Calculating average annual rainfall (AAR) and accumulated temperature

Two parameters were chosen for the primary assessment of climatic limitations: (1) AAR, as a measure of wetness and (2) accumulated temperature above 0 °C (AT0), as a measure of overall warmth. Accumulated temperature is measured above the selected threshold (0 °C) and over a specified period, such as the growing season (for AT0) or summer period (for accumulated temperature in summer (ATS)). Work on grass and cereals has shown that leaf extension can occur down to temperatures as low as 0 °C and this was therefore chosen as the threshold, while the period from January to June was determined to be the critical period for most crops in the UK. A single grade is given for the overall climate limitation, which combines the AAR and the AT0.

Annual summaries for rainfall and accumulated temperature above 0, 5·6 and 10 °C were calculated for each year in the period. The annual rainfall for each year was the sum of the monthly totals. The accumulated temperature function calculated how much of the minimum, maximum and mean temperatures, for each day, were above the given threshold and whether the record was between the specified dates using the method produced by the Meteorological Office (1969) and subsequently modified by Hallett & Jones (Reference Hallett and Jones1993). The function returned the daily effective temperature (measured as day-degrees above the threshold), which was then multiplied by the number of days in the month and accumulated over the required period. For AT0 and ATS, the threshold was set to 0 °C and the period was defined as January–June for AT0 and April–September for ATS.

The average (mean) annual rainfall and the median accumulated temperature (AT0) and median ATS was calculated for each of the 30-year periods, 1921–50, 1931–60, 1941–70, 1951–80, 1961–90 and 1971–2000. Monthly average rainfall (January–December) was also calculated to show seasonal changes.

Calculating evapotranspiration

The climate data provided by UKCP09 included all the variables required to make a reasonable approximation of evapotranspiration using the Penman–Monteith equation (Allen et al. Reference Allen, Periera, Raes and Smith1998). The methodology used to calculate the evapotranspiration from the available climate variables is described in detail in Hess (Reference Hess2000):

(1)$$\eqalign{{\rm ETo} = & \left[ {\displaystyle{{\rm \Delta} \over {{\rm \Delta} + \gamma ^ *}} \times \displaystyle{{(R_\eta - G)} \over \lambda}} \right] \cr & + \left[ {\displaystyle{{86{\cdot}4} \over \lambda} \times \displaystyle{1 \over {{\rm \Delta} + \gamma ^ *}} \times \displaystyle{{\rho cp} \over {{\rm ra}}}\left( {{\rm ea} - {\rm ed}} \right)} \right]} $$

where ETo is the reference crop evapotranspiration (mm/d), Δ is the slope of vapour pressure curve (MJ/kg) – ƒ(temp, VP), γ^* is the modified psychrometric constant (kPa/°C) – ƒ(temp, wind, altitude), Rn is the net solar radiation (MJ/m²/d) – ƒ(temp, VP, sun), G is the soil heat flux (MJ/m²/d) – set to 0 for monthly data, λ is the latent heat of vaporization – ƒ(temp), ρ is the atmospheric density (kg/m³) – ƒ(temp, altitude), cp is the specific heat of moist air (1·013 kJ/kg/°C), ra is the aerodynamic resistance (s/m) – ƒ(wind), ea is the mean saturation vapour pressure (kPa) – ƒ(temp) and ed is the actual vapour pressure (kPa) – ƒ(VP).

It was necessary to estimate the missing values for vapour pressure (1914–60), windspeed (1914–68) and sunshine hours (1914–28) to produce a contiguous dataset. Analysis of the vapour pressure records from 1961 to 2000 showed a strong relationship between VP and T _min (Fig. 1).

(2)$$VP = 6{\cdot}6932 \ {\rm e}^{0.0671 \ {T_{\min}}} $$

This formula was used to populate the missing VP records from 1914 to 1960.

Fig. 1.

Vapour pressure related to minimum temperature from UKCP09 monthly data from 1961 to 2000.

The wind speed was measured at a height of 10 m above ground and thus for the purpose of the Penman–Monteith method it was adjusted down to the reference height of 2 m. Wind speed was variable and there was no strong relationship with any of the other variables. In order to distinguish the exposed areas of Britain, such as the hills and coasts, from the less windy regions, the average windspeed was calculated for each individual grid point from the 1969–2000 records and this value was then used to populate the records before this date. The missing sunshine records from 1914 to 1928 were estimated by calculating the average sunshine by month using regression to determine a polynomial equation.

