scholarly journals Dynamics of key climate variables over Europe

2021 ◽  
Author(s):  
Chris Tzanis ◽  
Christos Kourtesiotis ◽  
Kostas Philippopoulos
Keyword(s):  
Relative Humidity ◽  
Grid Point ◽  
Specific Humidity ◽  
Positive Temperature ◽  
Climate Variables ◽  
Climate Trends ◽  
Climatic Trends ◽  
First Results ◽  
Slope Estimator ◽  
Stratospheric Cooling

<p>Temperature and humidity are key climatic variables for the assessment of climate variability. This study focuses on the climatic trends of temperature, specific and relative humidity both at the surface and in multiple pressure levels in the atmosphere. We present the first results of the analysis the dynamics of some key climate variables over Europe. The analysis was conducted for Europe, but it is focusing also on Greece. The main purpose of this study is to investigate whether possible changes in the basic climate variables exist over the recent years. </p><p>Data from the ERA5 reanalysis product are used for the period 1979-2018 (40 years) with spatial resolution of 0.25° x 0.25°. The Sen’s slope estimator is used to identify the climate trends at each grid point and the Mann-Kendall statistical test was applied to detect statistically significant spatial and temporal changes for the examined domain. The results indicate statistically significant warming trends at the 99% level over land and sea at surface. Regarding Greece, statistically significant warming trends at the 99% level occur during summer. In addition, positive temperature trends are also presented over land and sea, in the troposphere, over the particular domain. In contrast, in the stratosphere, statistically significant cooling trends at the 99% level are observed. Additionally, the stratospheric cooling trends increase with increasing altitude in the atmosphere. Regarding the climatic trends of the specific humidity, mainly positive values prevail up to mid-troposphere. Finally, the climatic trends of the relative humidity exhibit positive and negative values due to the relationship of humidity and temperature.</p>

scholarly journals Marine Boundary Layer Cloud Feedbacks in a Constant Relative Humidity Atmosphere

2012 ◽  
Vol 69 (8) ◽  
pp. 2538-2550 ◽  
Author(s):  
Malte Rieck ◽  
Louise Nuijens ◽  
Bjorn Stevens
Keyword(s):  
Boundary Layer ◽  
Relative Humidity ◽  
Liquid Water ◽  
Radiative Forcing ◽  
Marine Boundary Layer ◽  
Surface Fluxes ◽  
Lapse Rate ◽  
Specific Humidity ◽  
Trade Wind ◽  
Positive Temperature

Abstract The mechanisms that govern the response of shallow cumulus, such as found in the trade wind regions, to a warming of the atmosphere in which large-scale atmospheric processes act to keep relative humidity constant are explored. Two robust effects are identified. First, and as is well known, the liquid water lapse rate increases with temperature and tends to increase the amount of water in clouds, making clouds more reflective of solar radiation. Second, and less well appreciated, the surface fluxes increase with the saturation specific humidity, which itself is a strong function of temperature. Using large-eddy simulations it is shown that the liquid water lapse rate acts as a negative feedback: a positive temperature increase driven by radiative forcing is reduced by the increase in cloud water and hence cloud albedo. However, this effect is more than compensated by a reduction of cloudiness associated with the deepening and relative drying of the boundary layer, driven by larger surface moisture fluxes. Because they are so robust, these effects are thought to underlie changes in the structure of the marine boundary layer as a result of global warming.

scholarly journals Relationship between Shortwave Cloud Radiative Forcing and Local Meteorological Variables Compared in Observations and Several Global Climate Models

2006 ◽  
Vol 19 (17) ◽  
pp. 4344-4359 ◽  
Author(s):  
Markus Stowasser ◽  
Kevin Hamilton
Keyword(s):  
Relative Humidity ◽  
Vertical Velocity ◽  
Radiative Forcing ◽  
Large Scale ◽  
Climate Models ◽  
Grid Point ◽  
Global Climate Models ◽  
Coupled Models ◽  
Cloud Radiative Forcing ◽  
Cloud Forcing

