997 ◽

Cited By ~ 4

Author(s):

Karolina Sarna ◽

Herman W. J. Russchenberg

Keyword(s):

Remote Sensing ◽

The Netherlands ◽

Climate Models ◽

Cloud Droplet ◽

Doppler Velocity ◽

Backscatter Coefficient ◽

Liquid Water Path ◽

Data Set ◽

Aerosol Cloud ◽

The Impact

Abstract. The representation of aerosol–cloud interaction (ACI) processes in climate models, although long studied, still remains the source of high uncertainty. Very often there is a mismatch between the scale of observations used for ACI quantification and the ACI process itself. This can be mitigated by using the observations from ground-based remote sensing instruments. In this paper we presented a direct application of the aerosol–cloud interaction monitoring technique (ACI monitoring). ACI monitoring is based on the standardised Cloudnet data stream, which provides measurements from ground-based remote sensing instruments working in synergy. For the data set collected at the CESAR Observatory in the Netherlands we calculate ACI metrics. We specifically use attenuated backscatter coefficient (ATB) for the characterisation of the aerosol properties and cloud droplet effective radius (re) and number concentration (Nd) for the characterisation of the cloud properties. We calculate two metrics: ACIr  =  ln(re)/ln(ATB) and ACIN  =  ln(Nd)/ln(ATB). The calculated values of ACIr range from 0.001 to 0.085, which correspond to the values reported in previous studies. We also evaluated the impact of the vertical Doppler velocity and liquid water path (LWP) on ACI metrics. The values of ACIr were highest for LWP values between 60 and 105 g m−2. For higher LWP other processes, such as collision and coalescence, seem to be dominant and obscure the ACI processes. We also saw that the values of ACIr are higher when only data points located in the updraught regime are considered. The method presented in this study allow for monitoring ACI daily and further aggregating daily data into bigger data sets.

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Bias Correction of Climate Model’s Precipitation Using the Copula Method and Its Application in River Basin Simulation

Water ◽

10.3390/w11030600 ◽

2019 ◽

Vol 11 (3) ◽

pp. 600 ◽

Cited By ~ 7

Author(s):

Georgia Lazoglou ◽

Christina Anagnostopoulou ◽

Charalampos Skoulikaris ◽

Konstantia Tolika

Keyword(s):

River Basin ◽

Bias Correction ◽

Climate Models ◽

Climate Model ◽

Monthly Precipitation ◽

Distributed Hydrological Model ◽

Copula Method ◽

Corrected Data ◽

Precipitation Analysis ◽

Obs Data

During the last few decades, the utilization of the data from climate models in hydrological studies has increased as they can provide data in the regions that lack raw meteorological information. The data from climate models data often present biases compared to the observed data and consequently, several methods have been developed for correcting statistical biases. The present study uses the copula for modeling the dependence between the daily mean and total monthly precipitation using E-OBS data in the Mesta/Nestos river basin in order to use this relationship for the bias correction of the MPI climate model monthly precipitation. Additionally, both the non-corrected and bias corrected data are tested as they are used as the inputs to a spatial distributed hydrological model for simulating the basin runoff. The results showed that the MPI model significantly overestimates the E-OBS data while the differences are reduced sufficiently after the bias correction. The outputs from the hydrological models were proven to coincide with the precipitation analysis results and hence, the simulated discharges in the case of copula corrected data present an increased correlation with the observed flows.

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Updated world map of the Köppen-Geiger climate classification

Hydrology and Earth System Sciences ◽

10.5194/hess-11-1633-2007 ◽

2007 ◽

Vol 11 (5) ◽

pp. 1633-1644 ◽

Cited By ~ 4011

Author(s):

M. C. Peel ◽

B. L. Finlayson ◽

T. A. McMahon

Keyword(s):