Calculating potential soil moisture deficit (PSMD)

The degree of drought in a soil is influenced by three factors: rainfall amount, evapotranspiration and the store of water available in the soil. The ALC method to assess droughtiness is based on the concept of PSMD, which describes the balance of rainfall and potential evapotranspiration from a green crop that completely covers the ground during the growth cycle (Thomasson Reference Thomasson, Jarvis and Mackney1979). MD in the soil builds up over the summer months in most of lowland Britain, the potential evapotranspiration increasing progressively from spring onwards and peaking in July or August, resulting in a maximum recorded soil MD.

For calculating ALC grade, the PSMD is adjusted for two reference crops, winter wheat and main crop potatoes, representative of a broad range of crops in terms of their susceptibility to drought (MAFF 1988). In 1983, the crop adjusted soil MDs was calculated for 94 stations in the ‘Complete’ Agromet Data set (Field Reference Field1983) from 1961 to 1980 and subsequently extended to include a further 25 sites in Scotland and 2 sites in Northern Ireland (Harvey Reference Harvey1983). From these records, regression equations allowed MD for wheat and potatoes to be calculated from the ATS and the average summer rainfall (ASR). The ATS value was derived from a regression equation based on the AT0. To calculate the droughtiness of the soil, the crop-specific MD (mm) is subtracted from the water available to that crop in the soil (AP). Four classes of drought are defined (Table 1).

Table 1.

Classes of soil droughtiness

AP, available water in the soil profile; MD, moisture deficit.

PSMD was calculated for each month in each year throughout the period. The monthly MD equals the MD for the previous month plus the amount that potential evapotranspiration exceeds rainfall. When the balance rises above 0 (i.e. there is a moisture surplus) it is reset to 0. This calculation represents a potential climatic deficit but the actual deficit is modified by the amount of water available in the soil. For example, following a dry autumn some areas in eastern England may still experience potential deficit in January and February of the following year but to carry this deficit into the next spring period would distort the calculations in the following year. Therefore the PSMD is reset to 0 at the end of February each year. Over the 87-year period the annual maximum PSMD showed a skewed distribution with very high values in a few years. To compensate for these extreme years, the median PSMD value was used to describe the PSMD for each 30-year period.

The crop-adjusted MD under wheat and potatoes can be calculated by two methods. The first method calculates PSMD from the relationships with specific monthly PSMD values – see Eqns (3) and (4) below (Jones & Thomasson Reference Jones and Thomasson1985). For winter wheat, it is assumed that the crop requires only one-third of the MD until full ground cover is achieved, normally at the end of April, and the crop does not require water from the soil once it has reached the ripening stage of its growth, usually around mid-July:

(3)$$\eqalign{{\rm MDWHT =\ } & {\rm mid {\hbox{-}} July} \ {\rm PSMD} \cr & -{\rm 1}/{\rm 3} \ {\rm April} \ {\rm PSMD}} $$

Main crop potatoes can be considered to be under bare-ground conditions until mid-May, with full crop cover achieved around the end of June and growth continuing in August through the period of maximum deficit:

(4)$$\eqalign{{\rm MDPOT} = \ & {\rm August} \ {\rm PSMD} - {\rm 1}/{\rm 3} \ {\rm June} \ {\rm PSMD} \cr & - \ {\rm 1}/{\rm 3} \ {\rm mid {\hbox{-}} May} \ {\rm PSMD}} $$

The second method calculates potential moisture deficit under wheat (MDMWHT) and potatoes (MDMPOT) (Meteorological Office 1989) from relationships with ASR (April–September) and ATS from station data between 1960 and 1980 as follows:

(5)$$\eqalign{{\rm MDMWHT} = \ & {\rm 325} {\cdot} {\rm 4}-{\rm 162} {\cdot} {\rm 3 \log10}{\rm ASR} \cr & + 0 {\cdot} 0{\rm 8}0{\rm 22ATS}} $$

(6)$$\eqalign{{\rm MDMPOT} = \ & {\rm 326} {\cdot} {\rm 4} - {\rm 196} {\cdot} {\rm 5 \log10}{\rm ASR} \cr & + 0 {\cdot} {\rm 1127ATS}} $$