Abstract The relations between local monthly mean shortwave cloud radiative forcing and aspects of the resolved-scale meteorological fields are investigated in hindcast simulations performed with 12 of the global coupled models included in the model intercomparison conducted as part of the preparation for Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4). In particular, the connection of the cloud forcing over tropical and subtropical ocean areas with resolved midtropospheric vertical velocity and with lower-level relative humidity are investigated and compared among the models. The model results are also compared with observational determinations of the same relationships using satellite data for the cloud forcing and global reanalysis products for the vertical velocity and humidity fields. In the analysis the geographical variability in the long-term mean among all grid points and the interannual variability of the monthly mean at each grid point are considered separately. The shortwave cloud radiative feedback (SWCRF) plays a crucial role in determining the predicted response to large-scale climate forcing (such as from increased greenhouse gas concentrations), and it is thus important to test how the cloud representations in current climate models respond to unforced variability. Overall there is considerable variation among the results for the various models, and all models show some substantial differences from the comparable observed results. The most notable deficiency is a weak representation of the cloud radiative response to variations in vertical velocity in cases of strong ascending or strong descending motions. While the models generally perform better in regimes with only modest upward or downward motions, even in these regimes there is considerable variation among the models in the dependence of SWCRF on vertical velocity. The largest differences between models and observations when SWCRF values are stratified by relative humidity are found in either very moist or very dry regimes. Thus, the largest errors in the model simulations of cloud forcing are prone to be in the western Pacific warm pool area, which is characterized by very moist strong upward currents, and in the rather dry regions where the flow is dominated by descending mean motions.

scholarly journals Trends in continental temperature and humidity directly linked to ocean warming

2018 ◽  
Vol 115 (19) ◽  
pp. 4863-4868 ◽  
Author(s):  
Michael P. Byrne ◽  
Paul A. O’Gorman
Keyword(s):  
Relative Humidity ◽  
Land Surface ◽  
Moisture Transport ◽  
Climate Change Impacts ◽  
Atmospheric Dynamics ◽  
Specific Humidity ◽  
Climate Projections ◽  
Moist Static Energy ◽  
Temperature And Humidity ◽  
Static Energy

In recent decades, the land surface has warmed substantially more than the ocean surface, and relative humidity has fallen over land. Amplified warming and declining relative humidity over land are also dominant features of future climate projections, with implications for climate-change impacts. An emerging body of research has shown how constraints from atmospheric dynamics and moisture budgets are important for projected future land–ocean contrasts, but these ideas have not been used to investigate temperature and humidity records over recent decades. Here we show how both the temperature and humidity changes observed over land between 1979 and 2016 are linked to warming over neighboring oceans. A simple analytical theory, based on atmospheric dynamics and moisture transport, predicts equal changes in moist static energy over land and ocean and equal fractional changes in specific humidity over land and ocean. The theory is shown to be consistent with the observed trends in land temperature and humidity given the warming over ocean. Amplified land warming is needed for the increase in moist static energy over drier land to match that over ocean, and land relative humidity decreases because land specific humidity is linked via moisture transport to the weaker warming over ocean. However, there is considerable variability about the best-fit trend in land relative humidity that requires further investigation and which may be related to factors such as changes in atmospheric circulations and land-surface properties.

scholarly journals Nocturnal Relative Humidity Maxima above the Boundary Layer in the U.S. Midwest: A Diagnostic for the Mountain–Plains Solenoidal Circulation

2018 ◽  
Vol 146 (2) ◽  
pp. 641-658
Author(s):  
Amanda Mercer ◽  
Rachel Chang ◽  
Ian Folkins
Keyword(s):  
Relative Humidity ◽  
Cross Sections ◽  
Lower Troposphere ◽  
Vertical Motion ◽  
Specific Humidity ◽  
Reanalysis Dataset ◽  
Low Level Jet ◽  
Vertical Winds ◽  
Modern Era ◽  
The U.S