Climate Models ◽

Global Climate ◽

Global Climate Models ◽

Monthly Precipitation ◽

Climate Type ◽

Data Set ◽

Supplementary Material ◽

Global Data

Abstract. Although now over 100 years old, the classification of climate originally formulated by Wladimir Köppen and modified by his collaborators and successors, is still in widespread use. It is widely used in teaching school and undergraduate courses on climate. It is also still in regular use by researchers across a range of disciplines as a basis for climatic regionalisation of variables and for assessing the output of global climate models. Here we have produced a new global map of climate using the Köppen-Geiger system based on a large global data set of long-term monthly precipitation and temperature station time series. Climatic variables used in the Köppen-Geiger system were calculated at each station and interpolated between stations using a two-dimensional (latitude and longitude) thin-plate spline with tension onto a 0.1°×0.1° grid for each continent. We discuss some problems in dealing with sites that are not uniquely classified into one climate type by the Köppen-Geiger system and assess the outcomes on a continent by continent basis. Globally the most common climate type by land area is BWh (14.2%, Hot desert) followed by Aw (11.5%, Tropical savannah). The updated world Köppen-Geiger climate map is freely available electronically in the Supplementary Material Section.

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Modeling the global emission, transport and deposition of trace elements associated with mineral dust

Biogeosciences ◽

10.5194/bg-12-5771-2015 ◽

2015 ◽

Vol 12 (19) ◽

pp. 5771-5792 ◽

Cited By ~ 30

Author(s):

Y. Zhang ◽

N. Mahowald ◽

R. A. Scanza ◽

E. Journet ◽

K. Desboeufs ◽

...

Keyword(s):

Radiative Forcing ◽

Climate Models ◽

Mineral Dust ◽

Chemical Elements ◽

Global Climate ◽

Global Climate Models ◽

Data Set ◽

Desert Dust ◽

Mineral Data ◽

The Impact

Abstract. Trace element deposition from desert dust has important impacts on ocean primary productivity, the quantification of which could be useful in determining the magnitude and sign of the biogeochemical feedback on radiative forcing. However, the impact of elemental deposition to remote ocean regions is not well understood and is not currently included in global climate models. In this study, emission inventories for eight elements primarily of soil origin, Mg, P, Ca, Mn, Fe, K, Al, and Si are determined based on a global mineral data set and a soil data set. The resulting elemental fractions are used to drive the desert dust model in the Community Earth System Model (CESM) in order to simulate the elemental concentrations of atmospheric dust. Spatial variability of mineral dust elemental fractions is evident on a global scale, particularly for Ca. Simulations of global variations in the Ca / Al ratio, which typically range from around 0.1 to 5.0 in soils, are consistent with observations, suggesting that this ratio is a good signature for dust source regions. The simulated variable fractions of chemical elements are sufficiently different; estimates of deposition should include elemental variations, especially for Ca, Al and Fe. The model results have been evaluated with observations of elemental aerosol concentrations from desert regions and dust events in non-dust regions, providing insights into uncertainties in the modeling approach. The ratios between modeled and observed elemental fractions range from 0.7 to 1.6, except for Mg and Mn (3.4 and 3.5, respectively). Using the soil database improves the correspondence of the spatial heterogeneity in the modeling of several elements (Ca, Al and Fe) compared to observations. Total and soluble dust element fluxes to different ocean basins and ice sheet regions have been estimated, based on the model results. The annual inputs of soluble Mg, P, Ca, Mn, Fe and K associated with dust using the mineral data set are 0.30 Tg, 16.89 Gg, 1.32 Tg, 22.84 Gg, 0.068 Tg, and 0.15 Tg to global oceans and ice sheets.

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Deep mixed ocean volume in the Labrador Sea in HighResMIP models

Climate Dynamics ◽

10.1007/s00382-021-05785-x ◽

2021 ◽

Author(s):

Torben Koenigk ◽

Ramon Fuentes-Franco ◽

Virna L. Meccia ◽

Oliver Gutjahr ◽

Laura C. Jackson ◽

...