The PSMD values computed using the first method are much more extreme than using the second method and are likely to be the result of differences in the calculation of ETo. The original ETo data were calculated using a pre-Penman–Monteith method, which produced smaller MD values than the Penman–Monteith equation adopted for The Met Office Rainfall and Evaporation Calculation System (MORECS) (Thompson et al. Reference Thompson, Barrie and Ayles1981). However, deficiencies in the original documentation make it difficult to duplicate the original methods. The ranges of values go beyond the original data used to formulate the regression equations, so it could be argued that it may be inappropriate to adopt the regression methods. However, the methods that use the ETo derived using Penman–Monteith in the PSMD calculations result in a larger number of sites being limited by droughtiness than is appropriate for the UK. Thus, droughtiness calculated using the second method was selected over the first method as it was a better fit to the known pattern of drought in the UK.

Calculating FC days

The wetness component of the climatic regime is determined from the FCD. The start and end dates of FC are probably the most difficult of all the agroclimatic parameters to predict. A soil is said to be at FC when it holds the maximum amount of water against the force of gravity (Veihmeyer & Hendrickson Reference Veihmeyer and Hendrickson1931), which in a meteorological sense is when the soil is at zero MD. Soil MDs were originally determined by Smith (Reference Smith1967) from the ‘actual’ MD over the year calculated from the balance of bi-weekly rainfall and monthly potential transpiration. Smith used a simple water abstraction model to limit transpiration from the soil to take into account the fact that water is retained at stronger and stronger suctions in most soil material as it dries out. The start of the FC period was determined from the date at which the soil water was no longer in deficit, i.e. there was a water surplus in the soil. This state is often achieved in the autumn on agricultural land, but in drier areas of south-east England, for example, it can be as late as the end of November in a normal year. In the wettest areas at higher elevation, the soil can remain at FC throughout the year, e.g. >500 m asl in northern Wales and north-west England. Once the soil reaches FC it can fluctuate in and out for a few days or weeks, depending on the weather, but eventually settles down through the winter until the temperatures begin to increase in the spring; the soil once again begins to dry out and a soil MD develops.

In 1971, the start and end dates of FC were calculated for 97 sample stations across the country (Smith Reference Smith1971). From these analyses, estimates of the start and end dates of FC were developed from algorithms based on actual soil MD at the end of specific months and the annual average rainfall classified into four zones. The country was divided into 70 areas of similar climate and a full range of agroclimatic parameters were determined for each of these zones using meteorological station data from 1941 to 1970 (Smith Reference Smith1976). For ALC purposes, regression algorithms were developed from these data to calculate the start and end dates of FC from the AAR and altitude (Jones & Thomasson Reference Jones and Thomasson1985). Spatial coverage on a 10 km, and subsequently 5 km, grid was developed and the start and end dates adjusted by the residual difference between the equation and the measured value at the nearest climate station (Ragg et al. Reference Ragg, Jones and Proctor1988).

Calculating the start and end dates of FC from the raw monthly water balance data was contemplated, but it was decided that this was too crude as daily data are really needed to give a better estimate; thus regression functions (Table 2) were developed that related the FC data to the easting, northing and AAR (Jones & Thomasson Reference Jones and Thomasson1985). In the original ALC exercise in 1989, the regression value at each 5 km point was adjusted for the residual difference derived from measured values at the nearest weather station. To maintain continuity with the original methods, the FC dates, obtained by regression, were adjusted by the difference between the AAR of the original data (1941–70) and the AAR of the UKCP09 data multiplied by the coefficient for AAR from the original regression equation:

(7)$$\eqalign{{\rm xFC}_{({\rm ukcp}0{\rm 9})} = \ & {\rm xFC}_{({\rm original})} \times {\rm AARcoeff} \cr & \hskip -3.5pt\times {\rm} ({\rm AAR}_{({\rm ukcp}0{\rm 9})} -{\rm AAR}_{{\rm (original)}} {\rm )}} $$

Table 2.

Field capacity parameters for original 5 km dataset (Dr Robert Jones, personal communication)

Rfc, return to field capacity; Efc, end of field capacity.