Measurements from the Aircraft Communications, Addressing, and Reporting System (ACARS) dataset between 2005 and 2014 are used to construct diurnal vertical cross sections of relative humidity in the lower troposphere at six airports in the U.S. Midwest. In summer, relative humidity maxima occur between 2 and 3 km during the overnight hours of 0300–0900 local solar time (LST). These maxima coincide with negative anomalies in temperature and positive anomalies in specific humidity. Vertical winds from the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), reanalysis dataset show that the height and diurnal timing of these positive relative humidity anomalies are consistent with the regional diurnal pattern of vertical motion. During the day, there is rising motion over the Rocky Mountains and subsidence over the Midwest, while conversely at night, there is sinking motion over the mountains and rising motion over the Midwest. The nocturnal relative humidity maxima over the Midwest are the strongest direct observational evidence to date of this mountain–plains solenoidal circulation, and provide a useful diagnostic for testing the strength of this circulation in climate and reanalysis models. There is significant interannual variability in the strength of the nocturnal relative humidity maxima. In 2011, the relative humidity maxima are very pronounced. In 2014, however, they are almost nonexistent. Finally, the relative humidity maxima are discussed in relation to the low-level jet (LLJ). The LLJ appears to be too low to directly contribute to the nocturnal relative humidity maxima.

scholarly journals Alterations in Canadian Hydropower Production Potential Due to Continuation of Historical Trends in Climate Variables

Resources ◽  
2019 ◽  
Vol 8 (4) ◽  
pp. 163 ◽  
Author(s):  
Amirali Amir Jabbari ◽  
Ali Nazemi
Keyword(s):  
Power Plants ◽  
Critical Energy ◽  
Climate Variables ◽  
Climate Trends ◽  
Production Potential ◽  
The North ◽  
Energy Models ◽  
Hydropower Production ◽  
Domestic Use ◽  
Gain Loss

The vitality, timing, and magnitude of hydropower production is driven by streamflow, which is determined by climate variables, in particular precipitation and temperature. Accordingly, changes in climate characteristics can cause alterations in hydropower production potential. This delineates a critical energy security concern, especially in places such as Canada, where recent changes in climate are substantial and hydropower production is important for both domestic use and exportation. Current Canadian assessments, however, are limited as they mainly focus on a small number of power plants across the country. In addition, they implement scenario-led top-down impact assessments that are subject to large uncertainties in climate, hydrological, and energy models. To avoid these limitations, we propose a bottom-up impact assessment based on the historical information on climatic trends and causal links between climate variables and hydropower production across political jurisdictions. Using this framework, we estimate expected monthly gain/loss in regional hydropower production potential under the continuation of historical climate trends. Our findings show that Canada’s production potential is expected to increase, although the net gain/loss is subject to significant variations across different regions. Our results suggest increasing potential in Yukon, Ontario, and Quebec but decreasing production in the North Western Territories and Nunavut, British Columbia, and Alberta.

scholarly journals Atmospheric teleconnections between the Arctic and the eastern Baltic Sea regions

2017 ◽  
Vol 8 (4) ◽  
pp. 1019-1030 ◽  
Author(s):  
Liisi Jakobson ◽  
Erko Jakobson ◽  
Piia Post ◽  
Jaak Jaagus
Keyword(s):  
Baltic Sea ◽  
Reanalysis Data ◽  
Specific Humidity ◽  
The Arctic ◽  
Positive Temperature ◽  
Strong Negative Correlation ◽  
Mild Winter ◽  
Baltic Sea Region ◽  
The Arctic Oscillation ◽  
Eastern Baltic

Abstract. The teleconnections between meteorological parameters of the Arctic and the eastern Baltic Sea regions were analysed based on the NCEP-CFSR and ERA-Interim reanalysis data for 1979–2015. The eastern Baltic Sea region was characterised by meteorological values at a testing point (TP) in southern Estonia (58° N, 26° E). Temperature at the 1000 hPa level at the TP have a strong negative correlation with the Greenland sector (the region between 55–80° N and 20–80° W) during all seasons except summer. Significant teleconnections are present in temperature profiles from 1000 to 500 hPa. The strongest teleconnections between the same parameter at the eastern Baltic Sea region and the Arctic are found in winter, but they are clearly affected by the Arctic Oscillation (AO) index. After removal of the AO index variability, correlations in winter were below ±0.5, while in other seasons there remained regions with strong (|R| > 0.5, p < 0.002) correlations. Strong correlations (|R| > 0.5) are also present between different climate variables (sea-level pressure, specific humidity, wind speed) at the TP and different regions of the Arctic. These teleconnections cannot be explained solely with the variability of circulation indices. The positive temperature anomaly of mild winter at the Greenland sector shifts towards east during the next seasons, reaching the Baltic Sea region in summer. This evolution is present at 60 and 65° N but is missing at higher latitudes. The most permanent lagged correlations in 1000 hPa temperature reveal that the temperature in summer at the TP is strongly predestined by temperature in the Greenland sector in the previous spring and winter.