Keyword(s):

High Resolution ◽

Climate Models ◽

Deep Convection ◽

Deep Ocean ◽

Meridional Overturning Circulation ◽

Labrador Sea ◽

Surface Salinity ◽

Data Set ◽

Standard Resolution ◽

The Impact

AbstractSimulations from seven global coupled climate models performed at high and standard resolution as part of the high resolution model intercomparison project (HighResMIP) are analyzed to study deep ocean mixing in the Labrador Sea and the impact of increased horizontal resolution. The representation of convection varies strongly among models. Compared to observations from ARGO-floats and the EN4 data set, most models substantially overestimate deep convection in the Labrador Sea. In four out of five models, all four using the NEMO-ocean model, increasing the ocean resolution from 1° to 1/4° leads to increased deep mixing in the Labrador Sea. Increasing the atmospheric resolution has a smaller effect than increasing the ocean resolution. Simulated convection in the Labrador Sea is mainly governed by the release of heat from the ocean to the atmosphere and by the vertical stratification of the water masses in the Labrador Sea in late autumn. Models with stronger sub-polar gyre circulation have generally higher surface salinity in the Labrador Sea and a deeper convection. While the high-resolution models show more realistic ocean stratification in the Labrador Sea than the standard resolution models, they generally overestimate the convection. The results indicate that the representation of sub-grid scale mixing processes might be imperfect in the models and contribute to the biases in deep convection. Since in more than half of the models, the Labrador Sea convection is important for the Atlantic Meridional Overturning Circulation (AMOC), this raises questions about the future behavior of the AMOC in the models.

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The Effect of Forests on the Amount of Incoming Precipitation over Europe

10.5194/egusphere-egu2020-21573 ◽

2020 ◽

Author(s):

Ronny Meier ◽

Edouard Davin ◽

Jonas Schwaab ◽

Sonia Seneviratne

Keyword(s):

Geographically Weighted Regression ◽

Land Surface ◽

Regional Climate ◽

Rain Gauge ◽

Weighted Regression ◽

Tropical Rain Forests ◽

Data Set ◽

European Continent ◽

Tropical Regions ◽

The Impact

<p>Numerous studies have demonstrated that forests considerably alter temperatures at the land surface. These alterations vary in space and time due to a complex interplay of several modified energy fluxes at the land surface. The effect of forests on the amount and pattern of precipitation has gained less attention, despite its high socio-economic relevance. Previous work has demonstrated that the high precipitation amounts in tropical rain forests are self-sustained by the abundance of those forests itself. Yet, the impact of forests on precipitation in extra-tropical regions has gained only little attention. This study attempts to identify a relationship between the amount of precipitation and the abundance of forests over the European continent. Such a relationship can originate from two kinds of interactions: (1) The amount of precipitation can drive the abundance of forests, as water is a crucial resource for forests ecosystems. (2) The energy and water redistribution at the land surface associated with forests can alter processes in the atmospheric air column, which in term could affect the amount of precipitation at the location of the forest. Here, we aim to isolate the second kind of effects, as those are more relevant for human decision making.</p><p>Establishing a causal relationship between the abundance of forests and the amount of precipitation is complex due this two-way interaction. Hence, three different data sources are employed to advance our understanding of how forests influence precipitation patterns. Firstly, a geographically weighted regression is applied to the spatially-continuous, observation-based precipitation data set MSWEP2.2 (Beck et al., 2017). Besides the forest fraction, a number of topographical variables are considered as predictor variables to account for potential confounding factors (i.e, to assure that interactions of the first kind are not misinterpreted as interactions of the second kind). Secondly, closely-located, paired sites that resemble in topography, but differ in forest fraction are identified in the GHCN (Menne et al., 2012) and the GSDR (Lewis et al., 2019) rain gauge data sets. This allows to evaluate the results based on MSWEP2.2. Thirdly, the same geographically weighted regression is applied to convection-resolving regional climate simulations. By artificially defining the forest fraction distribution in model simulations, interactions of the first kind can be disabled, further fostering the understanding about the causality on the relations identified using the observations. Further sensitivity experiments could be conducted, to improve the process understanding on interactions of the second kind. Overall, our results indicate, that the abundance of a forest increases the amount of precipitation in the order of 100 mm/yr in many locations of Europe. This increased amount of precipitation is more pronounced during the winter months, while the summer signal is more close to zero.</p>

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