Calculating wetness class

Soil wetness adversely affects seed germination and survival, and restricts the development of a good root system. It reduces the temperature of the soil and causes anaerobic conditions. The wetness of the soil also affects the sensitivity of the soil to structural damage influencing the number of days when the site is accessible to farm machinery or livestock grazing. Soil wetness is assessed by a combination of the climatic regime, the soil water regime and the texture of the top 250 mm of the soil.

The soil–water regime was determined using soil wetness classes (I–VI) (Hodgson Reference Hodgson1976) based on the depth and duration of water-logging measured by field-based monitoring of dipwell levels (Robson & Thomasson Reference Robson and Thomasson1977; Jones Reference Jones1985). The scale ranges from class I, where the soil is not wet within 0·70 m for more than 30 days in a year (and is usually recognized by the lack of any mottling due to reducing conditions), to class VI, where the soil is wet within the top 0·40 m for more than 335 days in most years. For ALC purposes, wetness class of a soil is assessed by a decision-tree approach based on the climate region (FC day zone), the presence or absence of a slowly permeable layer or gleying within specified depths, whether the site is disturbed, and whether the soil is peaty, an organo-mineral or a red soil (MAFF 1988).

The wetness class at each of the NSI locations was calculated using the relevant duration of FC, the texture and the depth of the profile to a gleyed or an impermeable horizon (if it is within 1·50 m), following the method for calculating wetness class provided by MAFF (1988).

Calculating the ALC classification

Once a complete set of agroclimatic data had been created for each of the six 30-year periods, the ALC classification could be applied and the differences resulting from changes in the climate assessed. For this exercise, the climate data for the NSI point (McGrath & Loveland Reference McGrath and Loveland1992) were taken from the data of the 5 km cell in which it resides rather than interpolating the data from the four surrounding sites and adjusting for the altitude difference at the NSI point as described in the original ALC methodology (Meteorological Office 1989).

Functions were derived to calculate each of the 10 ALC criteria being assessed in this exercise.

Climate was calculated from AAR and AT0 using an equation describing each of the five curves which separate the six classes (Fig. 2).

Fig. 2.

ALC grade according to climate.

Drought was assessed by taking the available water of the soil profile identified at the NSI site and subtracting the MD at the location for wheat and potatoes and selecting the grade using the defined limits (Table 3).

Table 3.

Grade according to droughtiness

Wetness was assessed from the FCD, topsoil texture and wetness class of the soil, where wetness class was calculated using the FCD and soil properties from the NSI profile data.

The gradient of the site affects the ability of machinery to operate safely and efficiently and steeper slopes are also at increased risk of soil erosion. When assessing local sites it is also relevant to consider aspects of micro relief, such as rock outcrops or an intensely undulating landscape, which would reduce its manageability. The risk of flooding is assessed on the history of floods, and their duration and frequency at the site. This information is not available for the NSI sites, but, where a site is identified as being on an alluvial soil type this is taken as evidence that the land has been prone to flooding in the past and the ALC classification is therefore limited to ALC Grade 2 at best. Soil texture affects workability and the water available to plants and is therefore used to determine the soil droughtiness and wetness. In addition to these criteria, soils with sandy topsoils are restricted to Grade 3b or below and loamy sands are limited to Grade 2 due to rapid drying effects. The soil depth influences the available water capacity of the soil, crop growth and cultivation (Table 4).

Table 4.

Grade according to soil depth

The stoniness of the topsoil affects the mechanical cultivation and harvesting possibilities at a site as well as reducing the available water in a soil. Therefore the abundance and size of stones in the top 250 mm is used to grade the site. The effect of soil toxicity is also considered, and for the NSI sites the levels of five key elements have been measured: lead, cadmium, zinc, copper and nickel; on sites where these elements exceed a given threshold (Table 5) then the site is automatically limited to Grade 3b (CEC 1986). The last criterion considered by the ALC classification is the presence of soil erosion at the site. This was assessed by the surveyors at the NSI site and documented, if the wind or water erosion was considered significant. If evidence of erosion was recorded, a site was limited to Grade 2.

Table 5.

Threshold limits for heavy metals (ppm) (DOE, 1996, Table 4, p6)

After all 10 criteria were assessed the most limiting criteria was selected as the overall ALC grade for each site. The most limiting factor(s) which resulted in the overall ALC grade was also recorded.