scholarly journals Modeling Seasonal Influenza Transmission and Its Association with Climate Factors in Thailand Using Time-Series and ARIMAX Analyses

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Sudarat Chadsuthi ◽  
Sopon Iamsirithaworn ◽  
Wannapong Triampo ◽  
Charin Modchang
Keyword(s):  
Relative Humidity ◽  
Moving Average ◽  
Arima Model ◽  
Southern Region ◽  
Climate Variables ◽  
Climate Data ◽  
Average Temperature ◽  
Minimum Relative Humidity ◽  
Average Maximum ◽  
Influenza Transmission

Influenza is a worldwide respiratory infectious disease that easily spreads from one person to another. Previous research has found that the influenza transmission process is often associated with climate variables. In this study, we used autocorrelation and partial autocorrelation plots to determine the appropriate autoregressive integrated moving average (ARIMA) model for influenza transmission in the central and southern regions of Thailand. The relationships between reported influenza cases and the climate data, such as the amount of rainfall, average temperature, average maximum relative humidity, average minimum relative humidity, and average relative humidity, were evaluated using cross-correlation function. Based on the available data of suspected influenza cases and climate variables, the most appropriate ARIMA(X) model for each region was obtained. We found that the average temperature correlated with influenza cases in both central and southern regions, but average minimum relative humidity played an important role only in the southern region. The ARIMAX model that includes the average temperature with a 4-month lag and the minimum relative humidity with a 2-month lag is the appropriate model for the central region, whereas including the minimum relative humidity with a 4-month lag results in the best model for the southern region.

scholarly journals Glacier changes and climate trends derived from multiple sources in the data scarce Cordillera Vilcanota region, southern Peruvian Andes

2013 ◽  
Vol 7 (1) ◽  
pp. 103-118 ◽  
Author(s):  
N. Salzmann ◽  
C. Huggel ◽  
M. Rohrer ◽  
W. Silverio ◽  
B. G. Mark ◽  
...  
Keyword(s):  
Air Temperature ◽  
Specific Humidity ◽  
Spatial And Temporal Variability ◽  
Moderate Increase ◽  
Climate Data ◽  
Climate Trends ◽  
Multiple Sources ◽  
Mountain Areas ◽  
Peruvian Andes ◽  
Glacier Changes

Abstract. The role of glaciers as temporal water reservoirs is particularly pronounced in the (outer) tropics because of the very distinct wet/dry seasons. Rapid glacier retreat caused by climatic changes is thus a major concern, and decision makers demand urgently for regional/local glacier evolution trends, ice mass estimates and runoff assessments. However, in remote mountain areas, spatial and temporal data coverage is typically very scarce and this is further complicated by a high spatial and temporal variability in regions with complex topography. Here, we present an approach on how to deal with these constraints. For the Cordillera Vilcanota (southern Peruvian Andes), which is the second largest glacierized cordillera in Peru (after the Cordillera Blanca) and also comprises the Quelccaya Ice Cap, we assimilate a comprehensive multi-decadal collection of available glacier and climate data from multiple sources (satellite images, meteorological station data and climate reanalysis), and analyze them for respective changes in glacier area and volume and related trends in air temperature, precipitation and in a more general manner for specific humidity. While we found only marginal glacier changes between 1962 and 1985, there has been a massive ice loss since 1985 (about 30% of area and about 45% of volume). These high numbers corroborate studies from other glacierized cordilleras in Peru. The climate data show overall a moderate increase in air temperature, mostly weak and not significant trends for precipitation sums and probably cannot in full explain the observed substantial ice loss. Therefore, the likely increase of specific humidity in the upper troposphere, where the glaciers are located, is further discussed and we conclude that it played a major role in the observed massive ice loss of the Cordillera Vilcanota over the past decades.

Humidity profiles and their interactions with moisture transport and surface fluxes in the Antarctic

2020 ◽  
Author(s):  
Tuomas Naakka ◽  
Tiina Nygård ◽  
Timo Vihma
Keyword(s):  
Relative Humidity ◽  
Sea Ice ◽  
Moisture Transport ◽  
Vertical Structure ◽  
Water Cycle ◽  
Surface Fluxes ◽  
Specific Humidity ◽  
Near Surface ◽  
The Antarctic ◽  
Humidity Profiles

&lt;p&gt;Atmospheric humidity profiles control occurrence of clouds, which in turn has a large impact on radiative fluxes in the Antarctic. In addition, humidity profiles strongly interact with surface moisture fluxes, which are an important component in the water cycle. Despite their important role in the climate system, specific and relative humidity profiles in the Antarctic have not so far been comprehensively studied. Here, we address the vertical structure of tropospheric specific and relative humidity in the area south of 50&amp;#176;S and focus on interactions of this structure with horizontal and vertical moisture transport and surface fluxes of sensible and latent heat. The study is based on ERA5 reanalysis data from 15-years period, 2004 - 2018.&amp;#160;&lt;/p&gt;&lt;p&gt;We show that in the Antarctic, both moisture transport and surface fluxes shape the vertical structure of specific and relative humidity, but their relative contributions and effects vary considerably between regions. Therefore, we examined humidity profiles dividing the study area into five sub-regions: 1) open sea, 2) seasonal sea-ice area, 3) slopes of East Antarctica, 4) East Antarctica high plateau, and 5) West Antarctica. Expect west Antarctica, within each region the vertical structure of air moisture is relatively homogenous. Results indicate that each of these regions has own key processes (evaporation, condensation, vertical and horizontal moisture fluxes) controlling the vertical structure of relative and specific humidity.&lt;/p&gt;&lt;p&gt;The open ocean is a source area for atmospheric moisture. Over the open sea, a thin unsaturated well-mixed layer is seen near the surface, which is caused by year-around upward moisture flux (evaporation) and upward sensible heat flux. Above this layer, there is a layer of high relative humidity and frequently occurring cloud cover. Over sea ice, seasonal variability is large. During most of the year, moisture surface fluxes over sea ice are small, near-surface relative humidity is high, and specific humidity inversions are frequent. In summer, however, evaporation over sea ice increases, near-surface relative humidity is lower, and humidity inversions are uncommon.&lt;/p&gt;&lt;p&gt;The high plateau is the area where absolutely dry air masses are formed, as a consequence of near-surface condensation and downward moisture transport. There, the near-surface air is often saturated with respect to ice, and strong but thin surface-based specific humidity inversions are present during most of the year. On the slopes, adiabatic warming, due to katabatic winds, causes decrease of relative humidity when the air mass is advected downwards from the plateau. This leads to relatively high surface evaporation and makes surface-based specific humidity inversions rarer.&lt;/p&gt;&lt;p&gt;This study comprehensively describes the vertical structure of relative and specific humidity in the Antarctic, and increases understanding on how this vertical structure interacts with moisture transport and surface fluxes. The results can further contribute to understanding of processes related to cloud formation and water cycle in the high southern latitudes.&lt;/p&gt;

scholarly journals Evapo-Transpiration calculated from the new regional climate projections data set DRIAS-2020 over France

2021 ◽  
Author(s):  
Sébastien Bernus ◽  
Lola Corre ◽  
Agathe Drouin ◽  
Genaro Saavedra Soriano ◽  
Pascal Simon ◽  
...  
Keyword(s):  
Relative Humidity ◽  
Agricultural Sector ◽  
Regional Climate ◽  
Specific Humidity ◽  
Climate Projections ◽  
Visible Radiation ◽  
Adaptation Measures ◽  
Data Set ◽  
Thermal Amplitude ◽  
Regional Climate Projections

&lt;p&gt;&amp;#160;&lt;strong&gt;Evapo-Transpiration calculated from the new regional climate projections data set DRIAS-2020 over France&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;Changes in climatic variables such as temperature, precipitation, relative humidity or solar radiation strongly affect the agricultural sector. Relevant indicators are strongly needed to quantify the expected impacts and implement adaptation measures. Information on the future trend of Evapo-Transpiration (ET) is one of the key issues in order to take up the water management challenge.&lt;/p&gt;&lt;p&gt;&lt;span&gt;In 2020, a new set of climate indicators based on regional climate projections corrected over France was produced and published on the French national climate service DRIAS (&lt;/span&gt;&lt;span&gt;www.drias-climat.fr&lt;/span&gt;&lt;span&gt;) and the associated report was published in January 2021. The latter portal provides climate information in a variety of graphical or numerical forms. The climate projections are based on the EURO-CORDEX ensemble and have been corrected using the ADAMONT method according to the SAFRAN reference data set.&lt;/span&gt;&lt;/p&gt;&lt;p&gt;ET is calculated from this new data set with the aim of making it freely available on the DRIAS portal. Various calculation methods are used and compared. First, ET is calculated upstream and downstream of the ADAMONT method. Second, different calculation procedures are tested for the FAO recommended formula. One uses the average specific humidity instead of minimum and maximum of daily relative humidity which are not available in all selected models. ET is also calculated using the Hargreaves proxy for the visible radiation based on the square root of the maximum daily thermal amplitude multiplied by a coefficient. Three different values were tested for this coefficient&amp;#160;: 0.16, 0.175 and 0.19.&lt;/p&gt;&lt;p&gt;These various ET are then analyzed with a view to quantify the influence of the calculation method on the resulting estimated trends.&lt;/p&gt;&lt;p&gt;&lt;span&gt;&lt;strong&gt;Authors&amp;#160;: &lt;/strong&gt;&lt;/span&gt;&lt;span&gt;BERNUS S.&lt;/span&gt;&lt;sup&gt;&lt;span&gt;1&lt;/span&gt;&lt;/sup&gt;&lt;span&gt;, CORRE L.&lt;/span&gt;&lt;sup&gt;&lt;span&gt;2&lt;/span&gt;&lt;/sup&gt;&lt;span&gt;, DROUIN A.&lt;/span&gt;&lt;sup&gt;&lt;span&gt;2&lt;/span&gt;&lt;/sup&gt;&lt;span&gt;, SAAVEDRA&lt;/span&gt;&lt;span&gt; SORIANO G.&lt;/span&gt;&lt;sup&gt;&lt;span&gt;3&lt;/span&gt;&lt;/sup&gt;&lt;span&gt;, SIMON P.&lt;/span&gt;&lt;sup&gt;&lt;span&gt;2&lt;/span&gt;&lt;/sup&gt;&lt;span&gt;, PRATS&amp;#160;S.&lt;/span&gt;&lt;sup&gt;&lt;span&gt;4&lt;/span&gt;&lt;/sup&gt;&lt;span&gt;, &lt;/span&gt;&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;&lt;sup&gt;&lt;em&gt;1 &lt;/em&gt;&lt;/sup&gt;&lt;em&gt;M&amp;#233;t&amp;#233;o-France, Direction de la Climatologie et des Services Climatiques, Toulouse, France, [email protected]&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;sup&gt;&lt;span&gt;&lt;em&gt;2&lt;/em&gt;&lt;/span&gt;&lt;/sup&gt;&lt;span&gt;&lt;em&gt;M&amp;#233;t&amp;#233;o-France, Direction de la Climatologie et des Services Climatiques, Toulouse, France, [email protected]&lt;/em&gt;&lt;/span&gt;&lt;/p&gt;&lt;p&gt;&lt;sup&gt;&lt;em&gt;3&lt;/em&gt;&lt;/sup&gt;&lt;em&gt;&amp;#201;cole des Mines, Antibes, France, [email protected]&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;sup&gt;&lt;em&gt;4&lt;/em&gt;&lt;/sup&gt;&lt;em&gt;M&amp;#233;t&amp;#233;o-France, Direction des Services M&amp;#233;t&amp;#233;orologiques, Toulouse, Franc&lt;/em&gt;&lt;em&gt;e, [email protected]&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;References&lt;/strong&gt;&amp;#160;:&lt;/p&gt;&lt;p&gt;FAO (1998). Crop evapotranspiration: Guidelines for computing crop water requirements. FAO Irrigation and drainage paper 56, Rome, Italy&lt;/p&gt;

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